Philosophical Disquisitions: Recent Episodes
John Danaher
In this episode, John and Sven answer questions from podcast listeners. Topics covered include: the relationships between animal ethics and AI ethics; religion and philosophy of tech; the analytic-continental divide; the debate about short vs long-term risks; getting engineers to take ethics seriously and much much more. Thanks to everyone that submitted a question.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
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What does the future hold for humanity's relationship with technology? Will we become ever more integrated with and dependent on technology? What are the normative and axiological consequences of this? In this episode, Sven and John discuss these questions and reflect, more generally, on technology, ethics and the value of speculation about the future.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommended Reading
- Mark Coeckelbergh The Political Philosophy of AI
- David Chalmers Reality+
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In this episode, Sven and John talk about relationships with machines. Can you collaborate with a machine? Can robots be friends, colleagues or, perhaps, even lovers? These are common tropes in science fiction and popular culture, but is there any credibility to them? What would the ethical status of such relationships be? Should they be welcomed or avoided? These are just some of the questions addressed in this episode.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommended Reading
- Evans, Robbins and Bryson - 'Do we collaborate with what we design?'
- Helen Ryland - 'It's Friendship Jim But Not as We Know It: A Degrees-of-Friendship View of Human–Robot Friendships'
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In this episode Sven and John discuss the moral status of machines, particularly humanoid robots. Could machines ever be more than mere things? Some people see this debate as a distraction from the important ethical questions pertaining to technology; others take it more seriously. Sven and John share their thoughts on this topic and give some guidance as to how to think about the nature of moral status and its significance.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommended Reading
- David Gunkel, Person, Thing, Robot
- Butlin, Long et al 'Consciousness in AI: Insights from the Science of Consciousness'
- Summary of the above paper from Daily Nous.
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In this episode, Sven and John discuss the controversy arising from the idea moral agency in machines. What is an agent? What is a moral agent? Is it possible to create a machine with a sense of moral agency? Is this desirable or to be avoided at all costs? These are just some of the questions up for debate.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommended Reading
- Amanda Sharkey, 'Can we program or train robots to be good?'
- Paul Formosa and Malcolm Ryan, 'Making Moral Machines: Why we need artificial moral agents?'
- Michael Anderson and Susan Leigh Anderson, 'Machine ethics: creating an ethical intelligent agent'
- Carissa Véliz, 'Moral zombies: why algorithms are not moral agents'
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In this episode Sven and John discuss the thorny topic of responsibility gaps and technology. Over the past two decades, a small cottage industry of legal and philosophical research has arisen in relation to the idea that increasingly autonomous machines create gaps in responsibility. But what does this mean? Is it a serious ethical/legal problem? How can it be resolved? All this and more is explored in this episode.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommended Reading
- Robert Sparrow 'Killer Robots'
- Alexander Hevelke and Julian Nida-Rümelin, "Responsibility for Crashes of Autonomous Vehicles"
- Andreas Matthias 'The Responsibility Gap: Ascribing Responsibility for the Actions Learning Automata'
- Jack Stilgoe 'Who's Driving Innovation', Chapter 1
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To get a discounted copy of Sven’s book, click here and use the code ‘TEC20’ to get 20% off the regular price.
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In this episode, John and Sven talk about the role that technology can play in changing our behaviour. In doing so, they note the long and troubled history of philosophy and self-help. They also ponder whether we can use technology to control our lives or whether technology controls us.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommendations
- Brett Frischmann and Evan Selinger, Reengineering Humanity.
- Carissa Véliz, Privacy is Power.
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In this episode, John and Sven discuss risk and technology ethics. They focus, in particular, on the perennially popular and widely discussed problems of value alignment (how to get technology to align with our values) and control (making sure technology doesn't do something terrible). They start the conversation with the famous case study of Stanislov Petrov and the prevention of nuclear war.
You can listen below or download the episode here. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommendations for further reading Atoosa Kasirzadeh and Iason Gabriel, 'In Conversation with AI: Aligning Language Models with Human Values' * Nick Bostrom, relevant chapters from Superintelligence * Stuart Russell, Human Compatible * Langdon Winner, 'Do Artifacts Have Politics?' * Iason Gabriel, 'Artificial Intelligence, Values and Alignment' * Brian Christian, The Alignment Problem*
DiscountYou can purchase a 20% discounted copy of This is Technology Ethics by using the code TEC20 at the publisher's website.
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In this episode, John and Sven discuss the methods of technology ethics. What exactly is it that technology ethicists do? How can they answer the core questions about the value of technology and our moral response to it? Should they consult their intuitions? Run experiments? Use formal theories? The possible answers to these questions are considered with a specific case study on the ethics of self-driving cars. You can listen below or download the episode here. You can also subscribe to the podcast on Apple, Spotify, Google, Amazon and a range of other podcasting services.
Recommended Reading * Peter Königs 'Of Trolleys and Self-Driving Cars:What machine ethicists can and cannot learn from trolleyology' * John Harris 'The Immoral Machine' * Edmond Awad et al 'The Moral Machine Experiment'
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You can purchase a 20% discounted copy of This is Technology Ethics by using the code TEC20 at the publisher's website.
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I am very excited to announce the launch of a new podcast series with my longtime friend and collaborator Sven Nyholm. The podcast is intended to introduce key themes, concepts, arguments and ideas arising from the ethics of technology. It roughly follows the structure from the book This is Technology Ethics by Sven , but in a loose and conversational style. In the nine episodes, we will cover the nature of technology and ethics, the methods of technology ethics, the problems of control, responsibility, agency and behaviour change that are central to many contemporary debates about the ethics of technology. We will also cover perennially popular topics such as whether a machine could have moral status, whether a robot could (or should) be a friend, lover or work colleague, and the desirability of merging with machines.The podcast is intended to be accessible to a wide audience and could provide an ideal companion to an introductory or advanced course in the ethics of technology (with particular focus on AI, robotics and other digital technologies).
I will be releasing the podcast on the Philosophical Disquisitions podcast feed, but I have also created an independent podcast feed and website, if you are just interested in it. The first episode can be downloaded here or you can listen below. You can also subscribe on Apple, Spotify, Amazon and a range of other podcasting services.
If you go the website or subscribe via the standalone feed, you can download the first two episodes now. There is also a promotional tie with the book publisher. If you use the code 'TEC20' on the publisher's website (here) you can get 20% off the regular price.
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In this episode, I chat to Matthijs Maas about pausing AI development. Matthijs is currently a Senior Research Fellow at the Legal Priorities Project and a Research Affiliate at the Centre for the Study of Existential Risk at the University of Cambridge. In our conversation, we focus on the possibility of slowing down or limiting the development of technology. Many people are sceptical of this possibility but Matthijs has been doing some extensive research of historical case studies of, apparently successful, technological slowdown. We discuss these case studies in some detail.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
Relevant Links* Recording of Matthijs's Chalmers about this topic: https://www.youtube.com/watch?v=vn4ADfyrJ0Y&t=2s * Slides from this talk -- https://drive.google.com/file/d/1J9RW49IgSAnaBHr3-lJG9ZOi8ZsOuEhi/view?usp=share_link * Previous essay / primer, laying out the basics of the argument: https://verfassungsblog.de/paths-untaken/ * Incomplete longlist database of candidate case studies: https://airtable.com/shrVHVYqGnmAyEGsz
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In this episode of the podcast I chat to Atoosa Kasirzadeh. Atoosa is an Assistant Professor/Chancellor's fellow at the University of Edinburgh. She is also the Director of Research at the Centre for Technomoral Futures at Edinburgh. We chat about the alignment problem in AI development, roughly: how do we ensure that AI acts in a way that is consistent with human values. We focus, in particular, on the alignment problem for language models such as ChatGPT, Bard and Claude, and how some old ideas from the philosophy of language could help us to address this problem.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
Relevant Links* Atoosa's webpage * Atoosa's paper (with Iason Gabriel) 'In Conversation with AI: Aligning Language Models with Human Values'
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In this episode I chat to Miles Brundage. Miles leads the policy research team at Open AI. Unsurprisingly, we talk a lot about GPT and generative AI. Our conservation covers the risks that arise from their use, their speed of development, how they should be regulated, the harms they may cause and the opportunities they create. We also talk a bit about what it is like working at OpenAI and why Miles made the transition from academia to industry (sort of). Lots of useful insight in this episode from someone at the coalface of AI development.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode of the podcast I chat to Jess Morley. Jess is currently a DPhil candidate at the Oxford Internet Institute. Her research focuses on the use of data in healthcare, oftentimes on the impact of big data and AI, but, as she puts it herself, usually on 'less whizzy' things. Sadly, our conversation focuses on the whizzy things, in particular the recent hype about large language models and their potential to disrupt the way in which healthcare is managed and delivered. Jess is sceptical about the immediate potential for disruption but thinks it is worth exploring, carefully, the use of this technology in healthcare.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
Relevant Links* Jess's Website * Jess on Twitter * John Snow's cholera map Subscribe to the newsletter
In this episode, I chat to Robert Long about AI sentience. Robert is a philosopher that works on issues related to the philosopy of mind, cognitive science and AI ethics. He is currently a philosophy fellow at the Centre for AI Safety in San Francisco. He completed his PhD at New York University. We do a deep dive on the concept of sentience, why it is important, and how we can tell whether an animal or AI is sentient. We also discuss whether it is worth taking the topic of AI sentience seriously.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
Relevant Links* Robert's webpage * Robert's substack Subscribe to the newsletter
In this episode of the podcast, I talk to Thore Husfeldt about the impact of GPT on education. Thore is a Professor of Computer Science at the IT University of Copehagen, where he specialises in pretty technical algorithm-related research. He is also affiliated with Lund University in Sweden. Beyond his technical work, Thore is interested in ideas at the intersection of computer science, philosophy and educational theory. In our conversation, Thore outlines four models of what a university education is for, and considers how GPT disrupts these models. We then talk, in particular, about the 'signalling' theory of higher education and how technologies like GPT undercut the value of certain signals, and thereby undercut some forms of assessment. Since I am an educator, I really enjoyed this conversation, but I firmly believe there is much food for thought in it for everyone.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode of the podcast, I chat to Anton Korinek about the economic impacts of GPT. Anton is a Professor of Economics at the University of Virginia and the Economics Lead at the Centre for AI Governance. He has researched widely on the topic of automation and labour markets. We talk about whether GPT will substitute for or complement human workers; the disruptive impact of GPT on the economic organisation; the jobs/roles most immediately at risk; the impact of GPT on wage levels; the skills needed to survive in an AI-enhanced economy, and much more.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
Relevant Links* Anton's homepage * Anton's paper outlining 25 uses of LLMs for academic economists * Anton's dialogue with GPT, Claude and the economic David Autor Subscribe to the newsletter
In this episode of the podcast, I chat to Olle Häggström. Olle is a professor of mathematical statistics at Chalmers University of Technology in Sweden. We talk about GPT and LLMs more generally. What are they? Are they intelligent? What risks do they pose or presage? Are we proceeding with the development of this technology in a reckless way? We try to answer all these questions, and more.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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How should we conceive of social robots? Some sceptics think they are little more than tools and should be treated as such. Some are more bullish on their potential to attain full moral status. Is there some middle ground? In this episode, I talk to Paula Sweeney about this possibility. Paula defends a position she calls 'fictional dualism' about social robots. This allows us to relate to social robots in creative, human-like ways, without necessarily ascribing them moral status or rights. Paula is a philosopher based in the University of Aberdeen, Scotland. She has a background in the philosophy of language (which we talk about a bit) but has recently turned her attentio n to applied ethics of technology. She is currently writing a book about social robots.
You download the episode here, or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services.
Relevant Links* A Fictional Dualism Model of Social Robots by Paula * Trusting Social Robots by Paula * Why Indirect Harms do Not Support Social Robot Rights by Paula Subscribe to the newsletter
It's clear that human social morality has gone through significant changes in the past. But why? What caused these changes? In this episode, I chat to Jeroen Hopster from the University of Utrecht about this topic. We focus, in particular, on a recent paper that Jeroen co-authored with a number of colleagues about four historical episodes of moral change and what we can learn from them. That paper, from which I take the title of this podcast, was called 'Pistols, Pills, Pork and Ploughs' and, as you might imagine, looks at how specific technologies (pistols, pills, pork and ploughs) have played a key role in catalysing moral change.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
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In this episode (which by happenstance is the 100th official episode - although I have released more than that) I chat to Elise Bohan. Elise is a senior research scholar at the Future of Humanity Institute in Oxford University. She has a PhD in macrohistory ("big" history) and has written the first book-length history of the transhumanist movement. She has also, recently, published the book Future Superhuman, which is a guide to transhumanist ideas and arguments. We talk about this book in some detail, and cover some of its more controversial claims.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
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In this episode I chat to Matthias Uhl. Matthias is a professor of the social and ethical implications of AI at the Technische Hochschule Ingolstadt. Matthias is a behavioural scientist that has been doing a lot of work on human-AI/Robot interaction. He focuses, in particular, on applying some of the insights and methodologies of behavioural economics to these questions. We talk about three recent studies he and his collaborators have run revealing interesting quirks in how humans relate to AI decision-making systems. In particular, his findings suggesting that people do outsource responsibility to machines, are willing to trust untrustworthy machines and prefer the messy discretion of human decision-makers over the precise logic of machines. Matthias's research is fascinating and has some important implications for people working in AI ethics and policy.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Relevant Links* Matthias's Faculty Page * 'Hiding Behind Machines: Artificial Agents May Help to Evade Punishment' by Matthias and colleagues * 'Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions' by Matthias and colleagues * 'People Prefer Moral Discretion to Algorithms: Algorithm Aversion Beyond Intransparency' by Matthias and colleagues Subscribe to the newsletter
In this episode (the last in this series for the time being) I chat to Olle Häggström. Olle is a professor of mathematical statistics at Chalmers University of Technology in Sweden. Having spent the first half of his academic life focuses largely on pure mathematical research, Olle has shifted focus in recent years to consider how research can benefit humanity and how some research might be too risky to pursue. We have a detailed conversation about the ethics of research and contrast different ideals of what it means to be a scientist in the modern age. Lots of great food for thought in this one.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode I chat to Jessica Flanigan. Jessica is a Professor of Leadership Ethics at the University of Richmond, where she is also the Richard L Morrill Chair in Ethics & Democratic Values. We talk about the value of philosophical research, whether philosophers should emulate Socrates, and how to create good critical discussions in the classroom. I particularly enjoyed hearing Jessica's ideas about effective teaching and I think everyone can learn something from them.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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Is grading unethical? Coercive and competitive? Should we replace grading with something else? In this podcast I chat to Jesse Stommel, one of the foremost proponents of 'ungrading'. Jesse is a faculty member of the writing program at the University of Denver and is the founder of the Hybrid Pedagogy journal. We talk about the problem with traditional grading systems, the idea of ungrading, and how to create communities of respect in the classroom.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode I talk to Jason Brennan. Jason is a Professor of Strategy, Economics, Ethics, and Public Policy at the McDonough School of Business at Georgetown University. He is a prolific and productive scholar, having published over 20 books and 70 articles in the past decade or so. His research focuses on the intersections between politics, economics and philosophy. He has written quite a bit about the moral failures and conundrums of higher education, which makes him an ideal guest for this podcast. We talk about the purpose of research, the ethics of productivity, the problem with PhD programmes and the plight of adjuncts.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode I chat to Zena Hitz. Zena is currently a tutor at St John's College. She is a classicist and author of the book Lost in Thought. We have wide-ranging conversation about losing faith in academia, the dubious value of scholarship, the importance of learning, and the risks inherent in teaching. I learned a lot talking to Zena and found her perspective on the role of academics and educators to be enlightening.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode I chat to Aaron Rabinowitz. Aaron is a veteran podcaster and philosopher. He hosts the Embrace the Void and Philosophers in Space podcasts. He is currently doing a PhD in the philosophy of education at Rutgers University. Aaron is particularly interested in the problem of moral luck and how it should affect our approach to education. This was a fun conversation. Stay tuned for the Schopenhauer thought experiment around the 40 minute mark!
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode I chat to Helen de Cruz. Helen is the Danforth Chair in Humanities at the University of St. Louis. Helen has a diverse set of interests and outputs. Her research focuses on the philosophy of belief formation, but she also does a lot of professional and public outreach, writes science fiction, and plays the lute. If that wasn't impressive enough, she is also a very talented illustrator/artist, as can be seen from her book Philosophy Illustrated. We have a wide-ranging conversation about the ethics of research, teaching, public outreach and professional courtesy. Some of the particular highlights from the conversation are her thoughts on prestige bias in academia and the crisis of peer reviewing.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode I chat to Brian Earp. Brian is a Senior Research Fellow with the Uehiro Centre for Practical Ethics in Oxford. He is a prolific researcher and writer in psychology and applied ethics. We talk a lot about how Brian ended up where he is, the value of applied research and the importance of connecting research to the real world.
You can download the episode here or listen below. You can also subscribe the podcast on Apple, Spotify, Google, Amazon or whatever your preferred service might be.
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In this episode of the Ethics of Academia, I chat to Justin Weinberg, Associate Professor of Philosophy at University of South Carolina. Justin researches ethical and social philosophy, as well as metaphilosophy. He is also the editor of the popular Daily Nous blog and has, as a result, developed an interest in many of the moral dimensions of philosophical academia. As a result, our conversation traverses a wide territory, from the purpose of philosophical research to the ethics of grading.
You can download the episode here or listen below. You can also subscribe on Apple, Spotify, Google or any other preferred podcasting service.
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In this episode I talk to Regina Rini, Canada Research Chair at York University in Toronto. Regina has a background in neuroscience and cognitive science but now works primarily in moral philosophy. She has the distinction of writing a lot of philosophy for the public through her columns for the Time Literary Supplement and the value of this becomes a major theme of our conversation.
You can download the episode here or listen below. You can also subscribe on Apple, Spotify and other podcasting services.
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This is the second episode in my short series on The Ethics of Academia. In this episode I chat to Michael Cholbi, Professor of Philosophy at the University of Edinburgh. We reflect on the value of applied ethical research and the right approach to teaching. Michael has thought quite a lot about the ethics of work, in general, and the ethics of teaching and grading in particular. So those become central themes in our conversation.
You can download the podcast here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
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I have been reflecting on the ethics of academic life for some time. I've written several articles about it over the years. These have focused on the ethics of grading, student-teacher relationships, academic career choice, and the value of teaching (among other things). I've only scratched the surface. It seems to me that academic life is replete with ethical dilemmas and challenges. Some systematic reflection on and discussion of those ethical challenges would seem desirable. Obviously, there is a fair bit of writing available on the topic but, as best I can tell, there is no podcast dedicated to it. So I decided to start one.
I'm launching this podcast as both an addendum to my normal podcast (which deals primarily with the ethics of technology) and as an independent podcast in its own right. If you just want to subscribe to the Ethics of Academia, you can do so here (Apple and Spotify). (And if you do so, you'll get the added bonus of access to the first three episodes). I intend this to be a limited series but, if it proves popular, I might come back to it.
In the first episode, I chat to Sven Nyholm (Utrecht University) about the ethics of research, teaching and administration. Sven is a longtime friend and collaborator. He has been one of my most frequent guests on my main podcast so he seemed like the ideal person to kickstart this series. Although we talk about a lot of different things, Sven draws particular attention to the ethical importance of the division of labour in academic life.
You can download the episode here or listen below.
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How easily do we anthropomorphise robots? Do we see them as moral agents or, even, moral patients? Can we dehumanise them? These are some of the questions addressed in this episode with my guests, Dennis Küster and Aleksandra Świderska. Dennis is a postdoctoral researcher at the University of Bremen. Aleksandra is a senior researcher at the University of Warsaw. They have worked together on a number of studies about how humans perceive and respond to robots. We discuss several of their joint studies in this episode.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Relevant Links* Dennis's webpage * Aleksandra's webpage * 'I saw it on YouTube! How online videos shape perceptions of mind, morality, and fears about robots' by Dennis, Aleksandra and David Gunkel * 'Robots as malevolent moral agents: Harmful behavior results in dehumanization, not anthropomorphism' by Aleksandra and Dennis * 'Seeing the mind of robots: Harm augments mind perception but benevolent intentions reduce dehumanisation of artificial entities in visual vignettes' by Dennis and Aleksandra Subscribe to the newsletter
One particularly important social institution is the police force, who are increasingly using technological tools to help efficiently and effectively deploy policing resources. I’ve covered criticisms of these tools in the past, but in this episode, my guest Daniel Susser has some novel perspectives to share on this topic, as well as some broader reflections on how humans can relate to machines in social decision-making. This one was a lot of fun and covered a lot of ground.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Relevant Links* Daniel's Homepage * Daniel on Twitter * 'Predictive Policing and the Ethics of Preemption' by Daniel * 'Strange Loops: Apparent versus Actual Human Involvement in Automated Decision-Making' by Daniel (and Kiel Brennan-Marquez and Karen Levy) Subscribe to the newsletter
It is common to think that technology is morally neutral. “Guns don’t kill people; people kill people’ - as the typical gun lobby argument goes. But is this really the right way to think about technology? Could it be that technology is not so neutral as we might suppose? These are questions I explore today with my guest Olya Kudina. Olya is an ethicist of technology focusing on the dynamic interaction between values and technologies. Currently, she is an Assistant Professor at Delft University of Technology.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Relevant Links Olya's Homepage * Olya on Twitter * The technological mediation of morality: value dynamism, and the complex interaction between ethics and technology -* Olya's PhD Thesis * 'Ethics from Within: Google Glass, the Collingridge Dilemma, and the Mediated Value of Privacy' by Olya and Peter Paul Verbeek * "Alexa, who am I?”: Voice Assistants and Hermeneutic Lemniscate as the Technologically Mediated Sense-Making - by Olya * 'Moral Uncertainty in Technomoral Change: Bridging the Explanatory Gap' by Philip Nickel, Olya Kudina and Ibo van den Poel
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I was raised in the tradition of believing that everyone is of equal moral worth. But when I scrutinise my daily practices, I don’t think I can honestly say that I act as if everyone is of equal moral worth. The idea that some people belong within the circle of moral concern and some do not is central to many moral systems. But what affects the dynamics of the moral circle? How does it contract and expand? Can it expand indefinitely? In this episode I discuss these questions with Joshua Rottman. Josh is an associate Professor in the Department of Psychology and the Program in Scientific and Philosophical Studies of Mind at Franklin and Marshall College. His research is situated at the intersection of cognitive development and moral psychology, and he primarily focuses on studying the factors that lead certain entities and objects to be attributed with (or stripped of) moral concern.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics discussed include:* The normative significance of moral psychology * The concept of the moral circle * How the moral circle develops in children * How the moral circle changes over time * Can the moral circle expand indefinitely? * Do we have a limited budget of moral concern? * Do most people underuse their budget of moral concern? * Why do some people prioritise the non-human world over marginal humans?
Relevant Links* Josh's webpage at F and M College * Josh's personal webpage * Josh at Psychology Today * 'Tree huggers vs Human Lovers' by Josh et al * Summary of the above article at Psychology Today * 'Towards a Psychology of Moral Expansiveness' by Crimston et al Subscribe to the newsletter
Can we move beyond the Aristotelian account of friendship when thinking about our relationships with robots? Can we hate robots? In this episode, I talk to Helen Ryland about these topics. Helen is a UK-based philosopher. She completed her PhD in Philosophy in 2020 at the University of Birmingham. She now works as an Associate Lecturer for The Open University. Her work examines human-robot relationships, video game ethics, and the personhood and moral status of marginal cases of human rights (e.g., subjects with dementia, nonhuman animals, and robots).
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics covered include: What is friendship and why does it matter? * The Aristotelian account of friendship * Limitations of the Aristotelian account * Moving beyond Aristotle * The degrees of friendship model * Why we can be friends with robots * Criticisms of robot-human friendship * The possibility of hating robots * Do we already hate robots? * Why would it matter if we did hate robots? Relevant Links Helen's homepage * 'It's Friendship Jim, But Not as We Know It: A Degrees-of-Friendship View of Human–Robot Friendships' by Helen * Could you hate a robot? Does it matter if you could? by Helen Subscribe to the newsletter
| | | Thomas Sinclair (left), Ben Kenward (right) |
Lots of people are worried about the ethics of AI. One particular area of concern is whether we should program machines to follow existing normative/moral principles when making decisions. But social moral values change over time. Should machines not be designed to allow for such changes? If machines are programmed to follow our current values will they impede moral progress? In this episode, I talk to Ben Kenward and Thomas Sinclair about this issue. Ben is a Senior Lecturer in Psychology at Oxford Brookes University in the UK. His research focuses on ecological psychology, mainly examining environmental activism such as the Extinction Rebellion movement of which he is a part. Thomas is a Fellow and Tutor in Philosophy at Wadham College, Oxford, and an Associate Professor of Philosophy at Oxford's Faculty of Philosophy. His research and teaching focus on questions in moral and political philosophy.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics discussed incude: What is a moral value? * What is a moral machine? * What is moral progress? * Has society progress, morally speaking, in the past? * How can we design moral machines? * What's the problem with getting machines to follow our current moral consensus? * Will people over-defer to machines? Will they outsource their moral reasoning to machines? * Why is a lack of moral progress such a problem right now? Relevant Links Thomas's webpage * Ben's webpage * 'Machine morality, moral progress and the looming environmental disaster' by Ben and Tom
Are virtual worlds free from the ethical rules of ordinary life? Do they generate their own ethical codes? How do gamers and game designers address these issues? These are the questions that I explore in this episode with my guest Lucy Amelia Sparrow. Lucy is a PhD Candidate in Human-Computer Interaction at the University of Melbourne. Her research focuses on ethics and multiplayer digital games, with other interests in virtual reality and hybrid boardgames. Lucy is a tutor in game design and an academic editor, and has held a number of research and teaching positions at universities across Hong Kong and Australia.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here)
Show NotesTopics discussed include: Are virtual worlds amoral? Do we value them for their freedom from ordinary moral rules? * Is there an important distinction between virtual reality and games? * Do games generate their own internal ethics? * How prevalent are unwanted digitally enacted sexual interactions? * How do gamers respond to such interactions? Do they take them seriously? * How can game designers address this problem? * Do gamers tolerate immoral actions more than the norm? * Can there be a productive form of distrust in video game design? Relevant Links Lucy on Twitter * Lucy on Researchgate * 'Apathetic villagers and the trolls who love them' by Lucy Sparrow, Martin Gibbs and Michael Arnold * 'From ‘Silly’ to ‘Scumbag’: Reddit Discussion of a Case of Groping in a Virtual Reality Game' by Lucy et al * 'Productive Distrust: Playing with the player in digital games' by Lucy et al * 'The "digital animal intuition": the ethics of violence against animals in video games" by Simon Coghlan and Lucy Sparrow Subscribe to the newsletter
Should robots have rights? How about chimpanzees? Or rivers? Many people ask these questions individually, but few people have asked them all together at the same time. In this episode, I talk to a man who has. Josh Gellers is an Associate Professor in the Department of Political Science and Public Administration at the University of North Florida, a Fulbright Scholar to Sri Lanka, a Research Fellow of the Earth System Governance Project, and Core Team Member of the Global Network for Human Rights and the Environment. His research focuses on environmental politics, rights, and technology. He is the author of The Global Emergence of Constitutional Environmental Rights (Routledge 2017) and Rights for Robots: Artificial Intelligence, Animal and Environmental Law (Routledge 2020). We talk about the arguments and ideas in the latter book.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show notesTopics covered include: Should we even be talking about robot rights? * What is a right? What's the difference between a legal and moral right? * How do we justify the ascription of rights? * What is personhood? Who counts as a person? * Properties versus relations - what matters more when it comes to moral status? * What can we learn from the animal rights case law? * What can we learn from the Rights of Nature debate? * Can we imagine a future in which robots have rights? What kinds of rights might those be? Relevant Links Josh's homepage * Josh on Twitter * Rights for Robots: Artificial Intelligence, Animal and Environmental Law by Josh (digital version available Open Access) * "Earth system law and the legal status of non-humans in the Anthropocene" by Josh Subscribe to the newsletter
What does it mean to be human? What does it mean to be you? Philosophers, psychologists and sociologists all seem to agree that your identity is central to how you think of yourself and how you engage with others. But how are emerging technologies changing how we enact and constitute our identities? That's the subject matter of this podcast with Tracey Follows. Tracy is a professional futurist. She runs a consultancy firm called Futuremade. She is a regular writer and speaker on futurism. She has appeared on the BBC and is a contributing columnist with Forbes. She is also a member of the Association of Professional Futuriss and the World Futures Studies Federation. We talk about her book The Future of You: Can your identity survive the 21st Century?
You can download the podcast here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics covered in this episode include: The nature of identity * The link between technology and identity * Is technology giving us more creative control over identity? * Does technology encourage more conformity and groupthink? * Is our identity being fragmented by technology? * Who controls the technology of identity formation? * How should we govern the technology of identity formation in the future? Relevant Links The Future of You by Tracey * Tracey on Twitter * Tracey at Forbes * Futuremade consultancy * Tracey's talk to the London Futurists Subscribe to the newsletter
What are the origins and dynamics of human morality? Is morality, at root, an attempt to solve basic problems of cooperation? What implications does this have for the future? In this episode, I chat to Dr Oliver Scott Curry about these questions. We discuss, in particular, his theory of morality as cooperation (MAC). Dr Curry is Research Director for Kindlab, at kindness.org. He is also a Research Affiliate at the School of Anthropology and Museum Ethnography, University of Oxford, and a Research Associate at the Centre for Philosophy of Natural and Social Science, at the London School of Economics. He received his PhD from LSE in 2005. Oliver’s academic research investigates the nature, content and structure of human morality. He tackles such questions as: What is morality? How did morality evolve? What psychological mechanisms underpin moral judgments? How are moral values best measured? And how does morality vary across cultures? To answer these questions, he employs a range of techniques from philosophy, experimental and social psychology and comparative anthropology.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics discussed include: The nature of morality * The link between human morality and cooperation * The seven types of cooperation * How these seven types of cooperation generate distinctive moral norms * The evidence for the theory of morality as cooperation * Is the theory underinclusive, reductive and universalist? Is that a problem? * Is the theory overinclusive? Could it be falsified? * Why Morality as Cooperation is better than Moral Foundations Theory * The future of cooperation Relevant links Oliver's webpage * Oliver on Twitter * Oliver's Podcast - The Map * 'Morality as Cooperation: A Problem-Centred Approach' by Oliver (sets out the theory of MAC) * 'Morality is fundamentally an evolved solution to problems of social co-operation' (debate at the Royal Anthropological Society) * 'Moral Molecules: Morality as a combinatorial system' by Oliver and his colleagues * 'Is it good to cooperate? Testing the theory of morality-as-cooperation in 60 societies' by Oliver and colleagues * 'What is wrong with moral foundations theory?' by Oliver Subscribe to the newsletter
Should we use technology to surveil, rate and punish/reward all citizens in a state? Do we do it anyway? In this episode I discuss these questions with Wessel Reijers, focusing in particular on the lessons we can learn from the Chinese Social Credit System. Wessel is a postdoctoral Research Associate at the European University Institute, working in the ERC project “BlockchainGov”, which looks into the legal and ethical impacts of distributed governance. His research focuses on the philosophy and ethics of technology, notably on the development of a critical hermeneutical approach to technology and the investigation of the role of emerging technologies in the shaping of citizenship in the 21st century. He completed his PhD at the Dublin City University with a Dissertation entitled “Practising Narrative Virtue Ethics of Technology in Research and Innovation”. In addition to a range of peer-reviewed articles, he recently published the book Narrative and Technology Ethics with Palgrave, which he co-authored with Mark Coeckbelbergh.
You can download the episode here or listen below.You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics discussed in this episode include* The Origins of the Chinese Social Credit System * Historical Parallels to the System * Social Credit Systems in Western Cultures * Is China exceptional when it comes to the use of these systems? * The impact of social credit systems on human values such as freedom and authenticity * How the social credit system is reshaping citizenship * The possible futures of social credit systems
Relevant Links Wessel's homepage * Wessel on Twitter * 'A Dystopian Future? The Rise of Social Credit Systems' - a written debate featuring Wessel * 'How to Make the Perfect Citizen? Lessons from China's Model of Social Credit System' by Liav Orgad and Wessel Reijers * Narrative and Technology Ethics* by Wessel Reijers and Mark Coeckelbergh Subscribe to the newsletter
How do we make sure that an AI does the right thing? How could we do this when we ourselves don't even agree on what the right thing might be? In this episode, I talk to Iason Gabriel about these questions. Iason is a political theorist and ethicist currently working as a Research Scientist at DeepMind. His research focuses on the moral questions raised by artificial intelligence. His recent work addresses the challenge of value alignment, responsible innovation, and human rights. He has also been a prominent contributor to the debate about the ethics of effective altruism.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show Notes:Topics discussed include:
- What is the value alignment problem?
- Why is it so important that we get value alignment right?
- Different ways of conceiving the problem
- How different AI architectures affect the problem
- Why there can be no purely technical solution to the value alignment problem
- Six potential solutions to the value alignment problem
- Why we need to deal with value pluralism and uncertainty
- How political theory can help to resolve the problem
Relevant Links* Iason on Twitter * "Artificial Intelligence, Values and Alignment" by Iason * "Effective Altruism and its Critics" by Iason * My blog series on the above article * "Social Choice Ethics in Artificial Intelligence" by Seth Baum
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Have you ever played Hitman? Grand Theft Auto? Call of Duty? Did you ever question the moral propriety of what you did in those games? In this episode I talk to Sebastian Ostritsch about the ethics of video games. Sebastian is an Assistant Prof. (well, technically, he is a Wissenschaftlicher mitarbeiter but it's like an Assistant Prof) of Philosophy based at Stuttgart University in Germany. He has the rare distinction of being both an expert in Hegel and the ethics of computer games. He is the author of Hegel: Der Welt-Philosoph (published this year in German) and is currently running a project, funded by the German research body DFG, on the ethics of computer games.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopics discussed include:
- The nature of video games
- The problem of seemingly immoral video game content
- The amorality thesis: the view that playing video games is morally neutral
- Defences of the amorality thesis: it's not real and it's just a game.
- Problems with the 'it's not real' and 'it's just a game' arguments.
- The Gamer's Dilemma: Why do people seem to accept virtual murder but not, say, virtual paedophilia?
- Resolving the gamer's dilemma
- The endorsement view of video game morality: some video games might be immoral if they endorse an immoral worldview
- How these ideas apply to other forms of fictional media, e.g. books and movies.
Relevant Links Sebastian's homepage (in German) * Sebastian's book Hegel: Der Weltphilosoph* * 'The amoralist's challenge to gaming and the gamer's moral obligation' by Sebastian * 'The immorality of computer games: Defending the endorsement view against Young’s objections' by Sebastian and Samuel Ulbricht * The Gamer's Dilemma by Morgan Luck * Homo Ludens by Johan Huizinga
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Are we losing our liberty as a result of digital technologies and algorithmic power? In particular, might algorithmically curated filter bubbles be creating a world that encourages both increased polarisation and increased conformity at the same time? In today’s podcast, I discuss these issues with Henrik Skaug Sætra. Henrik is a political scientist working in the Faculty of Business, Languages and Social Science at Østfold University College in Norway. He has a particular interest in political theory and philosophy, and has worked extensively on Thomas Hobbes and social contract theory, environmental ethics and game theory. At the moment his work focuses mainly on issues involving the dynamics between human individuals, society and technology. You download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here). Show NotesTopics discussed include: * Selective Exposure and Confirmation Bias * How algorithms curate our informational ecology * Filter Bubbles * Echo Chambers * How the internet is created more internally conformist but externally polarised groups * The nature of political freedom * Tocqueville and the tyranny of the majority * Mill and the importance of individuality * How algorithmic curation of speech is undermining our liberty * What can be done about this problem?
Relevant Links* Henrik's faculty homepage * Henrik on Researchgate * Henrik on Twitter * 'The Tyranny of Perceived Opinion: Freedom and information in the era of big data' by Henrik * 'Privacy as an aggregate public good' by Henrik * 'Freedom under the gaze of Big Brother: Preparing the grounds for a liberal defence of privacy in the era of Big Data' by Henrik * 'When nudge comes to shove: Liberty and nudging in the era of big data' by Henrik
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Do our values change over time? What role do emotions and technology play in altering our values? In this episode I talk to Steffen Steinert (PhD) about these issues. Steffen is a postdoctoral researcher on the Value Change project at TU Delft. His research focuses on the philosophy of technology, ethics of technology, emotions, and aesthetics. He has published papers on roboethics, art and technology, and philosophy of science. In his previous research he also explored philosophical issues related to humor and amusement.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show Notes Topics discussed include:
- What is a value?
- Descriptive vs normative theories of value
- Psychological theories of personal values
- The nature of emotions
- The connection between emotions and values
- Emotional contagion
- Emotional climates vs emotional atmospheres
- The role of social media in causing emotional contagion
- Is the coronavirus promoting a negative emotional climate?
- Will this affect our political preferences and policies?
- General lessons for technology and value change
Relevant Links * Steffen's Homepage * The Designing for Changing Values Project @ TU Delft * Corona and Value Change by Steffen * 'Unleashing the Constructive Potential of Emotions' by Steffen and Sabine Roeser * An Overview of the Schwartz Theory of Basic Personal Values
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Are you being watched, tracked and traced every minute of the day? Probably. The digital world thrives on surveillance. What should we do about this? My guest today is Carissa Véliz. Carissa is an Associate Professor at the Faculty of Philosophy and the Institute of Ethics in AI at Oxford University. She is also a Tutorial Fellow at Hertford College Oxford. She works on privacy, technology, moral and political philosophy and public policy. She has also been a guest on this podcast on two previous occasions. Today, we’ll be talking about her recently published book Privacy is Power.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show Notes Topics discussed in this show include:
- The most surprising examples of digital surveillance
- The nature of privacy
- Is privacy dead?
- Privacy as an intrinsic and instrumental value
- The relationship between privacy and autonomy
- Does surveillance help with security and health?
- The problem with mass surveillance
- The phenomenon of toxic data
- How surveillance undermines democracy and freedom
- Are we willing to trade privacy for convenient services?
- And much more
Relevant Links * Carissa's Webpage * Privacy is Power by Carissa * Summary of Privacy is Power in Aeon * Review of Privacy is Power in The Guardian * Carissa's Twitter feed (a treasure trove of links about privacy and surveillance) * Views on Privacy: A Survey by Sian Brooke and Carissa Véliz * Data, Privacy and the Individual by Carissa Véliz
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Facial recognition technology has seen its fair share of both media and popular attention in the past 12 months. The runs the gamut from controversial uses by governments and police forces, to coordinated campaigns to ban or limit its use. What should we do about it? In this episode, I talk to Brenda Leong about this issue. Brenda is Senior Counsel and Director of Artificial Intelligence and Ethics at Future of Privacy Forum. She manages the FPF portfolio on biometrics, particularly facial recognition. She authored the FPF Privacy Expert’s Guide to AI, and co-authored the paper, “Beyond Explainability: A Practical Guide to Managing Risk in Machine Learning Models.” Prior to working at FPF, Brenda served in the U.S. Air Force. You can listen to the episode below or download here. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here). Show notesTopics discussed include: * What is facial recognition anyway? * Are there multiple forms that are confused and conflated? * What's the history of facial recognition? What has changed recently? * How is the technology used? * What are the benefits of facial recognition? * What's bad about it? What are the privacy and other risks? * Is there something unique about the face that should make us more worried about facial biometrics when compared to other forms? * What can we do to address the risks? Should we regulate or ban?
Relevant Links* Brenda's Homepage * Brenda on Twitter * 'The Privacy Expert's Guide to AI and Machine Learning' by Brenda (at FPF) * Brenda's US Congress Testimony on Facial Recognition * 'Facial recognition and the future of privacy: I always feel like … somebody’s watching me' by Brenda * 'The Case for Banning Law Enforcement From Using Facial Recognition Technology' by Evan Selinger and Woodrow Hartzog
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In today's episode, I talk to Nikita Aggarwal about the legal and regulatory aspects of AI and algorithmic governance. We focus, in particular, on three topics: (i) algorithmic credit scoring; (ii) the problem of 'too big to fail' tech platforms and (iii) AI crime. Nikita is a DPhil (PhD) candidate at the Faculty of Law at Oxford, as well as a Research Associate at the Oxford Internet Institute's Digital Ethics Lab. Her research examines the legal and ethical challenges due to emerging, data-driven technologies, with a particular focus on machine learning in consumer lending. Prior to entering academia, she was an attorney in the legal department of the International Monetary Fund, where she advised on financial sector law reform in the Euro area.
You can listen to the episode below or download here. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show Notes Topics discussed include:
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The digitisation, datafication and disintermediation of consumer credit markets
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Algorithmic credit scoring
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The problems of risk and bias in credit scoring
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How law and regulation can address these problems
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Tech platforms that are too big to fail
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What should we do if Facebook fails?
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The forms of AI crime
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How to address the problem of AI crime
Relevant Links * Nikita's homepage
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Nikita on Twitter
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'The Norms of Algorithmic Credit Scoring' by Nikita
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'What if Facebook Goes Down? Ethical and Legal Considerations for the Demise of Big Tech Platforms' by Carl Ohman and Nikita
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'Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions' by Thomas King, Nikita, Mariarosario Taddeo and Luciano Floridi
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Lots of algorithmic tools are now used to support decision-making in the criminal justice system. Many of them are criticised for being biased. What should be done about this? In this episode, I talk to Chelsea Barabas about this very question. Chelsea is a PhD candidate at MIT, where she examines the spread of algorithmic decision making tools in the US criminal legal system. She works with interdisciplinary researchers, government officials and community organizers to unpack and transform mainstream narratives around criminal justice reform and data-driven decision making. She is currently a Technology Fellow at the Carr Center for Human Rights Policy at the Harvard Kennedy School of Government. Formerly, she was a research scientist for the AI Ethics and Governance Initiative at the MIT Media Lab.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show notes Topics covered in this show include
- The history of algorithmic decision-making in criminal justice
- Modern AI tools in criminal justice
- The problem of biased decision-making
- Examples of bias in practice
- The FAT (Fairness, Accountability and Transparency) approach to bias
- Can we de-bias algorithms using formal, technical rules?
- Can we de-bias algorithms through proper review and oversight?
- Should we be more critical of the data used to build these systems?
- Problems with pre-trial risk assessment measures
- The abolitionist perspective on criminal justice reform
Relevant Links * Chelsea's homepage * Chelsea on Twitter * "Beyond Bias: Reimagining the terms "Ethical AI" in Criminal Law" by Chelsea * Video presentation of this paper * "Studying up: reorienting the study of algorithmic fairness around issues of power." by Chelsea and ors * Kleinberg et al on the impossibility of fairness * Kleinberg et al on using algorithms to detect discrimination * The Condemnation of Blackness by Khalil Gibran Muhammad
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What happens if an autonomous machine does something wrong? Who, if anyone, should be held responsible for the machine's actions? That's the topic I discuss in this episode with Daniel Tigard. Daniel Tigard is a Senior Research Associate in the Institute for History & Ethics of Medicine, at the Technical University of Munich. His current work addresses issues of moral responsibility in emerging technology. He is the author of several papers on moral distress and responsibility in medical ethics as well as, more recently, papers on moral responsibility and autonomous systems. You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).Show NotesTopics discussed include:
* What is responsibility? Why is it so complex?
* The three faces of responsibility: attribution, accountability and answerability
* Why are people so worried about responsibility gaps for autonomous systems?
* What are some of the alleged solutions to the "gap" problem?
* Who are the techno-pessimists and who are the techno-optimists?
* Why does Daniel think that there is no techno-responsibility gap?
* Is our application of responsibility concepts to machines overly metaphorical?
Relevant Links* Daniel's ResearchGATE profile * Daniel's papers on Philpapers * "There is no Techno-Responsibility Gap" by Daniel * "Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability" by Mark Coeckelbergh * Technologically blurred accountability? by Kohler, Roughley and Sauer
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Are robots like humans? Are they agents? Can we have relationships with them? These are just some of the questions I explore with today's guest, Sven Nyholm. Sven is an assistant professor of philosophy at Utrecht University in the Netherlands. His research focuses on ethics, particularly the ethics of technology. He is a friend of the show, having appeared twice before. In this episode, we are talking about his recent, great, book Humans and Robots: Ethics, Agency and Anthropomorphism. You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here). Show Notes:Topics covered in this episode include: * Why did Sven play football with a robot? Who won? * What is a robot? * What is an agent? * Why does it matter if robots are agents? * Why does Sven worry about a normative mismatch between humans and robots? What should we do about this normative mismatch? * Why are people worried about responsibility gaps arising as a result of the widespread deployment of robots? * How should we think about human-robot collaborations? * Why should human drivers be more like self-driving cars? * Can we be friends with a robot? * Why does Sven reject my theory of ethical behaviourism? * Should we be pessimistic about the future of roboethics?
Relevant Links Sven's Homepage * Sven on Philpapers * Humans and Robots: Ethics, Agency and Anthropomorphism* * 'Can a robot be a good colleague?' by Sven and Jilles Smids * 'Attributing Agency to Automated Systems: Reflections on Human–Robot Collaborations and Responsibility-Loci' by Sven * 'Automated Cars Meet Human Drivers: Responsible Human-Robot Coordination and The Ethics of Mixed Traffic' by Sven and Jilles Smids
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If an AI system makes a decision, should its reasons for making that decision be explainable to you? In this episode, I chat to Scott Robbins about this issue. Scott is currently completing his PhD in the ethics of artificial intelligence at the Technical University of Delft. He has a B.Sc. in Computer Science from California State University, Chico and an M.Sc. in Ethics of Technology from the University of Twente. He is a founding member of the Foundation for Responsible Robotics and a member of the 4TU Centre for Ethics and Technology. Scott is skeptical of AI as a grand solution to societal problems and argues that AI should be boring.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show NotesTopic covered include:
* Why do people worry about the opacity of AI?
* What's the difference between explainability and transparency?
* What's the moral value or function of explainable AI?
* Must we distinguish between the ethical value of an explanation and its epistemic value?
* Why is it so technically difficult to make AI explainable?
* Will we ever have a technical solution to the explanation problem?
* Why does Scott think there is Catch 22 involved in insisting on explainable AI?
* When should we insist on explanations and when are they unnecessary?
* Should we insist on using boring AI?
Relevant Links* Scotts's webpage * Scott's paper "A Misdirected Principle with a Catch: Explicability for AI" * Scott's paper "The Value of Transparency: Bulk Data and Authorisation" * "The Right to an Explanation Explained" by Margot Kaminski * Episode 36 - Wachter on Algorithms and Explanations
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How do we get back to normal after the COVID-19 pandemic? One suggestion is that we use increased amounts of surveillance and tracking to identify and isolate infected and at-risk persons. While this might be a valid public health strategy it does raise some tricky ethical questions. In this episode I talk to Carissa Véliz about these questions. Carissa is a Research Fellow at the Uehiro Centre for Practical Ethics at Oxford and the Wellcome Centre for Ethics and Humanities, also at Oxford. She is the editor of the Oxford Handbook of Digital Ethics as well as two forthcoming solo-authored books Privacy is Power (Transworld) and The Ethics of Privacy (Oxford University Press).
You can download the episode here or listen below.You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show NotesTopics discussed include
* The value of privacy
* Do we balance privacy against other rights/values?
* The significance of consent in debates about consent
* Digital contact tracing and digital quarantines
* The ethics of digital contact tracing
* Is the value of digital contact tracing being oversold?
* The relationship between testing and contact tracing
* COVID 19 as an important moment in the fight for privacy
* The data economy in light of COVID 19
* The ethics of immunity passports
* The importance of focusing on the right things in responding to COVID 19
Relevant Links* Carissa's Webpage * Carissa's Twitter feed (a treasure trove of links about privacy and surveillance) * Views on Privacy: A Survey by Sian Brooke and Carissa Véliz * Data, Privacy and the Individual by Carissa Véliz * Science paper on the value of digital contact tracing * The Apple-Google proposal for digital contact tracing * ''The new normal': China's excessive coronavirus public monitoring could be here to stay' * 'In Coronavirus Fight, China Gives Citizens a Color Code, With Red Flags' * 'To curb covid-19, China is using its high-tech surveillance tools' * 'Digital surveillance to fight COVID-19 can only be justified if it respects human rights' * 'Why ‘Mandatory Privacy-Preserving Digital Contact Tracing’ is the Ethical Measure against COVID-19' by Cansu Canca * 'The COVID-19 Tracking App Won't Work' * 'What are 'immunity passports' and could they help us end the coronavirus lockdown?' * 'The case for ending the Covid-19 pandemic with mass testing'
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There is a lot of data and reporting out there about the COVID 19 pandemic. How should we make sense of that data? Do the media narratives misrepresent or mislead us as to the true risks associated with the disease? Have governments mishandled the response? Can they be morally blamed for what they have done. These are the questions I discuss with my guest on today's show: David Shaw. David is a Senior Researcher at the Institute for Biomedical Ethics at the University of Basel and an Assistant Professor at the Care and Public Health Research Institute, Maastricht University. We discuss some recent writing David has been doing on the Journal of Medical Ethics blog about the coronavirus crisis.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show NotesTopics discussed include...
* Why is it important to keep death rates and other data in context?
* Is media reporting of deaths misleading?
* Why do the media discuss 'soaring' death rates and 'grim' statistics?
* Are we ignoring the unintended health consequences of COVID 19?
* Should we take the economic costs more seriously given the link between poverty/inequality and health outcomes?
* Did the UK government mishandle the response to the crisis? Are they blameworthy for what they did?
* Is it fair to criticise governments for their handling of the crisis?
* Is it okay for governments to experiment on their populations in response to the crisis?
Relevant Links* David's Profile Page at the University of Basel * 'The Vital Contexts of Coronavirus' by David * 'The Slow Dragon and the Dim Sloth: What can the world learn from coronavirus responses in Italy and the UK?' by Marcello Ienca and David Shaw * 'Don't let the ethics of despair infect the ICU' by David Shaw, Dan Harvey and Dale Gardiner * 'Deaths in New York City Are More Than Double the Usual Total' in the NYT (getting the context right?!) * Preliminary results from German Antibody tests in one town: 14% of the population infected * Do Death Rates Go Down in a Recession? * The Sun's Good Friday headline
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I'm still thinking a lot about the COVID-19 pandemic. In this episode I turn away from some of the 'classical' ethical questions about the disease and talk more about how to understand it and form reasonable beliefs about the public health information that has been issued in response to it. To help me do this I will be talking to Katherine Furman. Katherine is a lecturer in philosophy at the University of Liverpool. Her research interests are at the intersection of Philosophy and Health Policy. She is interested in how laypeople understand issues of science, objectivity in the sciences and social sciences, and public trust in science. Her previous work has focused on the HIV/AIDs pandemic and the Ebola outbreak in West Africa in 2014-2015. We will be talking about the lessons we can draw from this work for how we think about the COVID-19 pandemic.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show NotesTopics discussed include:
* The history of explaining the causes of disease
* Mono-causal theories of disease
* Multi-causal theories of disease
* Lessons learned from the HIV/AIDs pandemic
* The practical importance of understanding the causes of disease in the current pandemic
* Is there an ethics of belief?
* Do we have epistemic duties in relation to COVID-19?
* Is it reasonable to believe 'rumours' about the disease?
* Lessons learned from the 2014-2015 Ebola outbreak
* The importance of values in the public understanding of science
Relevant Links* Katherine's Homepage * Katherine @ University of Liverpool * "Mono-Causal and Multi-Causal Theories of Disease: How to Think Virally and Socially about the Aetiology of AIDS" by Katherine * "Moral Responsibility, Culpable Ignorance, and Suppressed Disagreement" by Katherine * "The international response to the Ebola outbreak has excluded Africans and their interests" by Katherine * Imperial College paper on COVID-19 scenarios * Oxford Paper on possible exposure levels to novel Coronavirus
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We have a limited number of ventilators. Who should get access to them? In this episode I talk to Lars Sandman. Lars is a Professor of Healthcare Ethics at Linköping University, Sweden. Lars’s research involves studying ethical aspects of distributing scarce resources within health care and studying and developing methods for ethical analyses of health-care procedures. We discuss the ethics of healthcare prioritisation in the midst of the COVID 19 pandemic, focusing specifically on some principles Lars, along with others, developed for the Swedish government.
You download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show Notes* The prioritisation challenges we currently face * Ethical principles for prioritisation in healthcare * Problems with applying ethical theories in practice * Swedish legal principles on healthcare prioritisation * Principles for access to ICU during the COVID 19 pandemic * Do we prioritise younger people? * Chronological age versus biological age * Could we use a lottery principle? * Should we prioritise healthcare workers? * Impact of COVID 19 prioritisation on other healthcare priorities
Relevant Links* Lar's Webpage * Swedish Legal Principles * Background to the Swedish Law * New priority principles in Sweden (English Translation by Christian Munthe) * "Principles for allocation of scarce medical interventions" by Persad, Werthheimer and Emanuel (good overview of the ethical debate) * The grim ethical dilemma of rationing medical care, explained - Vox.com
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Lots of people are dying right now. But people die all the time. How should we respond to all this death? In this episode I talk to Michael Cholbi about the philosophy of grief. Michael Cholbi is Professor of Philosophy at the University of Edinburgh. He has published widely in ethical theory, practical ethics, and the philosophy of death and dying. We discus the nature of grief, the ethics of grief and how grief might change in the midst of a pandemic.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show NotesTopics discussed include...
* What is grief?
* What are the different forms of grief?
* Is grief always about death?
* Is grief a good thing?
* Is grief a bad thing?
* Does the cause of death make a difference to grief?
* How does the COVID 19 pandemic disrupt grief?
* What are the politics of grief?
* Will future societies memorialise the deaths of people in the pandemic?
Relevant Links* Michael's Homepage * Regret, Resilience and the Nature of Grief by Michael * Finding the Good in Grief by Michael * Grief's Rationality, Backward and Forward by Michael * Coping with Grief: A Series of Philosophical Disquisitions by me * Grieving alone — coronavirus upends funeral rites (Financial Times) * Coronavirus: How Covid-19 is denying dignity to the dead in Italy (BBC) * Why the 1918 Spanish flu defied both memory and imagination * 100 years later, why don’t we commemorate the victims and heroes of ‘Spanish flu’?
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As nearly half the world's population is now under some form of quarantine or lockdown, it seems like an apt time to consider the ethics of infectious disease control measures of this sort. In this episode, I chat to Jonathan Pugh and Tom Douglas, both of whom are Senior Research Fellows at the Uehiro Centre for Practical Ethics in Oxford, about this very issue. We talk about the moral principles that should apply to our evaluation of infectious disease control and some of the typical objections to it. Throughout we focus specifically on some of different interventions that are being applied to tackle COVID-19.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show NotesTopics covered include:
* Methods of infectious disease control
* Consequentialist justifications for disease control
* Non-consequentialist justifications
* The proportionality of disease control measures
* Could these measures stigmatise certain populations?
* Could they exacerbate inequality or fuel discrimination?
* Must we err on the side of precaution in the midst of a novel pandemic?
* Is ethical evaluation a luxury at a time like this?
Relevant Links* Jonathan Pugh's Homepage * Tom Douglas's Homepage * 'Pandemic Ethics: Infectious Pathogen Control Measures and Moral Philosophy' by Jonathan and Tom * 'Justifications for Non-Consensual Medical Intervention: From Infectious Disease Control to Criminal Rehabilitation' by Jonathan and Tom * 'Infection Control for Third-Party Benefit: Lessons from Criminal Justice' by Tom * How Different Asian Countries Responded to COVID 19
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Like almost everyone else, I have been obsessing over the novel coronavirus pandemic for the past few months. Given the dramatic escalation in the pandemic in the past week, and the tricky ethical questions it raises for everyone, I thought it was about time to do an episode about it. So I reached out to people on Twitter and Jeff Sebo kindly volunteered himself to join me for a conversation. Jeff is a Clinical Assistant Professor of Environmental Studies, Affiliated Professor of Bioethics, Medical Ethics, and Philosophy, and Director of the Animal Studies M.A. Program at New York University. Jeff’s research focuses on bioethics, animal ethics, and environmental ethics. This episode was put together in a hurry but I think it covers a lot of important ground. I hope you find it informative and useful. Be safe!
You can download the episode here or listen below. You can also subscribe to the podcast on Apple Podcasts, Spotify, Stitcher and many over podcasting services (the RSS feed is here).
Show NotesTopics covered include:
* Individual duties and responsibilities to stop the spread
* Medical ethics and medical triage
* Balancing short-term versus long-term interests
* Health versus well-being and other goods
* State responsibilities and the social safety net
* The duties of politicians and public officials
* The risk of authoritarianism and the erosion of democratic values
* Global justice and racism/xenophobia
* Our duties to frontline workers and vulnerable members of society
* Animal ethics and the risks of industrial agriculture
* The ethical upside of the pandemic: will this lead to more solidarity and sustainability?
* Pandemics and global catastrophic risks
* What should we be doing right now?
Some Relevant Links* Jeff's webpage * Patient 31 in South Korea * The Duty to Vaccinate and collective action problems * Italian medical ethics recommendations * COVID 19 and the Impossibility of Morality * The problem with the UK government's (former) 'herd immunity' approach * A history of the Spanish Flu
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In this episode I talk to David Wood. David is currently the chair of the London Futurists group and a full-time futurist speaker, analyst, commentator, and writer. He studied the philosophy of science at Cambridge University. He has a background in designing, architecting, implementing, supporting, and avidly using smart mobile devices. He is the author or lead editor of nine books including, "RAFT 2035", "The Abolition of Aging", "Transcending Politics", and "Sustainable Superabundance". We chat about the last book on this list -- Sustainable Superabundance -- and its case for an optimistic future.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, Spotify and other podcasting services (the RSS feed is here).
Show Notes 0:00 - Introduction * 1:40 - Who are the London Futurists? What do they do? * 3:34 - Why did David write Sustainable Superabundance*? * 7:22 - What is sustainable superabundance? * 11:05 - Seven spheres of flourishing and seven types of superabundance? * 16:16 - Why is David a transhumanist? * 20:20 - Dealing with two criticisms of transhumanism: (i) isn't it naive and polyannish? (ii) isn't it elitist, inegalitarian and dangerous? * 30:00 - Key principles of transhumanism * 34:52 - How will we address energy needs of the future? * 40:35 - How optimistic can we really be about the future of energy? * 46:20 - Dealing with pessimism about food production? * 52:48 - Are we heading for another AI winter? * 1:01:08 - The politics of superabundance - what needs to change?
Relevant Links* David Wood on Twitter * London Futurists website * London Futurists Youtube * Sustainable Superabundance by David * Other books in the Transpolitica series * To be a machine by Mark O'Connell * Previous episode with James Hughes about techno-progressive transhumanism * Previous episode with Rick Searle about the dark side of transhumanism
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In this episode I talk (again) to Brian Earp. Brian is Associate Director of the Yale-Hastings Program in Ethics and Health Policy at Yale University and The Hastings Center, and a Research Fellow in the Uehiro Centre for Practical Ethics at the University of Oxford. Brian has diverse research interests in ethics, psychology, and the philosophy of science. His research has been covered in Nature, Popular Science, The Chronicle of Higher Education, The Atlantic, New Scientist, and other major outlets. We talk about his latest book, co-authored with Julian Savulescu, on love drugs.
You can listen to the episode below or download it here. You can also subscribe to the podcast on Apple, Stitcher, Spotify and other leading podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:17 - What is love? (Baby don't hurt me) What is a love drug? * 7:30 - What are the biological underpinnings of love? * 10:00 - How constraining is the biological foundation to love? * 13:45 - So we're not natural born monogamists or polyamorists? * 17:48 - Examples of actual love drugs * 23:32 - MDMA in couples therapy * 27:55 - The situational ethics of love drugs * 33:25 - The non-specific nature of love drugs * 39:00 - The basic case in favour of love drugs * 40:48 - The ethics of anti-love drugs * 44:00 - The ethics of conversion therapy * 48:15 - Individuals vs systemic change * 50:20 - Do love drugs undermine autonomy or authenticity? * 54:20 - The Vice of In-Principlism * 56:30 - The future of love drugs
Relevant Links Brian's Academia.edu page (freely accessible papers) * Brian's Researchgate page (freely accessible papers) * Brian asking Sam Harris a question * The book: Love Drugs or Love is the Drug* * 'Love and enhancement technology'by Brian Earp * 'The Vice of In-principlism and the Harmfulness of Love' by me
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[This is the text of a talk I gave to the Irish Law Reform Commission Annual Conference in Dublin on the 13th of November 2018. You can listen to an audio version of this lecture here or using the embedded player above.]
In the mid-19th century, a set of laws were created to address the menace that newly-invented automobiles and locomotives posed to other road users. One of the first such laws was the English The Locomotive Act 1865, which subsequently became known as the ‘Red Flag Act’. Under this act, any user of a self-propelled vehicle had to ensure that at least two people were employed to manage the vehicle and that one of these persons:
“while any locomotive is in motion, shall precede such locomotive on foot by not less than sixty yards, and shall carry a red flag constantly displayed, and shall warn the riders and drivers of horses of the approach of such locomotives…”
The motive behind this law was commendable. Automobiles did pose a new threat to other, more vulnerable, road users. But to modern eyes the law was also, clearly, ridiculous. To suggest that every car should be preceded by a pedestrian waving a red flag would seem to defeat the point of having a car: the whole idea is that it is faster and more efficient than walking. The ridiculous nature of the law eventually became apparent to its creators and all such laws were repealed in the 1890s, approximately 30 years after their introduction.[1]
The story of the Red Flag laws shows that legal systems often get new and emerging technologies badly wrong. By focusing on the obvious or immediate risks, the law can neglect the long-term benefits and costs.
I mention all this by way of warning. As I understand it, it has been over 20 years since the Law Reform Commission considered the legal challenges around privacy and surveillance. A lot has happened in the intervening decades. My goal in this talk is to give some sense of where we are now and what issues may need to be addressed over the coming years. In doing this, I hope not to forget the lesson of the Red Flag laws.
1. What’s changed?
Let me start with the obvious question. What has changed, technologically speaking, since the LRC last considered issues around privacy and surveillance? Two things stand out.
First, we have entered an era of mass surveillance. The proliferation of digital devices — laptops, computers, tablets, smart phones, smart watches, smart cars, smart fridges, smart thermostats and so forth — combined with increased internet connectivity has resulted in a world in which we are all now monitored and recorded every minute of every day of our lives. The cheapness and ubiquity of data collecting devices means that it is now, in principle, possible to imbue every object, animal and person with some data-monitoring technology. The result is what some scholars refer to as the ‘internet of everything’ and with it the possibility of a perfect ‘digital panopticon’. This era of mass surveillance puts increased pressure on privacy and, at least within the EU, has prompted significant legislative intervention in the form of the GDPR.
Second, we have created technologies that can take advantage of all the data that is being collected. To state the obvious: data alone is not enough. As all lawyers know, it is easy to befuddle the opposition in a complex law suit by ‘dumping’ a lot of data on them during discovery. They drown in the resultant sea of information. It is what we do with the data that really matters. In this respect, it is the marriage of mass surveillance with new kinds of artificial intelligence that creates the new legal challenges that we must now tackle with some urgency.
Artificial intelligence allows us to do three important things with the vast quantities of data that are now being collected:
- (i) It enables new kinds of pattern matching - what I mean here is that AI systems can spot patterns in data that were historically difficult for computer systems to spot (e.g. image or voice recognition), and that may also be difficult, if not impossible, for humans to spot due to their complexity. To put it another way, AI allows us to understand data in new ways.
- (ii) It enables the creation of new kinds of informational product - what I mean here is that the AI systems don’t simply rebroadcast, dispassionate and objective forms of the data we collect. They actively construct and reshape the data into artifacts that can be more or less useful to humans.
- (iii) It enables new kinds of action and behaviour - what I mean here is that the informational products created by these AI systems are not simply inert artifacts that we observe with bemused detachment. They are prompts to change and alter human behaviour and decision-making.
On top of all this, these AI systems do these things with increasing autonomy (or, less controversially, automation). Although humans do assist the AI systems in both understanding, constructing and acting on foot of the data being collected, advances in AI and robotics make it increasingly possible for machines to do things without direct human assistance or intervention.
It is these ways of using data, coupled with increasing automation, that I believe give rise to the new legal challenges. It is impossible for me to cover all of these challenges in this talk. So what I will do instead is to discuss three case studies that I think are indicative of the kinds of challenges that need to be addressed, and that correspond to the three things we can now do with the data that we are collecting.
2. Case Study: Facial Recognition Technology
The first case study has to do with facial recognition technology. This is an excellent example of how AI can understand data in new ways. Facial recognition technology is essentially like fingerprinting for the face. From a selection of images, an algorithm can construct a unique mathematical model of your facial features, which can then be used to track and trace your identity across numerous locations.
The potential conveniences of this technology are considerable: faster security clearance at airports; an easy way to record and confirm attendance in schools; an end to complex passwords when accessing and using your digital services; a way for security services to track and identify criminals; a tool for locating missing persons and finding old friends. Little surprise then that many of us have already welcomed the technology into our lives. It is now the default security setting on the current generation of smartphones. It is also being trialled at airports (including Dublin Airport),[2] train stations and public squares around the world. It is cheap and easily plugged into existing CCTV surveillance systems. It can also take advantage of the vast databases of facial images collected by governments and social media engines.
Despite its advantages, facial recognition technology also poses a significant number of risks. It enables and normalises blanket surveillance of individuals across numerous environments. This makes it the perfect tool for oppressive governments and manipulative corporations. Our faces are one of our most unique and important features, central to our sense of who we are and how we relate to each other — think of the Beatles immortal line ‘Eleanor Rigby puts on the face that she keeps in the jar by the door’ — facial recognition technology captures this unique feature and turns into a digital product that can be copied and traded, and used for marketing, intimidation and harassment.
Consider, for example, the unintended consequences of the FindFace app that was released in Russia in 2016. Intended by its creators to be a way of making new friends, the FindFace app matched images on your phone with images in social media databases, thus allowing you to identify people you may have met but whose names you cannot remember. Suppose you met someone at a party, took a picture together with them, but then didn’t get their name. FindFace allows you use the photo to trace their real identity.[3] What a wonderful idea, right? Now you need never miss out on an opportunity for friendship because of oversight or poor memory. Well, as you might imagine, the app also has a dark side. It turns out to be the perfect technology for stalkers, harassers and doxxers (the internet slang for those who want to out people’s real world identities). Anyone who is trying to hide or obscure their identity can now be traced and tracked by anyone who happens to take a photograph of them.
What’s more, facial recognition technology is not perfect. It has been shown to be less reliable when dealing with non-white faces, and there are several documented cases in which it matches the wrong faces, thus wrongly assuming someone is a criminal when they are not. For example, many US drivers have had their licences cancelled because an algorithm has found two faces on a licence database to be suspiciously similar and has then wrongly assumed the people in question to be using a false identity. In another famous illustration of the problem, 28 members of the US congress (most of them members of racial minorities), were falsely matched with criminal mugshots using facial recognition technology created by Amazon.[4] As some researchers have put it, the widespread and indiscriminate use of facial recognition means that we are all now part of a perpetual line-up that is both biased and error prone.[5] The conveniences of facial recognition thus come at a price, one that often only becomes apparent when something goes wrong, and is more costly for some social groups than others.
What should be done about this from a legal perspective? The obvious answer is to carefully regulate the technology to manage its risks and opportunities. This is, in a sense, what is already being done under the GDPR. Article 9 of the GDPR stipulates that facial recognition is a kind of biometric data that is subject to special protections. The default position is that it should not be collected, but this is subject to a long list of qualifications and exceptions. It is, for example, permissible to collect it if the data has already been made public, if you get the explicit consent of the person, if it serves some legitimate public interest, if it is medically necessary or necessary for public health reasons, if it is necessary to protect other rights and so on. Clearly the GDPR does restrict facial recognition in some ways. A recent Swedish case fined a school for the indiscriminate use of facial recognition for attendance monitoring.[6] Nevertheless, the long list of exceptions makes the widespread use of facial recognition not just a possibility but a likelihood. This is something the EU is aware of and in light of the Swedish case they have signalled an intention to introduce stricter regulation of facial recognition.
This is something we in Ireland should also be considering. The GDPR allows states to introduce stricter protections against certain kinds of data collection. And, according to some privacy scholars, we need the strictest possible protections to to save us from the depredations of facial recognition. Woodrow Hartzog, one of the foremost privacy scholars in the US, and Evan Selinger, a philosopher specialising in the ethics of technology, have recently argued that facial recognition technology must be banned. As they put it (somewhat alarmingly):[7]
“The future of human flourishing depends upon facial recognition technology being banned before the systems become too entrenched in our lives. Otherwise, people won’t know what it’s like to be in public without being automatically identified, profiled, and potentially exploited.”
They caution against anyone who thinks that the technology can be procedurally regulated, arguing that governmental and commercial interests will always lobby for expansion of the technology beyond its initially prescribed remit. They also argue that attempts at informed consent will be (and already are) a ‘spectacular failure’ because people don’t understand what they are consenting to when they give away their facial fingerprint.
Some people might find this call for a categorical ban extreme, unnecessary and impractical. Why throw the baby out with the bathwater and other cliches to that effect. But I would like to suggest that there is something worth taking seriously here, particularly since facial recognition technology is just the tip of the iceberg of data collection. People are already experimenting with emotion recognition technology, which uses facial images to predict future behaviour in real time, and there are many other kinds of sensitive data that are being collected, digitised and traded. Genetic data is perhaps the most obvious other example. Given that data is what fuels the fire of AI, it is possible that we should consider cutting off some of the fuel supply in its entirety.
3. Case Study: Deepfakes
Let me move on to my second case study. This one has to do with how AI is used to create new informational products from data. As an illustration of this I will focus on so-called ‘deepfake’ technology. This is a machine learning technique that allows you to construct realistic synthetic media from databases of images and audio files. The most prevalent use of deepfakes is, perhaps unsurprisingly, in the world of pornography, where the faces of famous actors have been repeatedly grafted onto porn videos. This is disturbing and makes deepfakes an ideal technology for ‘synthetic’ revenge porn.
Perhaps more socially significant than this, however, are the potential political uses of deepfake technology. In 2017, a team of researchers at the University of Washington created a series of deepfake videos of Barack Obama which I will now play for you.[8] The images in these videos are artificial. They haven’t been edited together from different clips. They have been synthetically constructed by an algorithm from a database of audiovisual materials. Obviously, the video isn’t entirely convincing. If you look and listen closely you can see that there is something stilted and artificial about it. In addition to this it uses pre-recorded audio clips to sync to the synthetic video. Nevertheless, if you weren’t looking too closely, you might be convinced it was real. Furthermore, there are other teams working on using the same basic technique to create synthetic audio too. So, as the technology improves, it could be very difficult for even the most discerning viewers to tell the difference between fiction and reality.
Now there is nothing new about synthetic media. With the support of the New Zealand Law Foundation, Tom Barraclough and Curtis Barnes have published one of the most detailed investigations into the legal policy implications of deepfake technology.[9] In their report, they highlight the fact that an awful lot of existing audiovisual media is synthetic: it is all processed, manipulated and edited to some degree. There is also a long history of creating artistic and satirical synthetic representations of political and public figures. Think, for example, of the caricatures in Punch magazine or in the puppet show Spitting Image. Many people who use deepfake technology to create synthetic media will, no doubt, claim a legitimate purpose in doing so. They will say they are engaging in legitimate satire or critique, or producing works of artistic significance.
Nevertheless, there does seem to be something worrying about deepfake technology. The highly realistic nature of the audiovisual material being created makes it the ideal vehicle for harassment, manipulation, defamation, forgery and fraud. Furthermore, the realism of the resultant material also poses significant epistemic challenges for society. The philosopher Regina Rini captures this problem well. She argues that deepfake technology poses a threat to our society’s ‘epistemic backstop’. What she means is that as a society we are highly reliant on testimony from others to get by. We rely on it for news and information, we use it to form expectations about the world and build trust in others. But we know that testimony is not always reliable. Sometimes people will lie to us; sometimes they will forget what really happened. Audiovisual recordings provide an important check on potentially misleading forms of testimony. They encourage honesty and competence. As Rini puts it:[10]
“The availability of recordings undergirds the norms of testimonial practice…Our awareness of the possibility of being recorded provides a quasi-independent check on reckless testifying, thereby strengthening the reasonability of relying on the words of others. Recordings do this in two distinctive ways: actively correcting errors in past testimony and passively regulating ongoing testimonial practices.”
The problem with deepfake technology is that it undermines this function. Audiovisual recordings can no longer provide the epistemic backstop that keeps us honest.
What does this mean for the law? I am not overly concerned about the impact of deepfake technology on legal evidence-gathering practices. The legal system, with its insistence on ‘chain of custody’ and testimonial verification of audiovisual materials, is perhaps better placed than most to deal with the threat of deepfakes (though there will be an increased need for forensic experts to identify deepfake recordings in court proceedings). What I am more concerned about is how deepfake technologies will be weaponised to harm and intimidate others — particularly members of vulnerable populations. The question is whether anything can be done to provide legal redress for these problems? As Barraclough and Barnes point out in their report, it is exceptionally difficult to legislate in this area. How do you define the difference between real and synthetic media (if at all)? How do you balance the free speech rights against the potential harms to others? Do we need specialised laws to do this or are existing laws on defamation and fraud (say) up to the task? Furthermore, given that deepfakes can be created and distributed by unknown actors, who would the potential cause of action be against?
These are difficult questions to answer. The one concrete suggestion I would make is that any existing or proposed legislation on ‘revenge porn’ should be modified so that it explicitly covers the possibility of synthetic revenge porn. Ireland is currently in the midst of legislating against the nonconsensual sharing of ‘intimate images’ in the Harassment, Harmful Communications and Related Offences Bill. I note that the current wording of the offence in section 4 of the Bill covers images that have been ‘altered’ but someone might argue that synthetically constructed images are not, strictly speaking, altered. There may be plans to change this wording to cover this possibility — I know that consultations and amendments to the Bill are ongoing[11] — but if there aren’t then I suggest that there should be.
To reiterate, I am using deepfake technology as an illustration of a more general problem. There are many other ways in which the combination data and AI can be used to mess with the distinction between fact and fiction. The algorithmic curation and promotion of fake news, for example, or the use of virtual and augmented reality to manipulate our perception of public and private spaces, both pose significant threats to property rights, privacy rights and political rights. We need to do something to legally manage this brave new (technologically constructed) world.
4. Case Study: Algorithmic Risk Prediction
Let me turn turn now to my final case study. This one has to do with how data can be used to prompt new actions and behaviours in the world. For this case study, I will look to the world of algorithmic risk prediction. This is where we take a collection of datapoints concerning an individual’s behaviour and lifestyle and feed it into an algorithm that can make predictions about their likely future behaviour. This is a long-standing practice in insurance, and is now being used in making credit decisions, tax auditing, child protection, and criminal justice (to name but a few examples). I’ll focus on its use in criminal justice for illustrative purposes.
Specifically, I will focus on the debate surrounding the COMPAS algorithm, that has been used in a number of US states. The COMPAS algorithm (created by a company called Northpointe, now called Equivant) uses datapoints to generate a recidivism risk score for criminal defendants. The datapoints include things like the person’s age at arrest, their prior arrest/conviction record, the number of family members who have been arrested/convicted, their address, their education and job and so on. These are then weighted together using an algorithm to generate a risk score. The exact weighting procedure is unclear, since the COMPAS algorithm is a proprietary technology, but the company that created it has released a considerable amount of information about the datapoints it uses into the public domain.
If you know anything about the COMPAS algorithm you will know that it has been controversial. The controversy stems from two features of how the algorithm works. First, the algorithm is relatively opaque. This is a problem because the fair administration of justice requires that legal decision-making be transparent and open to challenge. A defendant has a right to know how a tribunal or court arrived at its decision and to challenge or question its reasoning. If this information isn’t known — either because the algorithm is intrinsically opaque or has been intentionally rendered opaque for reasons of intellectual property — then this principle of fair administration is not being upheld. This was one of the grounds on which the use of COMPAS algorithm was challenged in the US case of Loomis v Wisconsin.[12] In that case, the defendant, Loomis, challenged his sentencing decision on the basis that the trial court had relied on the COMPAS risk score in reaching its decision. His challenge was ultimately unsuccessful. The Wisconsin Supreme Court reasoned that the trial court had not relied solely on the COMPAS risk score in reaching its decision. The risk score was just one input into the court’s decision-making process, which was itself transparent and open to challenge. That said, the court did agree that courts should be wary when relying on such algorithms and said that warnings should be attached to the scores to highlight their limitations.
The second controversy associated with the COMPAS algorithm has to do with its apparent racial bias. To understand this controversy I need to say a little bit more about how the algorithm works. Very roughly, the COMPAS algorithm is used to sort defendants into to outcome ‘buckets’: a 'high risk' reoffender bucket or a 'low risk' reoffender bucket. A number of years back a group of data journalists based at ProPublica conducted an investigation into which kinds of defendants got sorted into those buckets. They discovered something disturbing. They found that the COMPAS algorithm was more likely to give black defendants a false positive high risk score and more likely to give white defendants a false negative low risk score. The exact figures are given in the table below. Put another way, the COMPAS algorithm tended to rate black defendants as being higher risk than they actually were and white defendants as being lower risk than they actually were. This was all despite the fact that the algorithm did not explicitly use race as a criterion in its risk scores.
Needless to say, the makers of the COMPAS algorithm were not happy about this finding. They defended their algorithm, arguing that it was in fact fair and non-discriminatory because it was well calibrated. In other words, they argued that it was equally accurate in scoring defendants, irrespective of their race. If it said a black defendant was high risk, it was right about 60% of the time and if it said that a white defendant was high risk, it was right about 60% of the time. This turns out to be true. The reason why it doesn't immediately look like it is equally accurate upon a first glance at the relevant figures is that there are a lot more black defendants than white defendants -- an unfortunate feature of the US criminal justice system that is not caused by the algorithm but is, rather, a feature the algorithm has to work around.
So what is going on here? Is the algorithm fair or not? Here is where things get interesting. Several groups of mathematicians analysed this case and showed that the main problem here is that the makers of COMPAS and the data journalists were working with different conceptions of fairness and that these conceptions were fundamentally incompatible. This is something that can be formally proved. The clearest articulation of this proof can be found in a paper by Jon Kleinberg, Sendhil Mullainathan and Manish Raghavan.[13] To simplify their argument, they said that there are two things you might want a fair decision algorithm to do: (i) you might want it to be well-calibrated (i.e. equally accurate in its scoring irrespective of racial group); (ii) you might want it to achieve an equal representation for all groups in the outcome buckets. They then proved that except in two unusual cases, it is impossible to satisfy both criteria. The two unusual cases are when the algorithm is a 'perfect predictor' (i.e. it always get things right) or, alternatively, when the base rates for the relevant populations are the same (e.g. there are the same number of black defedants as there are white defendants). Since no algorithmic decision procedure is a perfect predictor, and since our world is full of base rate inequalities, this means that no plausible real-world use of a predictive algorithm is likely to be perfectly fair and non-discriminatory. What's more, this is generally true for all algorithmic risk predictions and not just true for cases involving recidivism risk. If you would like to see a non-mathematical illustration of the problem, I highly recommend checking out a recent article in the MIT Technology Review which includes a game you can play using the COMPAS algorithm and which illustrates the hard tradeoff between different conceptions of fairness.[14]
What does all this mean for the law? Well, when it comes to the issue of transparency and challengeability, it is worth noting that the GDPR, in articles 13-15 and article 22, contains what some people refer to as a ‘right to explanation’. It states that, when automated decision procedures are used, people have a right to access meaningful information about the logic underlying the procedures. What this meaningful information looks like in practice is open to some interpretation, though there is now an increasing amount of guidance from national data protection units about what is expected.[15] But in some ways this misses the deeper point. Even if we make these procedures perfectly transparent and explainable, there remains the question about how we manage the hard tradeoff between different conceptions of fairness and non-discrimination. Our legal conceptions of fairness are multidimensional and require us to balance competing interests. When we rely on human decision-makers to determine what is fair, we accept that there will be some fudging and compromise involved. Right now, we let this fudging take place inside the minds of the human decision-makers, oftentimes without questioning it too much or making it too explicit. The problem with algorithmic risk predictions is that they force us to make this fudging explicit and precise. We can no longer pretend that the decision has successfully balanced all the competing interests and demands. We have to pick and choose. Thus, in some ways, the real challenge with these systems is not that they are opaque and non-transparent but, rather, that when they are transparent they force us to make hard choices.
To some, this is the great advantage of algorithmic risk prediction. A paper by Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan and Cass Sunstein entitled ‘Discrimination in the Age of the Algorithm’ makes this very case.[16] They argue that the real problem at the moment is that decision-making is discriminatory and its discriminatory nature is often implicit and hidden from view. The widespread use of transparent algorithms will force it into the open where it can be washed by the great disinfectant of sunlight. But I suspect others will be less sanguine about this new world of algorithmically mediated justice. They will argue that human-led decision-making, with its implicit fudging, is preferable, partly because it allows us to sustain the illusion of justice. Which world do we want to live in? The transparent and explicit world imagined by Kleinberg et al, or the murky and more implicit world of human decision-making? This is also a key legal challenge for the modern age.
5. Conclusion
It’s time for me to wrap up. One lingering question you might have is whether any of the challenges outlined above are genuinely new. This is a topic worth debating. In one sense, there is nothing completely new about the challenges I have just discussed. We have been dealing with variations of them for as long as humans have lived in complex, literate societies. Nevertheless, there are some differences with the past. There are differences of scope and scale — mass surveillance and AI enables collection of data at an unprecedented scale and its use on millions of people at the same time. There are differences of speed and individuation — AI systems can update their operating parameters in real time and in highly individualised ways. And finally, there are the crucial differences in the degree of autonomy with which these systems operate, which can lead to problems in how we assign legal responsibility and liability.
Endnotes
* [1] I am indebted to Jacob Turner for drawing my attention to this story. He discusses it in his book Robot Rules - Regulating Artificial Intelligence (Palgrave MacMillan, 2018). This is probably the best currently available book about Ai and law.
* [2] See https://www.irishtimes.com/business/technology/airport-facial-scanning-dystopian-nightmare-rebranded-as-travel-perk-1.3986321; and https://www.dublinairport.com/latest-news/2019/05/31/dublin-airport-participates-in-biometrics-trial
* [3] https://arstechnica.com/tech-policy/2016/04/facial-recognition-service-becomes-a-weapon-against-russian-porn-actresses/#
* [4] This was a stunt conducted by the ACLU. See here for the press release https://www.aclu.org/blog/privacy-technology/surveillance-technologies/amazons-face-recognition-falsely-matched-28
* [5] https://www.perpetuallineup.org/
* [6] For the story, see here https://www.bbc.com/news/technology-49489154
* [7] Their original call for this can be found here: https://medium.com/s/story/facial-recognition-is-the-perfect-tool-for-oppression-bc2a08f0fe66
* [8] The video can be found here; https://www.youtube.com/watch?v=UCwbJxW-ZRg; For more information on the research see here: https://www.washington.edu/news/2017/07/11/lip-syncing-obama-new-tools-turn-audio-clips-into-realistic-video/; https://grail.cs.washington.edu/projects/AudioToObama/siggraph17_obama.pdf
* [9] The full report can be found here: https://static1.squarespace.com/static/5ca2c7abc2ff614d3d0f74b5/t/5ce26307ad4eec00016e423c/1558340402742/Perception+Inception+Report+EMBARGOED+TILL+21+May+2019.pdf
* [10] The paper currently exists in a draft form but can be found here: https://philpapers.org/rec/RINDAT
* [11] https://www.dccae.gov.ie/en-ie/communications/consultations/Pages/Regulation-of-Harmful-Online-Content-and-the-Implementation-of-the-revised-Audiovisual-Media-Services-Directive.aspx
* [12] For a summary of the judgment, see here: https://harvardlawreview.org/2017/03/state-v-loomis/
* [13] “Inherent Tradeoffs in the Fair Determination of Risk Scores” - available here https://arxiv.org/abs/1609.05807
* [14] The article can be found at this link - https://www.technologyreview.com/s/613508/ai-fairer-than-judge-criminal-risk-assessment-algorithm/
* [15] Casey et al ‘Rethinking Explainabie Machines’ - available here https://scholarship.law.berkeley.edu/btlj/vol34/iss1/4/
* [16] An open access version of the paper can be downloaded here https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3329669
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In this episode I talk to Dr Regina Rini. Dr Rini currently teaches in the Philosophy Department at York University, Toronto where she holds the Canada Research Chair in Philosophy of Moral and Social Cognition. She has a PhD from NYU and before coming to York in 2017 was an Assistant Professor / Faculty Fellow at the NYU Center for Bioethics, a postdoctoral research fellow in philosophy at Oxford University and a junior research fellow of Jesus College Oxford. We talk about the political and epistemological consequences of deepfakes. This is a fascinating and timely conversation.
You can download this episode here or listen below. You can also subscribe to the podcast on Apple Podcasts, Stitcher and a variety of other podcasting services (the RSS feed here).
Show Notes* 0:00 - Introduction * 3:20 - What are deepfakes? * 7:35 - What is the academic justification for creating deepfakes (if any)? * 11:35 - The different uses of deepfakes: Porn versus Politics * 16:00 - The epistemic backstop and the role of audiovisual recordings * 22:50 - Two ways that recordings regulate our testimonial practices * 26:00 - But recordings aren't a window onto the truth, are they? * 34:34 - Is the Golden Age of recordings over? * 39:36 - Will the rise of deepfakes lead to the rise of epistemic elites? * 44:32 - How will deepfakes fuel political partisanship? * 50:28 - Deepfakes and the end of public reason * 54:15 - Is there something particularly disruptive about deepfakes? * 58:25 - What can be done to address the problem?
Relevant Links* Regina's Homepage * Regina's Philpapers Page * "Deepfakes and the Epistemic Backstop" by Regina * "Fake News and Partisan Epistemology" by Regina * Jeremy Corbyn and Boris Johnson Deepfake Video * "California’s Anti-Deepfake Law Is Far Too Feeble" Op-Ed in Wired
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In this episode I talk to Dr Pak-Hang Wong. Pak is a philosopher of technology and works on ethical and political issues of emerging technologies. He is currently a research associate at the Universitat Hamburg. He received his PhD in Philosophy from the University of Twente in 2012, and then held academic positions in Oxford and Hong Kong. In 2017, he joined the Research Group for Ethics in Information Technology, at the Department of Informatics, Universitat Hamburg. We talk about the robotic disruption of morality and how it affects our capacity to develop moral virtues. Pak argues for a distinctive Confucian approach to this topic and so provides something of a masterclass on Confucian virtue ethics in the course of our conversation.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:56 - How do robots disrupt our moral lives? * 7:18 - Robots and Moral Deskilling * 12:52 - The Folk Model of Virtue Acquisition * 21:16 - The Confucian approach to Ethics * 24:28 - Confucianism versus the European approach * 29:05 - Confucianism and situationism * 34:00 - The Importance of Rituals * 39:39 - A Confucian Response to Moral Deskilling * 43:37 - Criticisms (moral silencing) * 46:48 - Generalising the Confucian approach * 50:00 - Do we need new Confucian rituals?
Relevant Links* Pak's homepage at the University of Hamburg * Pak's Philpeople Profile * "Rituals and Machines: A Confucian Response to Technology Driven Moral Deskilling" by Pak * "Responsible Innovation for Decent Nonliberal Peoples: A Dilemma?" by Pak * "Consenting to Geoengineering" by Pak * Episode 45 with Shannon Vallor on Technology and the Virtues
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In this episode I talk to Dr Karina Vold. Karina is a philosopher of mind, cognition, and artificial intelligence. She works on the ethical and societal impacts of emerging technologies and their effects on human cognition. Dr Vold is currently a postdoctoral Research Associate at the Leverhulme Centre for the Future of Intelligence, a Research Fellow at the Faculty of Philosophy, and a Digital Charter Fellow at the Alan Turing Institute. We talk about the ethics extended cognition and how it pertains to the use of artificial intelligence. This is a fascinating topic because it addresses one of the oft-overlooked effects of AI on the human mind.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple, Stitcher and a range of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:55 - Some examples of AI cognitive extension * 13:07 - Defining cognitive extension * 17:25 - Extended cognition versus extended mind * 19:44 - The Coupling-Constitution Fallacy * 21:50 - Understanding different theories of situated cognition * 27:20 - The Coupling-Constitution Fallacy Redux * 30:20 - What is distinctive about AI-based cognitive extension? * 34:20 - The three/four different ways of thinking about human interactions with AI * 40:04 - Problems with this framework * 49:37 - The Problem of Cognitive Atrophy * 53:31 - The Moral Status of AI Extenders * 57:12 - The Problem of Autonomy and Manipulation * 58:55 - The policy implications of recognising AI cognitive extension
Relevant Links* Karina's homepage * Karina at the Leverhulme Centre for the Future of Intelligence * "AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI" by José Hernández Orallo and Karina Vold * "The Parity Argument for Extended Consciousness" by Karina * "Are ‘you’ just inside your skin or is your smartphone part of you?" by Karina * "The Extended Mind" by Clark and Chalmers * Theory and Application of the Extended Mind (series by me)
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[The following is the text of a talk I delivered at the World Summit AI on the 10th October 2019. The talk is essentially a nugget taken from my new book Automation and Utopia. It's not an excerpt per se, but does look at one of the key arguments I make in the book. You can listen to the talk using the plugin above or download it here.]
The science fiction author Arthur C. Clarke once formulated three “laws” for thinking about the future. The third law states that “any sufficiently advanced technology is indistinguishable from magic”. The idea, I take it, is that if someone from the Paleolithic was transported to the modern world, they would be amazed by what we have achieved. Supercomputers in our pockets; machines to fly us from one side of the planet to another in less than a day; vaccines and antibiotics to cure diseases that used to kill most people in childhood. To them, these would be truly magical times.
It’s ironic then that many people alive today don’t see it that way. They see a world of materialism and reductionism. They think we have too much knowledge and control — that through technology and science we have made the world a less magical place. Well, I am here to reassure these people. One of the things AI will do is re-enchant the world and kickstart a new era of techno-superstition. If not for everyone, then at least for most people who have to work with AI on a daily basis. The catch, however, is that this is not necessarily a good thing. In fact, it is something we should worry about.
Let me explain by way of an analogy. In the late 1940s, the behaviorist psychologist BF Skinner — famous for his experiments on animal learning —got a bunch of pigeons and put them into separate boxes. Now, if you know anything about Skinner you’ll know he had a penchant for this kind of thing. He seems to have spent his adult life torturing pigeons in boxes. Each box had a window through which a food reward would be presented to the bird. Inside the box were different switches that the pigeons could press with their beaks. Ordinarily, Skinner would set up experiments like this in such a way that pressing a particular sequence of switches would trigger the release of the food. But for this particular experiment he decided to do something different. He decided to present the food at random intervals, completely unrelated to the pressing of the switches. He wanted to see what the pigeons would do as a result.
The findings were remarkable. Instead of sitting idly by and waiting patiently for their food to arrive, the pigeons took matters into their own hands. They flapped their wings repeatedly, they danced around in circles, they hopped on one foot, convinced that their actions had something to do with the presentation of the food reward. Skinner and his colleagues likened what the pigeons were doing to the ‘rain dances’ performed by various tribes around the world: they were engaging in superstitious behaviours to control an unpredictable and chaotic environment.
It’s important that we think about this situation from the pigeon’s perspective. Inside the Skinner box, they find themselves in an unfamiliar world that is deeply opaque to them. Their usual foraging tactics and strategies don’t work. Things happen to them, food gets presented, but they don’t really understand why. They cannot cope with the uncertainty; their brains rush to fill the gap and create the illusion of control.
Now what I want to argue here is that modern workers, and indeed all of us, in an environment suffused with AI, can end up sharing the predicament of Skinner’s pigeons. We can end up working inside boxes, fed information and stimuli by artificial intelligence. And inside these boxes, stuff can happen to us, work can get done, but we are not quite sure if or how our actions make a difference. We end up resorting to odd superstitions and rituals to make sense of it all and give ourselves the illusion of control, and one of the things I worry about, in particular, is that a lot of the current drive for transparent or explainable AI will reinforce this phenomenon.
This might sound far-fetched, but it’s not. There has been a lot of talk in recent years about the ‘black box’ nature of many AI-systems. For example, the machine learning systems used to support risk assessments in bureaucratic, legal and financial settings. These systems all work in the same way. Data from human behaviour gets fed into them, and they then spit out risk scores and recommendations to human decision-makers. The exact rationale for those risk scores — i.e. the logic the systems use — is often hidden from view. Sometimes this is for reasons intrinsic to the coding of the algorithm; other times it is because it is deliberately concealed or people just lack the time, inclination or capacity to decode the system.
The metaphor of the black box, useful though it is, is, however, misleading in one crucial respect: It assumes that the AI is inside the box and we are the ones trying to look in from the outside. But increasingly this is not the case. Increasingly, it is we who are trapped inside the box, being sent signals and nudges by the AI, and not entirely sure what is happening outside.
Consider the way credit-scoring algorithms work. Many times neither the decision-maker (the human in the loop) nor the person affected knows why they get the score they do. The systems are difficult to decode and often deliberately concealed to prevent gaming. Nevertheless, the impact of these systems on human behaviour is profound. The algorithm constructs a game in which humans have to act within the parameters set by the algorithm to get a good score. There are many websites dedicated to helping people reverse engineer these systems, often giving dubious advice about behaviours and rituals you must follow to improve your scores. If you follow this advice, it is not too much of a stretch to say that you end up like one Skinner’s pigeons - flapping your wings to maintain some illusion of control.
Some of you might say that this is an overstatement. The opaque nature of AI is a well-known problem and there are now a variety of technical proposals out there for making it less opaque and more “explainable” [some of which have been discussed here today]. These technical proposals have been accompanied by increased legal safeguards that mandate greater transparency. But we have to ask ourselves a question: will these solutions really work? Will they help ordinary people to see outside the box and retain some meaningful control and understanding of what is happening to them?
A recent experiment by Ben Green and Yiling Chen from Harvard tried to answer these questions. It looked at how human decision-makers interact with risk assessment algorithms in criminal justice and finance (specifically in making decisions about pretrial release of defendants and the approval loan applications). Green and Chen created their own risk assessment systems, based on some of the leading commercially available models. They then got a group of experimental subjects (recruited via Amazon’s Mechanical Turk) to use these algorithms to make decisions under a number of different conditions. I won’t go through all the conditions here, but I will describe the four most important. In the first condition, the experimental subjects were just given the raw score provided by the algorithm and asked to make a decision on foot of this; in the second they were asked to give their own prediction initially and then update it after being given the algorithm’s prediction; in the third they were given the algorithm’s score, along with an explanation of how that score was derived, and asked to make a choice; and in the fourth they were given the opportunity to learn how accurate the algorithm was based on real world results (did someone default on their loan or not; did they show up to their trial or not). The question was: how would the humans react to these different scenarios? Would giving them more information improve the accuracy, reliability and fairness of their decision-making?
The findings were dispiriting. Green and Chen found that using algorithms did improve the overall accuracy of decision-making across all conditions, but this was not because adding information and explanations enabled the humans to play a more meaningful role in the process. On the contrary, adding more information often made the human interaction with the algorithm worse. When given the opportunity to learn from the real-world outcomes, the humans became overconfident in their own judgments, more biased, and less accurate overall. When given explanations, they could maintain accuracy but only to the extent that they deferred more to the algorithm. In short, the more transparent the system seemed to the worker, the more the workers made them worse or limited their own agency.
It is important not to extrapolate too much from one study, but the findings here are consistent what has been found in other cases of automation in the workplace: humans are often the weak link in the chain. They need to be kept in check. This suggests that if we want to reap the benefits of AI and automation, we may have to create an environment that is much like that of the Skinner box, one in which humans can flap their wings, convinced they are making a difference, but prevented from doing any real damage. This is the enchanted world of techno-superstition: a world in which we adopt odd rituals and habits (explainable AI; fair AI etc) to create an illusion of control.
Now, the original title of my talk promised five reasons for pessimism about AI in the workplace. But what we have here is one big reason that breaks down into five sub-reasons. Let me explain what I mean. The problem of techno-superstitionism stems from two related problems: (i) a lack of understanding/knowledge of how the world (in this case the AI system) works and (ii) the illusion of control over that system.
These two problems combine into a third problem: the erosion of the possibility of achievement. One reason why we work is so that we can achieve certain outcomes. But when we lack understanding and control it undermines our sense of achievement. We achieve things when we use our reason to overcome obstacles to problem-solving in the real world. Some people might argue that a human collaborating with an AI system to produce some change in the world is achieving something through the combination of their efforts. But this is only true if the human plays some significant role in the collaboration. If humans cannot meaningfully make a difference to the success of AI or accurately calibrate their behaviour to produce better outcomes in tandem with the AI, then the pathway to achievement is blocked. This seems to be what happens, even when we try to make the systems more transparent.
Related to this is the fourth problem: that in order to make AI systems work effectively with humans, the designers and manufacturers have to control human attention and behaviour in a way that undermines human autonomy. Humans cannot be given free rein inside the box. They have to be guided, nudged, manipulated and possibly even coerced, to do the right thing. Explanations have to be packaged in a way that prevents the humans from undermining the accuracy, reliability and fairness of the overall system. This, of course, is not unusual. Workplaces are always designed with a view to controlling and incentivising behaviour, but AI enables a rapidly updating and highly dynamic form of behavioural control. The traditional human forms of resistance to outside control cannot easily cope with this new reality.
This all then culminates in the fifth and final problem: the pervasive use of AI in the workplace (and society more generally) (v) undermines human agency. Instead of being the active captains of our fates; we become the passive recipients of technological benefits. This is a tragedy because we have built so much of our civilisation and sense of self-worth on the celebrations of agency. We are supposed to be agents of change, responsible to ourselves and to one another for what happens in the world around us. This is why we value the work we do and why we crave the illusion of control. What happens if agency can no longer be sustained?
As per usual, I have left the solutions to the very end — to the point in the talk where they cannot be fully fleshed out and where I cannot be reasonably criticised for failing to do so — but it seems to me that we face two fundamental choices when it comes to addressing techno-superstition: (i) we can tinker with what’s presented to us inside the box, i.e. we can add more bells and whistles to our algorithms, more levers and switches. These will either give humans genuine understanding and control over the systems or the illusion of understanding and control. The problem with the former is that frequently involves tradeoffs or compromises to the system’s efficacy and the problem with the latter is that involves greater insults to the agency of the humans working inside the box. But there is an alternative: we can stop flapping our wings and get out of the box altogether. Leave the machines to do what they are best at while we do something else. Increasingly, I have come to think we should do the latter; that do so would acknowledge the truly liberating power of AI. This is the argument I develop further in my book Automation and Utopia.
Thank you for your attention.
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[This is the text of a lecture that I delivered at Tilburg University on the 24th of September 2019. It was delivered as part of the 25th Anniversary celebrations for TILT (Tilburg Institute for Law, Technology and Society). My friend and colleague Sven Nyholm was the discussant for the evening. The lecture is based on my longer academic article ‘Welcoming Robots into the Moral Circle: A Defence of Ethical Behaviourism’ but was written from scratch and presents some key arguments in a snappier and clearer form. I also include a follow up section responding to criticisms from the audience on the evening of the lecture. My thanks to all those involved in organizing the event (Aviva de Groot, Merel Noorman and Silvia de Conca in particular). You can download an audio version of this lecture, minus the reflections and follow ups, here or listen to it above]
1. Introduction
My lecture this evening will be about the conditions under which we should welcome robots into our moral communities. Whenever I talk about this, I am struck by how much my academic career has come to depend upon my misspent youth for its inspiration. Like many others, I was obsessed with science fiction as a child, and in particular with the representation of robots in science fiction. I had two favourite, fictional, robots. The first was R2D2 from the original Star Wars trilogy. The second was Commander Data from Star Trek: the Next Generation. I liked R2D2 because of his* personality - courageous, playful, disdainful of authority - and I liked Data because the writers of Star Trek used him as a vehicle for exploring some important philosophical questions about emotion, humour, and what it means to be human.
In fact, I have to confess that Data has had an outsized influence on my philosophical imagination and has featured in several of my academic papers. Part of the reason for this was practical. When I grew up in Ireland we didn’t have many options to choose from when it came to TV. We had to make do with what was available and, as luck would have it, Star Trek: TNG was on every day when I came home from school. As a result, I must have watched each episode of its 7-season run multiple times.
One episode in particular has always stayed with me. It was called ‘Measure of a Man’. In it, a scientist from the Federation visits the Enterprise because he wants to take Data back to his lab to study him. Data, you see, is a sophisticated human-like android, created by a lone scientific genius, under somewhat dubious conditions. The Federation scientist wants to take Data apart and see how he works with a view to building others like him. Data, unsurprisingly, objects. He argues that he is not just a machine or piece of property that can be traded and disassembled to suit the whims of human beings. He has his own, independent moral standing. He deserves to be treated with dignity.
But how does Data prove his case? A trial ensues and evidence is given on both sides. The prosecution argue that Data is clearly just a piece of property. He was created not born. He doesn’t think or see the world like a normal human being (or, indeed, other alien species). He even has an ‘off switch’. Data counters by giving evidence of the rich relationships he has formed with his fellow crew members and eliciting testimony from others regarding his behaviour and the interactions they have with him. Ultimately, he wins the case. The court accepts that he has moral standing.
Now, we can certainly lament the impact that science fiction has on the philosophical debate about robots. As David Gunkel observes in his 2018 book Robot Rights:
“[S]cience fiction already — and well in advance of actual engineering practice — has established expectations for what a robot is or can be. Even before engineers have sought to develop working prototypes, writers, artists, and filmmakers have imagined what robots do or can do, what configurations they might take, and what problems they could produce for human individuals and communities.”
(Gunkel 2018, 16)
He continues, noting that this is a “potential liability” because:
“science fiction, it is argued, often produces unrealistic expectations for and irrational fears about robots that are not grounded in or informed by actual science.”
(Gunkel 2018, 18)
I certainly heed this warning. But, nevertheless, I think the approach taken by the TNG writers in the episode ‘Measure of a Man’ is fundamentally correct. Even if we cannot currently create a being like Data, and even if the speculation is well in advance of the science, they still give us the correct guide to resolving the philosophical question of when to welcome robots into our moral community. Or so, at least, I shall argue in the remainder of this lecture.
2. Tribalism and Conflict in Robot Ethics
Before I get into my own argument, let me say something about the current lay of the land when it comes to this issue. Some of you might be familiar with the famous study by the social psychologist Muzafer Sherif. It was done in the early 1950s at a summer camp in Robber’s Cave, Oklahoma. Suffice to say, it is one of those studies that wouldn’t get ethics approval nowadays. Sherif and his colleagues were interested in tribalism and conflict. They wanted to see how easy it would be to get two groups of 11-year old boys to divide into separate tribes and go to war with one another. It turned out to be surprisingly easy. By arbitrarily separating the boys into two groups, giving them nominal group identity (the ‘Rattlers’ and the ‘Eagles’), and putting them into competition with each other, Sherif and his research assistants sowed the seeds for bitter and repeated conflict.
The study has become a classic, repeatedly cited as evidence of how easy it is for humans to get trapped in intransigent group conflicts. I mention it here because, unfortunately, it seems to capture what has happened with the debate about the potential moral standing of robots. The disputants have settled into two tribes. There are those that are ‘anti’ the idea; and there are those that are ‘pro’ the idea. The members of these tribes sometimes get into heated arguments with one another, particularly on Twitter (which, admittedly, is a bit like a digital equivalent of Sherif’s summer camp).
Those that are ‘anti’ the idea would include Noel Sharkey, Amanda Sharkey, Deborah Johnson, Aimee van Wynsberghe and the most recent lecturer in this series, Joanna Bryson. They cite a variety of reasons for their opposition. The Sharkeys, I suspect, think the whole debate is slightly ridiculous because current robots clearly lack the capacity for moral standing, and debating their moral standing distracts from the important issues in robot ethics - namely stopping the creation and use of robots that are harmful to human well-being. Deborah Johnson would argue that since robots can never experience pain or suffering they will never have moral standing. Van Wynsberghe and Bryson are maybe a little different and lean more heavily on the idea that even if it were possible to create robots with moral standing — a possibility that Bryson at least is willing to concede — it would be a very bad idea to do so because it would cause considerable moral and legal disruption.
Those that are pro the idea would include Kate Darling, Mark Coeckelbergh, David Gunkel, Erica Neely, and Daniel Estrada. Again, they cite a variety of reasons for their views. Darling is probably the weakest on the pro side. She focuses on humans and thinks that even if robots themselves lack moral standing we should treat them as if they had moral standing because that would be better for us. Coeckelbergh and Gunkel are more provocative, arguing that in settling questions of moral standing we should focus less on the intrinsic capacities of robots and more on how we relate to them. If those relations are thick and meaningful, then perhaps we should accept that robots have moral standing. Erica Neely proceeds from a principle of moral precaution, arguing that even if we are unsure of the moral standing of robots we should err on the side of over-inclusivity rather than under-inclusivity when it comes to this issue: it is much worse to exclude a being with moral standing to include one without. Estrada is almost the polar opposite of Bryson, welcoming the moral and legal disruption that embracing robots would entail because it would loosen the stranglehold of humanism on our ethical code.
To be clear, this is just a small sample of those who have expressed an opinion about this topic. There are many others that I just don’t have time to discuss. I should, however, say something here about this evening’s discussant, Sven and his views on the matter. I had the fortune of reading a manuscript of Sven’s forthcoming book Humans, Robots and Ethics. It is an excellent and entertaining contribution to the field of robot ethics and in it Sven shares his own views on the moral standing of robots. I’m sure he will explain them later on but, for the time being, I would tentatively place him somewhere near Kate Darling on this map: he thinks we should be open to the idea of treating robots as if they had moral standing, but not because of what the robots themselves are but because of what respecting them says about our attitudes to other humans.
And what of myself? Where do I fit in all of this? People would probably classify me as belonging to the pro side. I have argued that we should be open to the idea that robots have moral standing. But I would much prefer to transcend this tribalistic approach to the issue. I am not advocate for the moral standing of robots. I think many of the concerns raised by those on the anti side are valid. Debating the moral standing of robots can seem, at times, ridiculous and a distraction from other important questions in robot ethics; and accepting them into our moral communities will, undoubtedly, lead to some legal and moral disruption (though I would add that not all disruption is a bad thing). That said, I do care about the principles we should use to decide questions of moral standing, and I think that those on the anti of the debate sometimes use bad arguments to support their views. This is why, in the remainder of this lecture, I will defend a particular approach to settling the question of the moral standing of robots. I do so in the hope that this can pave the way to a more fruitful and less tribalistic debate.
In this sense, I am trying to return to what may be the true lesson of Sherif’s famous experiment on tribalism. In her fascinating book The Lost Boys: Inside Muzafer Sherif’s Robbers Cave Experiment, Gina Perry has revealed the hidden history behind Sherif’s work. It turns out that Sherif tried to conduct the exact same experiment as he did in Robber’s Cave one year before in Middle Grove, New York. It didn’t work out. No matter what the experimenters did to encourage conflict, the boys refused to get sucked into it. Why was this? One suggestion is that at Middle Grove, Sherif didn’t sort the boys into two arbitrary groups as soon as they arrived. They were given the chance to mingle and get to know one another before being segregated. This initial intermingling may have inoculated them from tribalism. Perhaps we can do the same thing with philosophical dialogue? I live in hope.
3. In Defence of Ethical Behaviourism
The position I wish to defend is something I call ‘ethical behaviourism’. According to this view, the behavioural representations of another entity toward you are a sufficient ground for determining their moral status. Or, to put it slightly differently, how an entity looks and acts is enough to determine its moral status. If it looks and acts like a duck, then you should probably treat it like you treat any other duck.
Ethical behaviourism works through comparisons. If you are unsure of the moral status of a particular entity — for present purposes this will be a robot but it should be noted that ethical behaviourism has broader implications — then you should compare its behaviours to that of another entity that is already agreed to have moral status — a human or an animal. If the robot is roughly performatively equivalent to that other entity, then it too has moral status. I say “roughly” since no two entities are ever perfectly equivalent. If you compared two adult human beings you would spot performative differences between them, but this wouldn’t mean that one of them lacks moral standing as a result. The equivalence test is an inexact one, not an exact one.
There is nothing novel in ethical behaviourism. It is, in effect, just a moral variation of the famous Turing Test for machine intelligence. Where Turing argued that we should assess intelligence on the basis of behaviour, I am arguing that we should determine moral standing on the basis of behaviour. It is also not a view that is original to me. Others have defended similar views, even if they haven’t explicitly labelled it as such.
Despite the lack of novelty, ethical behaviourism is easily misunderstood and frequently derided. So let me just clarify a couple of points. First, note that it is a practical and epistemic thesis about how we can settle questions of moral standing; it is not an abstract metaphysical thesis about what it is that grounds moral standing. So, for example, someone could argue that the capacity to feel pain is the metaphysical grounding for moral status and that this capacity depends on having a certain mental apparatus. The ethical behaviourist can agree with this. They will just argue that the best evidence we have for determining whether an entity has the capacity to feel pain is behavioural. Furthermore, ethical behaviourism is agnostic about the broader consequences of its comparative tests. To say that one entity should have the same moral standing as another entity does not mean both are entitled to a full set of legal and moral rights. That depends on other considerations. A goat could have moral standing, but that doesn’t mean it has the right to own property. This is important because when I am arguing that we should apply this approach to robots and I am not thereby endorsing a broader claim that we should grant robots legal rights or treat them like adult human beings. This depends on who or what the robots is being compared to.
So what’s the argument for ethical behaviourism? I have offered different formulations of this but for this evening’s lecture I suggest that it consists of three key propositions or premises.
- (P1) The most popular criteria for moral status are dependent on mental states or capacities, e.g. theories focused on sentience, consciousness, having interests, agency, and personhood.
- (P2) The best evidence — and oftentimes the only practicable evidence — for the satisfaction of these criteria is behavioural.
- (P3) Alternative alleged grounds of moral status or criteria for determining moral status either fail to trump or dislodge the sufficiency of the behavioural evidence.
Therefore, ethical behaviourism is correct: behaviour provides a sufficient basis for settling questions of moral status.
I take it that the first premise of this argument is uncontroversial. Even if you think there are other grounds for moral status, I suspect you agree that an entity with sentience or consciousness (etc) has some kind of moral standing. The second premise is more controversial but is, I think, undeniable. It’s a trite observation but I will make it anyway: We don’t have direct access to one another’s minds. I cannot crawl inside your head and see if you really are experiencing pain or suffering. The only thing I have to go on is how you behave and react to the world. This is true, by the way, even if I can scan your brain and see whether the pain-perceiving part of it lights up. This is because the only basis we have for verifying the correlations between functional activity in the brain and mental states is behavioural. What I mean is that scientists ultimately verify those correlations by asking people in the brain scanners what they are feeling. So all premise (2) is saying is that if the most popular theories of moral status are to work in practice, it can only be because we use behavioural evidence to guide their application.
That brings us to premise (3): that all other criteria fail to dislodge the importance of behavioural evidence. This is the most controversial one. Many people seem to passionately believe that there are other ways of determining moral status and indeed they argue that relying on behavioural evidence would be absurd. Consider these two recent Twitter comments on an article I wrote about ethical behaviourism and how it relates to animals and robots:
First comment: “[This is] Errant #behaviorist #materialist nonsense…Robots are inanimate even if they imitate animal behavior. They don’t want or care about anything. But knock yourself out. Put your toaster in jail if it burns your toast.”
Second comment: “If I give a hammer a friendly face so some people feel emotionally attached to it, it still remains a tool #AnthropomorphicFallacy”
These are strong statements, but they are not unusual. I encounter this kind of criticism quite frequently. But why? Why are people so resistant to ethical behaviourism? Why do they think that there must be something more to how we determine moral status? Let’s consider some of the most popular objections.
4. Objections and Replies
In a recent paper, I suggested that there were seven (more, depending on how you count) major objections to ethical behaviourism. I won’t review all seven here, but I will consider four of the most popular ones. Each of these objections should be understood as an attempt to argue that behavioural evidence by itself cannot suffice for determining moral standing. Other evidence matters as well and can ‘defeat’ the behavioural evidence.
(A) The Material Cause Objection
The first objection is that the ontology of an entity makes a difference to its moral standing. To adopt the Aristotelian language, we can say that the material cause of an entity (i.e. what it is made up of) matters more than behaviour when it comes to moral standing. So, for example, someone could argue that robots lack moral standing because they are not biological creatures. They are not made from the same ‘wet’ organic components as human beings or animals. Even if they are performatively equivalent to human beings or animals, this ontological difference scuppers any claim they might have to moral standing.
I find this objection unpersuasive. It smacks to me of biological mysterianism. Why exactly does being made of particular organic material make such a crucial difference? Imagine if your spouse, the person you live with everyday, was suddenly revealed to be an alien from the Andromeda galaxy. Scientists conduct careful tests and determine that they are not a carbon-based lifeform. They are made from something different, perhaps silicon. Despite this, they still look and act in the same way as they always have (albeit now with some explaining to do). Would the fact that they are made of different stuff mean that they no longer warrant any moral standing in your eyes? Surely not. Surely the behavioural evidence suggesting that they still care about you and still have the mental capacities you used to associate with moral standing would trump the new evidence you have regarding their ontology. I know non-philosophers dislike thought experiments of this sort, finding them to be slightly ridiculous and far-fetched. Nevertheless, I do think they are vital in this context because they suggest that behaviour does all the heavy lifting when it comes to assessing moral standing. In other words, behaviour matters more than matter. This is also, incidentally, one reason why it is wrong to say that ethical behaviourism is a ‘materialist’ view: ethical behaviourism is actually agnostic regarding the ontological instantiation of the capacities that ground moral status; it is concerned only with the evidence that is sufficient for determining their presence.
All that said, I am willing to make one major concession to the material cause objection. I will concede that ontology might provide an alternative, independent ground for determining the moral status of an entity. Thus, we might accept that an entity that is made from the right biological stuff has moral standing, even if they lack the behavioural sophistication we usually require for moral standing. So, for example someone in a permanent coma might have moral standing because of what they are made of, and not because of what they can do. Still, all this shows is that being made of the right stuff is an independent sufficient ground for moral standing, not that it is a necessary ground for moral standing. The latter is what would need to be proved to undermine ethical behaviourism.
(B) The Efficient Cause Objection
The second objection is that how an entity comes into existence makes a difference to its moral standing. To continue the Aristotelian theme, we can say that the efficient cause of existence is more important than the unfolding reality. This is an objection that the philosopher Michael Hauskeller hints at in his work. Hauskeller doesn’t focus on moral standing per se, but does focus on when we can be confident that another entity cares for us or loves us. He concedes that behaviour seems like the most important thing when addressing this issue — what else could caring be apart from caring behaviour? — but then resiles from this by arguing that how the being came into existence can undercut the behavioural evidence. So, for example, a robot might act as if it cares about you, but when you learn that the robot was created and manufactured by a team of humans to act as if it cares for you, then you have reason to doubt the sincerity of its behaviour.
It could be that what Hauskeller is getting at here is that behavioural evidence can often be deceptive and misleading. If so, I will deal with this concern in a moment. But it could also be that he thinks that the mere fact that a robot was programmed and manufactured, as opposed to being evolved and developed, makes a crucial difference to moral standing. If that is what he is claiming, then it is hard to see why we should take it seriously. Again, imagine if your spouse told you that they were not conceived and raised in the normal way. They were genetically engineered in a lab and then carefully trained and educated. Having learned this, would you take a new view of their moral standing? Surely not. Surely, once again, how they actually behave towards you — and not how they came into existence — would be what ultimately mattered. We didn’t deny the first in vitro baby moral standing simply because she came into existence in a different way from ordinary human beings. The same principle should apply to robots.
Furthermore, if this is what Hauskeller is arguing, it would provide us with an unstable basis on which to make crucial judgments of moral standing. After all, the differences between humans and robots with respect to their efficient causes is starting to breakdown. Increasingly, robots are not being programmed and manufactured from the top-down to follow specific rules. They are instead given learning algorithms and then trained on different datasets with the process sometimes being explicitly modeled on evolution and childhood development. Similarly, humans are increasingly being designed and programmed from the top down, through artificial reproduction, embryo selection and, soon, genetic engineering. You may object to all this tinkering with the natural processes of human development and conception. But I think you would be hard pressed to deny a human that came into existence as a result of these process the moral standing you ordinarily give to other human beings.
(C) The Final Cause Objection
The third objection is that the purposes an entity serves and how it is expected to fulfil those purposes makes a difference to its moral standing. This is an objection that Joanna Bryson favours in her work. In several papers, she has argued that because robots will be designed to fulfil certain purposes on our behalf (i.e. they will be designed to serve us) and because they will be owned and controlled by us in the process, they should not have moral standing. Now, to be fair, Bryson is more open to the possibility of robot moral standing than most. She has said, on several occasions, that it is possible to create robots that have moral standing. She just thinks that that this should not happen, in part because they will be owned and controlled by us, and because they will be (and perhaps should be) designed to serve our ends.
I don’t think there is anything in this that dislodges or upsets ethical behaviourism. For one thing, I find it hard to believe that the fact that an entity has been designed to fulfil a certain purpose should make a crucial difference to its moral standing. Suppose, in the future, human parents can genetically engineer their offspring to fulfil certain specific ends. For example, they can select genes that will guarantee (with the right training regime) that their child will be a successful athlete (this is actually not that dissimilar to what some parents try to do nowadays). Suppose they succeed. Would this fact alone undermine the child’s claim to moral standing? Surely not, and surely the same standard should apply to a robot. If it is performatively equivalent to another entity with moral standing, then the mere fact that it has been designed to fulfil a specific purpose should not affect its moral standing.
Related to this, it is hard to see why the fact that we might own and control robots should make a critical difference to their moral standing. If anything, this inverts the proper order of moral justification. The fact that a robot looks and acts like another entity that we believe to have moral standing should cause us to question our approach to ownership and control, not vice versa. We once thought it was okay for humans to own and control other humans. We were wrong to think this because it ignored the moral standing of those other humans.
That said, there are nuances here. Many people think that animals have some moral standing (i.e. that we need to respect their welfare and well-being) but that it is not wrong to own them or attempt to control them. The same approach might apply to robots if they are being compared to animals. This is the crucial point about ethical behaviourism: the ethical consequences of accepting that a robot is performatively equivalent to another entity with moral standing depends, crucially, on who or what that other entity is.
(D) The Deception Objection
The fourth objection is that ethical behaviourism cannot work because it is too easy to be deceived by behavioural cues. A robot might look and act like it is in pain, but this could just be a clever trick, used by its manufacturer, to foster false sympathy. This is, probably, the most important criticism of ethical behaviourism. It is what I think lurks behind the claim that ethical behaviourism is absurd and must be resisted.
It is well-known that humans have a tendency toward hasty anthropomorphism. That is, we tend to ascribe human-like qualities to features of our environment without proper justification. We anthropomorphise the weather, our computers, the trees and the plants, and so forth. It is easy to ‘hack’ this tendency toward hasty anthropomorphism. As social roboticists know, putting a pair of eyes on a robot can completely change how a human interacts with it, even if the robot cannot see anything. People worry, consequently, that ethical behaviourism is easily exploited by nefarious technology companies.
I sympathise with the fear that motivates this objection. It is definitely true that behaviour can be misleading or deceptive. We are often misled by the behaviour of our fellow humans. To quote Shakespeare, someone can ‘smile and smile and be a villain’. But what is the significance of this fact when it comes to assessing moral status? To me, the significance is that it means we should be very careful when assessing the behavioural evidence that is used to support a claim about moral status. We shouldn’t extrapolate too quickly from one behaviour. If a robot looks and acts like it is in pain (say) that might provide some warrant for thinking it has moral status, but we should examine its behavioural repertoire in more detail. It might emerge that other behaviours are inconsistent with the hypothesis that it feels pain or suffering.
The point here, however, is that we are always using other behavioural evidence to determine whether the initial behavioural evidence was deceptive or misleading. We are not relying on some other kind of information. Thus, for example, I think it would be a mistake to conclude that a robot cannot feel pain, even though it performs as if it does, because the manufacturer of the robot tells us that it was programmed to do this, or because some computer engineer can point to some lines of code that are responsible for the pain performance. That evidence by itself — in the absence of other countervailing behavioural evidence — cannot undermine the behavioural evidence suggesting that the robot does feel pain. Think about it like this: imagine if a biologist came to you and told you that evolution had programmed the pain response into humans in order to elicit sympathy from fellow humans. What’s more, imagine if a neuroscientist came to you and and told you she could point to the exact circuit in the brain that is responsible for the human pain performance (and maybe even intervene in and disrupt it). What they say may well be true, but it wouldn’t mean that the behavioural evidence suggesting that your fellow humans are in pain can be ignored.
This last point is really the crucial bit. This is what is most distinctive about the perspective of ethical behaviourism. The tendency to misunderstand it, ignore it, or skirt around it, is why I think many people on the ‘anti’ side of the debate make bad arguments.
5. Implications and Conclusions
That’s all I will say in defence of ethical behaviourism this evening. Let me conclude by addressing some of its implications and heading off some potential misunderstandings.
First, let me re-emphasise that ethical behaviourism is about the principles we should apply when assessing the moral standing of robots. In defending it, I am not claiming that robots currently have moral standing or, indeed, that they will ever have moral standing. I think this is possible, indeed probable, but I could be wrong. The devil is going to be in the detail of the behavioural tests we apply (just as it is with the Turing test for intelligence).
Second, there is nothing in ethical behaviourism that suggests that we ought to create robots that cross the performative threshold to moral standing. It could be, as people like Bryson and Van Wysnberghe argue, that this is a very bad idea: that it will be too disruptive of existing moral and legal norms. What ethical behaviourism does suggest, however, is that there is an ethical weight to the decision to create human-like and animal-like robots that may be underappreciated by robot manufacturers.
Third, acknowledging the potential risks, there are also potential benefits to creating robots that cross the performative threshold. Ethical behaviourism can help to reveal a value to relationships with robots that is otherwise hidden. If I am right, then robots can be genuine objects of moral affection, friendship and love, under the right conditions. In other words, just as there are ethical risks to creating human-like and animal-like robots, there are also ethical rewards and these tend to be ignored, ridiculed or sidelined in the current debate.
Fourth, and related to this previous point, the performative threshold that robots have to cross in order to unlock the different kinds of value might vary quite a bit. The performative threshold needed to attain basic moral standing might be quite low; the performative threshold needed to say that a robot can be a friend or a partner might be substantially higher. A robot might have to do relatively little to convince us that it should be treated with moral consideration, but it might have to do a lot to convince us that it is our friend.
These are topics that I have explored in greater detail in some of my papers, but they are also topics that Sven has explored at considerable length. Indeed, several chapters of his forthcoming book are dedicated to them. So, on that note, it is probably time for me to shut up and hand over to him and see what he has to say about all of this.
Reflections and Follow Ups After I delivered the above lecture, my colleague and friend Sven Nyholm gave a response and there were some questions and challenges from the audience. I cannot remember every question that was raised, but I thought I would respond to a few that I can remember.
1. The Randomisation Counterexample
One audience member (it was Nathan Wildman) presented an interesting counterexample to my claim that other kinds of evidence don’t defeat or undermine the behavioural evidence for moral status. He argued that we could cook-up a possible scenario in which our knowledge of the origins of certain behaviours did cause us to question whether it was sufficient for moral status.
He gave the example of a chatbot that was programmed using a randomisation technique. The chatbot would generate text at random (perhaps based on some source dataset). Most of the time the text is gobbledygook but on maybe one occasion it just happens to have a perfectly intelligible conversation with you. In other words, whatever is churned out by the randomisation algorithm happens to perfectly coincide with what would be intelligible in that context (like picking up a meaningful book in Borges’s Library of Babel). This might initially cause you to think it has some significant moral status, but if the computer programmer came along and told you about the randomisation process underlying the programming you would surely change your opinion. So, on this occasion, it looks like information about the causal origins of the behaviour, makes a difference to moral status.
Response: This is a clever counterexample but I think it overlooks two critical points. First, it overlooks the point I make about avoiding hasty anthropomorphisation towards the end of my lecture. I think we shouldn’t extrapolate too much from just one interaction with a robot. We should conduct a more thorough investigation of the robot’s (or in this case the chatbot’s) behaviours. If the intelligible conversation was just a one-off, then we will quickly be disabused of our belief that it has moral status. But if it turns out that the intelligible conversation was not a one-off, then I don’t think the evidence regarding the randomisation process would have any such effect. The computer programmer could shout and scream as much as he/she likes about the randomisation algorithm, but I don’t think this would suffice to undermine the consistent behavioural evidence. This links to a second, and perhaps deeper metaphysical point I would like to make: we don’t really know what the true material instantiation of the mind is (if it is indeed material). We think the brain and its functional activity is pretty important, but we will probably never have a fully satisfactory theory of the relationship between matter and mind. This is the core of the hard problem of consciousness. Given this, it doesn’t seem wise or appropriate to discount the moral status of this hypothetical robot just because it is built on a randomisation algorithm. Indeed, if such a robot existed, it might give us reason to think that randomisation was one of the ways in which a mind could be functionally instantiated in the real world.
I should say that this response ignores the role of moral precaution in assessing moral standing. If you add a principle of moral precaution to the mix, then it may be wrong to favour a more thorough behavioural test. This is something I discuss a bit in my article on ethical behaviourism.
2. The Argument confuses how we know X is valuable with what makes X actually valuable
One point that Sven stressed in his response, and which he makes elsewhere too, is that my argument elides or confuses two separate things: (i) how we know whether something is of value and (ii) what it is that makes it valuable. Another way of putting it: I provide a decision-procedure for deciding who or what has moral status but I don’t thereby specify what it is that makes them have moral status. It could be that the capacity to feel pain is what makes someone have moral standing and that we know someone feels pain through their behaviour, but this doesn’t mean that they have moral standing because of their behaviour.
Response: This is probably a fair point. I may on occasion elide these two things. But my feeling is that this is a ‘feature’ rather than a ‘bug’ in my account. I’m concerned with how we practically assess and apply principles of moral standing in the real world, and not so much with what it is that metaphysically undergirds moral standing.
3. Proxies for Behaviour versus Proxies for Mind
Another comment (and I apologise for not remembering who gave it) is that on my theory behaviour is important but only because it is a proxy for something else, namely some set of mental states or capacities. This is similar to the point Sven is making in his criticism. If that’s right, then I am wrong to assume that behaviour is the only (or indeed the most important) proxy for mental states. Other kinds of evidence serve as proxies for mental states. The example was given of legal trials where the prosecution is trying to prove what the mental status of the defendant was at the time of an offence. They don’t just rely on behavioural evidence. They also rely on other kinds of forensic evidence to establish this.
Response: I don’t think this is true and this gets to a deep feature of my theory. To take the criminal trial example, I don’t think it is true to say that we use other kinds of evidence as proxies for mental states. I think we use them as proxies for behaviour which we then use as proxies for mental states. In other words, the actual order of inference goes:
- Other evidence → behaviour → mental state
And not:
- Other evidence → mental state
This is the point I was getting at in my talk when I spoke about how we make inferences from functional brain activity to mental state. I believe what happens when we draw a link between brain activity and mental state, what we are really doing is this:
- Brain state → behaviour → mental state
And not
- Brain state → mental state.
Now, it is, of course, true to say that sometimes scientists think we can make this second kind of inference. For example, purveyors of brain based lie detection tests (and, indeed, other kinds of lie detection test) try to draw a direct line of inference from a brain state to a mental state, but I would argue that this is only because they have previously verified their testing protocol by following the “brain state → behaviour → mental state” route and confirming that it is reliable across multiple tests. This gives them the confidence to drop the middle step on some occasions, but ultimately this is all warranted (if it is, in fact, warranted – brain-based lie detection is controversial) because the scientists first took the behavioural step. To undermine my view, you would have to show that it is possible to cut out the behavioural step in this inference pattern. I don’t think this can be done, but perhaps I can be proved wrong.
This is perhaps the most metaphysical aspect of my view.
4. Default Settings and Practicalities
Another point that came up in conversation with Sven, Merel Noorman and Silvia de Conca, had to do with the default assumptions we are likely to have when dealing with robots and how this impacts on the practicalities of robots being accepting into the moral circle. In other words, even if I am right in some abstract, philosophical sense, will anyone actually follow the behavioural test I advocate? Won’t there be a lot of resistance to it in reality?
Now, as I mentioned in my lecture, I am not an activist for robot rights or anything of the sort. I am interested in the general principles we should apply when settling questions of moral status; not with whether a particular being, such as a robot, has acquired moral status. That said, implicit views about the practicalities of applying the ethical behaviourist test may play an important role in some of the arguments I am making.
One example of this has to do with the ‘default’ assumption we have when interpreting the behaviour of humans/animals vis-à-vis robots. We tend to approach humans and animals with an attitude of good faith, i.e. we assume their each of their outward behaviours is a sincere representation of their inner state of mind. It’s only if we receive contrary evidence that we will start to doubt the sincerity of the behaviour.
But what default assumption do we have when confronting robots? It seems plausible to suggest that most people will approach them with an attitude of bad faith. They will assume that their behaviours are representative of nothing at all and will need a lot of evidence to convince them that they should be granted some weight. This suggests that (a) not all behavioural evidence is counted equally and (b) it might be very difficult, in practice, for robots to be accepted into the moral circle.
Response: I don’t see this as a criticism of ethical behaviourism but, rather, a warning to anyone who wishes to promote it. In other words, I accept that people will resist ethical behaviourism and may treat robots with greater suspicion than human or animal agents. One of the key points of this lecture and the longer academic article I wrote about the topic was to address this suspicion and skepticism. Nevertheless, the fact that there may be these practical difficulties does not mean that ethical behaviourism is incorrect. In this respect, it is worth noting that Turing was acutely aware of this problem when he originally formulated his 'Imitation Game' test. The reason why the test was purely text-based in its original form was to prevent human-centric biases affecting its operation.
5. Ethical Mechanicism vs Ethical Behaviourism
After I posted this article, Natesh Ganesh posted a critique of my handling of the deception objection on Twitter. He made two interesting points. First, he argued that the thought experiment I used to dismiss the deception objection was misleading and circular. If a scientist revealed the mechanisms underlying my own pain performances I would have no reason to doubt that the pain was genuine since I already know that someone with my kind of neural circuitry can experience pain. If they revealed the mechanisms underlying a robot’s pain performances things would be different because I do not yet have a reason to think that a being with that kind of mechanism can experience genuine pain. As a result, the thought experiment is circular because only somebody who already accepted ethical behaviourism would be so dismissive of the mechanistic evidence. Here’s how Natesh expresses the point:
“the analogy in the last part [the response to the deception objection] seems flawed. Showing me the mechanisms of pain in entities (like humans) who we share similar mechanisms with & agree have moral standing is different from showing me the mechanisms of entities (like robots) whose moral standing we are trying to determine. Denying experience of pain in the 1st simply because I now know the circuitry would imply denying your own pain & hence moral standing. But accepting/ denying the 2nd if its a piece of code implicitly depends on whether you already accept/deny ethical behaviorism. It is just circular to appeal to that example as evidence.”
He then follows up with a second point (implicit in what was just said) about the importance of mechanical similarities between entities when it comes to assessing moral standing:
“I for one am more likely to [believe] a robot can experience pain if it shows the behavior & the manufacturer opened it up & showed me the circuitry and if that was similar to my own (different material perhaps) I am more likely to accept the robot experiences pain. In this case once again I needed machinery on top of behavior.”
What I would say here, is that Natesh, although not completely dismissive of the importance of behaviour to assessing moral standing, is a fan of ethical mechanicism, and not ethical behaviourism. He thinks you must have mechanical similarity (equivalence?) before you can conclude that two entities share moral standing.
Response: On the charge of circularity, I don’t think this is quite fair. The thought experiment I propose when responding to the deception objection is, like all thought experiments, intended to be an intuition pump. The goal is to imagine a situation in which you could describe and intervene in the mechanical underpinning of a pain performance with great precision (be it a human pain performance or otherwise) and ask whether the mere fact that you could describe the mechanism in detail or intervene in it would be make a difference to the entity’s moral standing. My intuitions suggest it wouldn’t make a difference, irrespective of the details of the mechanism (this is the point I make, above, in relation to the example given by Nathan Wildman about the robot whose behaviour is the result of a random-number generator programme). Perhaps other people’s intuitions are pumped in a different direction. That can happen but it doesn’t mean the thought experiment is circular.
What about the importance of mechanisms in addition to behaviour? This is something I address in more detail in the academic paper. I have two thoughts about it. First, I could just bite the bullet and agree that the underlying mechanisms must be similar too. This would just add an additional similarity test to the assessment of moral status. There would then be similar questions as to how similar the mechanisms must be. Is it enough if they are, roughly, functionally similar or must they have the exact same sub-components and processes? If the former, then it still seems possible in principle for roboticists to create a functionally similar underlying mechanism and this could then ground moral standing for robots.
Second, despite this, I would still push back against the claim that similar underlying mechanisms are necessary. This strikes me as being just a conservative prejudgment rather than a good reason for denying moral status to behaviourally equivalent entities. Why are we so confident that only entities with our neurological mechanisms (or something very similar) can experience pain (or instantiate the other mental properties relevant to moral standing)? Or, to put it less controversially, why should we be so confident that mechanical similarity undercuts behavioural similarity? If there is an entity that looks and acts like it is in pain (or has interests, a sense of personhood, agency etc), and all the behavioural tests confirm this, then why deny it moral standing because of some mechanical differences?
Part of the resistance here could be that people are confusing two different claims:
- Claim 1: it is impossible (physically, metaphysically) for an entity that lacks sufficient mechanical similarity (with humans/animals) to have the behavioural sophistication we associate with experiencing pain, having agency etc.
- Claim 2: an entity that has the behavioural sophistication we associate with experiencing pain, having agency (etc) but then lacks mechanical similarity to other entities with such behavioural sophistication, should be denied moral standing because they lack mechanical similarity.
Ethical behaviourism denies claim 2, but it does not, necessarily, deny claim 1. It could be the case that mechanical similarity is essential for behavioural similarity. This is something that can only be determined after conducting the requisite behavioural tests. The point, as always throughout my defence of the position, is that the behavioural evidence should be our guide. This doesn’t mean that other kinds of evidence are irrelevant but simply that they do not carry as much weight. My sense is that people who favour ethical mechanicism have a very strong intuition in favour of claim 1, which they then carry over into support for claim 2. This carry over is not justified as the two claims are not logically equivalent.
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In this episode I talk to Christian Munthe. Christian is a Professor of Practical Philosophy at the University of Gothenburg, Sweden. He conducts research and expert consultation on ethics, value and policy issues arising in the intersection of health, science & technology, the environment and society. He is probably best-known for his work on the precautionary principle and its uses in ethical and policy debates. This was the central topic of his 2011 book The Price of Precaution and the Ethics of Risk. We talk about the problems with the practical application of the precautionary principle and how they apply to the debate about existential risk. You can download the episode here or listen below.
You can also subscribe on Apple Podcasts, Stitcher and a variety of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:35 - What is the precautionary principle? Where did it come from? * 6:08 - The key elements of the precautionary principle * 9:35 - Precaution vs. Cost Benefit Analysis * 15:40 - The Problem of the Knowledge Gap in Existential Risk * 21:52 - How do we fill the knowledge gap? * 27:04 - Why can't we fill the knowledge gap in the existential risk debate? * 30:12 - Understanding the Black Hole Challenge * 35:22 - Is it a black hole or total decisional paralysis? * 39:14 - Why does precautionary reasoning have a 'price'? * 44:18 - Can we develop a normative theory of precautionary reasoning? Is there such a thing as a morally good precautionary reasoner? * 52:20 - Are there important practical limits to precautionary reasoning? * 1:01:38 - Existential risk and the conservation of value
Relevant Links Christian's Academic Homepage * Christian's Twitter account * "The Black Hole Challenge: Precaution, Existential Risks and the Problem of Knowledge Gaps" by Christian * The Price of Precaution and the Ethics of Risk by Christian * Hans Jonas's The Imperative of Responsibility* * The Precautionary Approach from the Rio Declaration * Episode 62 with Olle Häggström
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In this episode I talk to Joseph Reagle. Joseph is an Associate Professor of Communication Studies at Northeastern University and a former fellow (in 1998 and 2010) and faculty associate at the Berkman Klein Center for Internet and Society at Harvard. He is the author of several books and papers about digital media and the social implications of digital technology. Our conversation focuses on his most recent book: Hacking Life: Systematized Living and its Discontents (MIT Press 2019).
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher and a variety of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:52 - What is life-hacking? The four features of life-hacking * 4:20 - Life Hacking as Self Help for the 21st Century * 7:00 - How does technology facilitate life hacking? * 12:12 - How can we hack time? * 20:00 - How can we hack motivation? * 27:00 - How can we hack our relationships? * 31:00 - The Problem with Pick-Up Artists * 34:10 - Hacking Health and Meaning * 39:12 - The epistemic problems of self-experimentation * 49:05 - The dangers of metric fixation * 54:20 - The social impact of life-hacking * 57:35 - Is life hacking too individualistic? Should we focus more on systemic problems? * 1:03:15 - Does life hacking encourage a less intuitive and less authentic mode of living? * 1:08:40 - Conclusion (with some further thoughts on inequality)
Relevant Links* Joseph's Homepage * Joseph's Blog * Hacking Life: Systematized Living and Its Discontents (including open access HTML version) * The Lifehacker Website * The Quantified Self Website * Seth Roberts' first and final column: Butter Makes me Smarter * The Couple that Pays Each Other to Put the Kids to Bed (story about the founders of the Beeminder App) * 'The Quantified Relationship' by Danaher, Nyholm and Earp * Episode 6 - The Quantified Self with Deborah Lupton
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In this episode I talk to Olle Häggström. Olle is a professor of mathematical statistics at Chalmers University of Technology and a member of the Royal Swedish Academy of Sciences (KVA) and of the Royal Swedish Academy of Engineering Sciences (IVA). Olle’s main research is in probability theory and statistical mechanics, but in recent years he has broadened his research interests to focus applied statistics, philosophy, climate science, artificial intelligence and social consequences of future technologies. He is the author of Here be Dragons: Science, Technology and the Future of Humanity (OUP 2016). We talk about AI motivations, specifically the Omohundro-Bostrom theory of AI motivation and its weaknesses. We also discuss AI risk denialism.
You can download the episode here or listen below. You can also subscribe to the podcast on Apple Podcasts, Stitcher and a variety of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:02 - Do we need to define AI? * 4:15 - The Omohundro-Bostrom theory of AI motivation * 7:46 - Key concepts in the Omohundro-Bostrom Theory: Final Goals vs Instrumental Goals * 10:50 - The Orthogonality Thesis * 14:47 - The Instrumental Convergence Thesis * 20:16 - Resource Acquisition as an Instrumental Goal * 22:02 - The importance of goal-content integrity * 25:42 - Deception as an Instrumental Goal * 29:17 - How the doomsaying argument works * 31:46 - Critiquing the theory: the problem of self-referential final goals * 36:20 - The problem of incoherent goals * 42:44 - Does the truth of moral realism undermine the orthogonality thesis? * 50:50 - Problems with the distinction between instrumental goals and final goals * 57:52 - Why do some people deny the problem of AI risk? * 1:04:10 - Strong versus Weak AI Scepticism * 1:09:00 - Is it difficult to be taken seriously on this topic?
Relevant Links* Olle's Blog * Olle's webpage at Chalmers University * 'Challenges to the Omohundro-Bostrom framework for AI Motivations' by Olle (highly recommended) * 'The Superintelligent Will' by Nick Bostrom * 'The Basic AI Drives' by Stephen Omohundro * Olle Häggström: Science, Technology, and the Future of Humanity (video) * Olle Häggström and Thore Husveldt debate AI Risk (video) * Summary of Bostrom's theory (by me) * 'Why AI doomsayers are like sceptical theists and why it matters' by me
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In this episode I talk to Roman Yampolskiy. Roman is a Tenured Associate Professor in the department of Computer Engineering and Computer Science at the Speed School of Engineering, University of Louisville. He is the founding and current director of the Cyber Security Lab and an author of many books and papers on AI security and ethics, including Artificial Superintelligence: a Futuristic Approach. We talk about how you might test for machine consciousness and the first steps towards a science of AI welfare.
You can listen below or download here. You can also subscribe to the podcast on Apple, Stitcher and a variety of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:30 - Artificial minds versus Artificial Intelligence * 6:35 - Why talk about machine consciousness now when it seems far-fetched? * 8:55 - What is phenomenal consciousness? * 11:04 - Illusions as an insight into phenomenal consciousness * 18:22 - How to create an illusion-based test for machine consciousness * 23:58 - Challenges with operationalising the test * 31:42 - Does AI already have a minimal form of consciousness? * 34:08 - Objections to the proposed test and next steps * 37:12 - Towards a science of AI welfare * 40:30 - How do we currently test for animal and human welfare * 44:10 - Dealing with the problem of deception * 47:00 - How could we test for welfare in AI? * 52:39 - If an AI can suffer, do we have a duty not to create it? * 56:48 - Do people take these ideas seriously in computer science? * 58:08 - What next?
Relevant Links* Roman's homepage * 'Detecting Qualia in Natural and Artificial Agents' by Roman * 'Towards AI Welfare Science and Policies' by Soenke Ziesche and Roman Yampolskiy * The Hard Problem of Consciousness * 25 famous optical illusions * Could AI get depressed and have hallucinations?
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This audio essay looks at the Epicurean philosophy of death, focusing specifically on how they addressed the problem of premature death. The Epicureans believe that premature death is not a tragedy, provided it occurs after a person has attained the right state of pleasure. If you enjoy listening to these audio essays, and the other podcast episodes, you might consider rating and/or reviewing them on your preferred podcasting service.
You can listen below or download here. You can also subscribe on Apple, Stitcher or a range of other services (the RSS feed is here).
I've written lots about the philosophy of death over the years. Here are some relevant links if you would like to do further reading on the topic:
- The Badness of Death and the Meaning of Life (index)
- The Lucretian Symmetry Argument (Part 1 and Part 2)
- Is Death Bad or Less Good? (Part 1, Part 2, Part 3, and Part 4)
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In this episode I talk to Carissa Véliz. Carissa is a Research Fellow at the Uehiro Centre for Practical Ethics and the Wellcome Centre for Ethics and Humanities at the University of Oxford. She works on digital ethics, practical ethics more generally, political philosophy, and public policy. She is also the Director of the research programme 'Data, Privacy, and the Individual' at the IE's Center for the Governance of Change'. We talk about the problems with online speech and how to use pseudonymity to address them.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher, and a variety of other podcasting services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:25 - The problems with online speech * 4:55 - Anonymity vs Identifiability * 9:10 - The benefits of anonymous speech * 16:12 - The costs of anonymous speech - The online Ring of Gyges * 23:20 - How digital platforms mediate speech and make things worse * 28:00 - Is speech more trustworthy when the speaker is identifiable? * 30:50 - Solutions that don't work * 35:46 - How pseudonymity could address the problems with online speech * 41:15 - Three forms of pseudonymity and how they should be used * 44:00 - Do we need an organisation to manage online pseudonyms? * 49:00 - Thoughts on the Journal of Controversial Ideas * 54:00 - Will people use pseudonyms to deceive us? * 57:30 - How pseudonyms could address the issues with un-PC speech * 1:02:04 - Should we be optimistic or pessimistic about the future of online speech?
Relevant Links Carissa's Webpage * "Online Masquerade: Redesigning the Internet for Free Speech Through the Use of Pseudonyms" by Carissa * "Why you might want to think twice about surrendering online privacy for the sake of convenience" by Carissa * "What If Banks Were the Main Protectors of Customers’ Private Data?" by Carissa * The Secret Barrister * Delete: The Virtue of Forgetting in the Digital Age* by Viktor Mayer-Schönberger * Mill's Argument for Free Speech: A Guide * 'Here Comes the Journal of Controversial Ideas. Cue the Outcry' by Bartlett
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In this episode I talk to Phil Torres. Phil is an author and researcher who primarily focuses on existential risk. He is currently a visiting researcher at the Centre for the Study of Existential Risk at Cambridge University. He has published widely on emerging technologies, terrorism, and existential risks, with articles appearing in the Bulletin of the Atomic Scientists, Futures, Erkenntnis, Metaphilosophy, Foresight, Journal of Future Studies, and the Journal of Evolution and Technology. He is the author of several books, including most recently Morality, Foresight, and Human Flourishing: An Introduction to Existential Risks. We talk about the problem of apocalyptic terrorists, the proliferation dual-use technology and the governance problem that arises as a result. This is both a fascinating and potentially terrifying discussion.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher and a variety of other podcasting services (the RSS feed is here).
Show Notes* 0:00 – Introduction * 3:14 – What is existential risk? Why should we care? * 8:34 – The four types of agential risk/omnicidal terrorists * 17:51 – Are there really omnicidal terror agents? * 20:45 – How dual-use technology give apocalyptic terror agents the means to their desired ends * 27:54 – How technological civilisation is uniquely vulernable to omnicidal agents * 32:00 – Why not just stop creating dangerous technologies? * 36:47 – Making the case for mass surveillance * 41:08 – Why mass surveillance must be asymmetrical * 45:02 – Mass surveillance, the problem of false positives and dystopian governance * 56:25 – Making the case for benevolent superintelligent governance * 1:02:51 – Why advocate for something so fantastical? * 1:06:42 – Is an anti-tech solution any more fantastical than a benevolent AI solution? * 1:10:20 – Does it all just come down to values: are you a techno-optimist or a techno-pessimist?
Relevant Links* Phil’s webpage * ‘Superintelligence and the Future of Governance: On Prioritizing the Control Problem at the End of History’ by Phil * Morality, Foresight, and Human Flourishing: An Introduction to Existential Risks by Phil * ‘The Vulnerable World Hypothesis” by Nick Bostrom * Phil’s comparison of his paper with Bostrom’s paper * The Guardian orders the small-pox genome * Slaughterbots * The Future of Violence by Ben Wittes and Gabriela Blum * Future Crimes by Marc Goodman * The Dyn Cyberattack * Autonomous Technology by Langdon Winner * 'Biotechnology and the Lifetime of Technological Civilisations’ by JG Sotos * The God Machine Thought Experiment (Persson and Savulescu)
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In this episode I talk to Erica Neely. Erica is an Associate Professor of Philosophy at Ohio Northern University specializing in philosophy of technology and computer ethics. Her work focuses is on the ethical ramifications of emerging technologies. She has written a number of papers on 3D printing, the ethics of video games, robotics and augmented reality. We chat about the ethics of augmented reality, with a particular focus on property rights and the problems that arise when we blend virtual and physical reality together in augmented reality platforms.
You can download the episode here or listen below. You can also subscribe on Apple Podcasts, Stitcher and a variety of other services (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:00 - What is augmented reality (AR)? * 5:55 - Is augmented reality overhyped? * 10:36 - What are property rights? * 14:22 - Justice and autonomy in the protection of property rights * 16:47 - Are we comfortable with property rights over virtual spaces/objects? * 22:30 - The blending problem: why augmented reality poses a unique problem for the protection of property rights * 27:00 - The different modalities of augmented reality: single-sphere or multi-sphere? * 30:45 - Scenario 1: Single-sphere AR with private property * 34:28 - Scenario 2: Multi-sphere AR with private property * 37:30 - Other ethical problems in scenario 2 * 43:25 - Augmented reality vs imagination * 47:15 - Public property as contested space * 49:38 - Scenario 3: Multi-sphere AR with public property * 54:30 - Scenario 4: Single-sphere AR with public property * 1:00:28 - Must the owner of the single-sphere AR platform be regulated as a public utility/entity? * 1:02:25 - Other important ethical issues that arise from the use of AR
Relevant Links* Erica's Homepage * 'Augmented Reality, Augmented Ethics: Who Has the Right to Augment a Particular Physical Space?' by Erica * 'The Ethics of Choice in Single Player Video Games' by Erica * 'The Risks of Revolution: Ethical Dilemmas in 3D Printing from a US Perspective' by Erica * 'Machines and the Moral Community' by Erica * IKEA Place augmented reality app * L'Oreal's use of augmented reality make-up apps * Holocaust Museum Bans Pokemon Go
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This audio essay is an Easter special. It focuses on David Hume's famous argument about miracles. First written over 250 years, Hume's essay 'Of Miracles' purports to provide an "everlasting check" against all kinds of "superstitious delusion". But is this true? Does Hume give us good reason to reject the testimonial proof provided on behalf of historical miracles? Maybe not, but he certainly provides a valuable framework for thinking critically about this issue.
You can download the audio here or listen below. You can also subscribe on Apple, Stitcher and a variety of other podcatching services (the RSS feed is here).
This audio essay is based on an earlier written essay (available here). If you are interested in further reading about the topic, I recommend the following essays:
- Hume's Argument Against Miracles (Part One)
- Hume's Argument Against Miracles (Part Two)
- Hume, Miracles and the Many Witnesses Objection
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In this episode I talk Stefan Lorenz Sorgner. Stefan teaches philosophy at John Cabot University in Rome. He is director and co-founder of the Beyond Humanism Network, Fellow at the Institute for Ethics and Emerging Technologies (IEET), Research Fellow at the Ewha Institute for the Humanities at Ewha Womans University in Seoul, and Visting Fellow at the Ethics Centre of the Friedrich-Schiller-University in Jena. His main fields of research are Nietzsche, the philosophy of music, bioethics and meta-, post- and transhumanism. We talk about his case for a Nietzschean form of transhumanism.
You can download the episode here or listen below. You can also subscribe to the podcast on iTunes, Stitcher and a variety of other podcasting apps (the RSS feed is here).
Show Notes 0:00 - Introduction * 2:12 - Recent commentary on Stefan's book Ubermensch* * 3:41 - Understanding transhumanism - getting away from the "humanism on steroids" ideal * 10:33 - Transhumanism as an attitude of experimentation and not a destination? * 13:34 - Have we always been transhumanists? * 16:51 - Understanding Nietzsche * 22:30 - The Will to Power in Nietzschean philosophy * 26:41 - How to understand "power" in Nietzschean terms * 30:40 - The importance of perspectivalism and the abandonment of universal truth * 36:40 - Is it possible for a Nietzschean to consistently deny absolute truth? * 39:55 - The idea of the Ubermensch (Overhuman) * 45:48 - Making the case for a Nietzschean form of transhumanism * 51:00 - What about the negative associations of Nietzsche? * 1:02:17 - The problem of moral relativism for transhumanists
Relevant Links Stefan's homepage * The Ubermensch: A Plea for a Nietzschean Transhumanism - Stefan's new book (in German) * Posthumanism and Transhumanism: An Introduction -* edited by Stefan and Robert Ranisch * "Nietzsche, the Overhuman and Tranhumanism" by Stefan (open access) * "Beyond Humanism: Reflections on Trans and Post-humanism" by Stefan (a response to critics of the previous article) * Nietzsche at the Stanford Encyclopedia of Philosophy
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In this episode I talk to Jacob Turner. Jacob is a barrister and author. We chat about his new book, Robot Rules: Regulating Artificial Intelligence (Palgrave Macmillan, 2018), which discusses how to address legal responsibility, rights and ethics for AI.
You can download here or listen below. You can also subscribe to the show on iTunes, Stitcher and a variety of other services (the RSS feed is here).
Show Notes 0:00 - Introduction * 1:33 - Why did Jacob write Robot Rules?* * 2:47 - Do we need special legal rules for AI? * 6:34 - The responsibility 'gap' problem * 11:50 - Private law vs criminal law: why it's important to remember the distinction * 14:08 - Is is easy to plug the responsibility gap in private law? * 23:07 - Do we need to think about the criminal law responsibility gap? * 26:14 - Is it absurd to hold AI criminally responsible? * 30:24 - The problem with holding proximate humans responsible * 36:40 - The positive side of responsibility: lessons from the Monkey selfie case * 41:50 - What is legal personhood and what would it mean to grant it to an AI? * 48:57 - Pragmatic reasons for granting an AI legal personhood * 51:48 - Is this a slippery slope? * 56:00 - Explainability and AI: Why is this important? * 1:02:38 - Is there are right to explanation under EU law? * 1:06:16 - Is explainability something that requires a technical solution not a legal solution? * 1:08:32 - The danger of fetishising explainability
Relevant Links Robot Rules: Regulating Artificial Intelligence* * Website for the book * Jacob on Twitter * Jacob giving a lecture about the book at the University of Law * "Robots, Law and the Retribution Gap" by John Danaher * The Darknet Shopper Case * The Monkey Selfie Case * Algorithmic Entities by Lynn LoPucki (discussing Shawn Bayern's argument) * Matthew Scherer's critique of Bayern's claim that AI's can already acquire legal personhood
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Schopenhauer was a profoundly pessimistic man. He argued that all life was suffering. Was he right or is there room for optimism? This audio essay tries to answer that question. It is based on an earlier written essay. You can listen below or download here.
These audio essays are released as part of the Philosophical Disquisitions podcast. You can subscribe to the podcast on Apple Podcasts, Player FM, Podbay, Podbean, Castbox, Overcast and more. Full details available here.
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In this episode I talk to Seth Baum. Seth is an interdisciplinary researcher working across a wide range of fields in natural and social science, engineering, philosophy, and policy. His primary research focus is global catastrophic risk. He also works in astrobiology. He is the Co-Founder (with Tony Barrett) and Executive Director of the Global Catastrophic Risk Institute. He is also a Research Affiliate of the University of Cambridge Centre for the Study of Existential Risk. We talk about the importance of studying the long-term future of human civilisation, and map out four possible trajectories for the long-term future.
You can download the episode here or listen below. You can also subscribe on a variety of different platforms, including iTunes, Stitcher, Overcast, Podbay, Player FM and more. The RSS feed is available here.
Show Notes* 0:00 - Introduction * 1:39 - Why did Seth write about the long-term future of human civilisation? * 5:15 - Why should we care about the long-term future? What is the long-term future? * 13:12 - How can we scientifically and ethically study the long-term future? * 16:04 - Is it all too speculative? * 20:48 - Four possible futures, briefly sketched: (i) status quo; (ii) catastrophe; (iii) technological transformation; and (iv) astronomical * 23:08 - The Status Quo Trajectory - Keeping things as they are * 28:45 - Should we want to maintain the status quo? * 33:50 - The Catastrophe Trajectory - Awaiting the likely collapse of civilisation * 38:58 - How could we restore civilisation post-collapse? Should we be working on this now? * 44:00 - Are we under-investing in research into post-collapse restoration? * 49:00 - The Technological Transformation Trajectory - Radical change through technology * 52:35 - How desirable is radical technological change? * 56:00 - The Astronomical Trajectory - Colonising the solar system and beyond * 58:40 - Is the colonisation of space the best hope for humankind? * 1:07:22 - How should the study of the long-term future proceed from here?
Relevant Links Seth's homepage * The Global Catastrophic Risk Institute * "Long-Term Trajectories for Human Civilisation" by Baum et al * "The Perils of Short-Termism: Civilisation's Greatest Threat" by Fisher, BBC News * The Knowledge by Lewis Dartnell * "Space Colonization and the Meaning of Life" by Baum, Nautilus* * "Astronomical Waste: The Opportunity Cost of Delayed Technological Development" by Nick Bostrom * "Superintelligence as a Cause or Cure for Risks of Astronomical Suffering" by Kaj Sotala and Lucas Gloor * "Space Colonization and Suffering Risks" by Phil Torres * "Thomas Hobbes in Space: The Problem of Intergalactic War" by John Danaher
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This is an experiment. For a number of years, people have been asking me to provide audio versions of the essays that I post on the blog. I've been reluctant to do this up until now, but I have recently become a fan of the audio format and I appreciate its conveniences. Also, I watched an interview with Michael Lewis (the best-selling non-fiction author in the world) just this week where he suggested that audio essays might be the future of the essay format. So, in an effort to jump ahead of the curve (or at least jump onto the curve before it pulls away from me), I'm going to post a few audio essays over the coming months.
They will all be based on stuff I've previously published on the blog, with a few minor edits and updates. I'll send them out on the regular podcast feed (which you can subscribe to in various formats here). I'm learning as I go. The quality and style will probably evolve over time, and I'm quite keen on getting feedback from listeners too. Do you like this kind of thing or would you prefer I didn't do it?
This first audio essay is based on something I previously wrote on the moral problem of accelerating change. You can find the original essay here. You can listen below or download at this link.
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In this episode I talk to Jeff Sebo. Jeff is a Clinical Assistant Professor of Environmental Studies, Affiliated Professor of Bioethics, Medical Ethics, and Philosophy, and Director of the Animal Studies M.A. Program at New York University. Jeff’s research focuses on bioethics, animal ethics, and environmental ethics. He has two co-authored books Chimpanzee Rights and Food, Animals, and the Environment. We talk about something Jeff calls the 'moral problem of other minds', which is roughly the problem of what we should to if we aren't sure whether another being is sentient or not.
You can download the episode here or listen below. You can also subscribe to the show on iTunes and Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:38 - What inspired Jeff to think about the moral problem of other minds? * 7:55 - The importance of sentience and our uncertainty about it * 12:32 - The three possible responses to the moral problem of other minds: (i) the incautionary principle; (ii) the precautionary principle and (iii) the expected value principle * 15:26 - Understanding the Incautionary Principle * 20:09 - Problems with the Incautionary Principle * 23:14 - Understanding the Precautionary Principle: More plausible than the incautionary principle? * 29:20 - Is morality a zero-sum game? Is there a limit to how much we can care about other beings? * 35:02 - The problem of demandingness in moral theory * 37:06 - Other problems with the precautionary principle * 41:41 - The Utilitarian Version of the Expected Value Principle * 47:36 - The problem of anthropocentrism in moral reasoning * 53:22 - The Kantian Version of the Expected Value Principle * 59:08 - Problems with the Kantian principle * 1:03:54 - How does the moral problem of other minds transfer over to other cases, e.g. abortion and uncertainty about the moral status of the foetus?
Relevant Links Jeff's Homepage * 'The Moral Problem of Other Minds' by Jeff * Chimpanzee Ethics by Jeff and ors * Food, Animals and the Environment* by Jeff and Christopher Schlottman * 'Consider the Lobster' by David Foster Wallace * 'Ethical Behaviourism in the Age of the Robot' by John Danaher * Episode 48 with David Gunkel on Robot Rights
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In this episode I talk to Angèle Christin. Angèle is an assistant professor in the Department of Communication at Stanford University, where she is also affiliated with the Sociology Department and Program in Science, Technology, and Society. Her research focuses on how algorithms and analytics transform professional values, expertise, and work practices. She is currently working on a book on the use of audience metrics in web journalism and a project on the use of risk assessment algorithms in criminal justice. We talk about both.
You can download the episode here or listen below. You can also subscribe to the show on iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:30 - What's missing from the current debate about algorithmic governance? What does Angèle's ethnographic perspective add? * 5:10 - How does ethnography work? What does an ethnographer do? * 8:30 - What are the limitations of ethnographic studies? * 12:33 - Why did Angèle focus on the use of algorithms in criminal justice and web journalism? * 23:06 - What were Angèle's two key research findings? Decoupling and Buffering * 24:40 - What is 'decoupling' and how does it happen? * 30:00 - Different attitudes to algorithmic tools in the US and France (French journalists, perhaps surprisingly, more obsessed with real time analytics than their American counterparts) * 39:20 - What explains the ambivalent attitude to metrics in different professions? * 44:42 - What is 'buffering' and how does it arise? * 54:30 - How people who worry about algorithms might misunderstand the practical realities of criminal justice * 57:47 - Does the resistance/acceptance of an algorithmic tool depend on the nature of the tool and the nature of the workplace? What might the relevant variables be?
Relevant Links* Angèle's Homepage * "Algorithms in Practice: Comparing Web Journalism and Criminal Justice" by Angèle * "Counting Clicks: Quantification and Variation in Web Journalism in the United States and France" by Angèle * "Courts and Predictive Algorithms" by Christin, Rosenblat and Boyd * "The Mistrials of Algorithmic Sentencing" by Angèle * Episode 41 with Reuben Binns (covering the debate about the Compas algorithm and bias) * Episode 19 with Andrew Ferguson on big data and policing
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In this episode I talk to Kate Devlin. Kate is a Senior Lecturer in the Department of Digital Humanities at King's College London. Kate's research is in the fields of Human Computer Interaction (HCI) and Artificial Intelligence (AI), investigating how people interact with and react to technology in order to understand how emerging and future technologies will affect us and the society in which we live. Kate has become a driving force in the field of intimacy and technology, running the UK's first sex tech hackathon in 2016. She has also become the face of sex robots – quite literally in the case of one mis-captioned tabloid photograph. We talk about her recent, excellent book Turned On: Science, Sex and Robots, which covers the past, present and future of sex technology.
You download the episode here or listen below. You can also subscribe on iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:08 - Why did Kate talk about sex robots in the House of Lords? * 3:01 - How did Kate become the face of sex robots? * 5:34 - Are sex robots really a thing? Should academics be researching them? * 11:10 - The important link between archaeology and sex technology * 15:00 - The myth of hysteria and the origin of the vibrator * 17:36 - What was the most interesting thing Kate learned while researching this book? (Ans: owners of sex dolls are not creepy isolationists) * 23:03 - Is there are moral panic about sex robots? And are we talking about robots or dolls? * 30:41 - What are the arguments made by defenders of the 'moral panic' view? * 38:05 - What could be the social benefits of sex robots? Do men and women want different things from sex tech? * 47:57 - Why is Kate so interested in 'non-anthropomorphic' sex robots? * 55:15 - Is the media fascination with this topic destructive or helpful? * 57:32 - What question does Kate get asked most often and what does she say in response?
Relevant Links Kate's Webpage * Kate's Academic Homepage * Turned On: Science, Sex and Robots by Kate Devlin * Kate and I in conversation at the Virtual Futures Salon in London * 'A Failure of Academic Quality Control: The Technology of the Orgasm' by Hallie Lieberman and Eric Schatzberg (on the myth that vibrators were used to treat hysteria) * Laodamia - Owner of the world's first sex doll? * 'In Defence of Sex Machines: Why trying to ban sex robots is wrong?' by Kate * 'Sex robot molested at electronics festival' at Huffington Post * 'First tester made love to sex robot so furiously it actually broke' at Metro.co.uk * The 2nd London Sex Tech Hackathon * Robot Sex: Social and Ethical Implications* edited by Danaher and McArthur
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In this episode I talk to Ole Martin Moen. Ole Martin is a Research Fellow in Philosophy at the University of Oslo. He works on how to think straight about thorny issues in applied ethics. He is the Principal Investigator of “What should not be bought and sold?”, a $1 million research project funded by the Research Council of Norway. In the past, he has written articles about the ethics of prostitution, the desirability of cryonics, the problem of wild animal suffering and the case for philosophical hedonism. Along with his collaborator, Aksel Braanen Sterri, he runs a podcast, Moralistene (in Norwegian), and he regularly discusses moral issues behind the news on Norwegian national radio. We talk about a potentially controversial topic: the anti-tech philosophy of the Unabomber, Ted Kaczysnki, and what's wrong with it.
You can download the episode here or listen below. You can also subscribe via iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:05 - Should we even be talking about Ted Kaczynski's ethics? Does it not lend legitimacy to his views? * 6:32 - Are we unnecessarily anti-rational when it comes to discussing dangerous ideas? * 8:32 - The Evolutionary Mismatch Argument * 12:43 - The Surrogate Activities Argument * 20:20 - The Helplessness/Complexity Argument * 23:08 - The Unstoppability Argument * 26:45 - The Domesticated Animals Argument * 30:45 - Why does Ole Martin overlook Kaczynski's criticisms of 'leftists' in his analysis? * 34:03 - What's original in Kaczynski's arguments? * 36:31 - Are philosophers who write about Kaczynski engaging in a motte and bailey fallacy? * 38:36 - Ole Martin's main critique of Kaczynski: the evaluative double standard * 42:20 - How this double standard works in practice * 47:27 - Why not just drop out of industrial society instead of trying to overthrow it? * 55:04 - Is Kaczynski a revolutionary nihilist? * 58:59 - Similarities and differences between Kaczynski's argument and the work of Nick Bostrom, Ingmar Persson and Julian Savulescu * 1:04:21 - Where should we go from here? Should there be more papers on this topic?
Relevant Links Ole Martin's Homepage * 'The Unabomber's Ethics' by Ole Martin Moen * "Bright New World" and "Smarter Babies" by Ole Martin Moen * "The Case for Cryonics" by Ole Martin Moen * Ted Kaczynski on Wikipedia (includes links to relevant writings) * "The Unabomber's Penpal" - article about the philosopher David Skrbina who has corresponded with Kaczynski for some time * "The Unabomber on Robots" - by Jai Galliott (article appearing in Robot Ethics 2.0 edited by Lin et al) * Unfit for the Future* by Ingmar Persson and Julian Savulescu * Nick Bostrom's Homepage (check out his recent paper 'The Vulnerable World Hypothesis")
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In this episode I talk to Michele Loi. Michele is a political philosopher turned bioethicist turned digital ethicist. He is currently (2017-2020) working on two interdisciplinary projects, one of which is about the ethical implications of big data at the University of Zurich. In the past, he developed an ethical framework of governance for the Swiss MIDATA cooperative (2016). He is interested in bringing insights from ethics and political philosophy to bear on big data, proposing more ethical forms of institutional organization, firm behavior, and legal-political arrangements concerning data. We talk about how you can use Rawls's theory of justice to evaluate the role of dominant tech platforms (particularly Facebook) in modern life.
You download the show here or listen below. You can also subscribe on iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:29 - Why use Rawls to assess data platforms? * 2:58 - Does the analogy between data and oil hold up to scrutiny? * 7:04 - The First Key Idea: Rawls's Basic Social Structures * 11:20 - The Second Key Idea: Dominant Tech Platforms as Basic Social Structures * 15:02 - Is Facebook a Dominant Tech Platform? * 19:58 - How Zuckerberg's recent memo highlights Facebook's status as a basic social structure * 23:10 - A brief primer on Rawls's two principles of justice * 29:18 - Dominant tech platforms and respect for the basic liberties (particularly free speech) * 36:48 - Facebook: Media Company or Nudging Platform? Does it matter from the perspective of justice? * 41:43 - Why Facebook might have a duty to ensure that we don't get trapped in a filter bubble * 44:32 - Is it fair to impose such a duty on Facebook as a private enterprise? * 51:18 - Would it be practically difficult for Facebook to fulfil this duty? * 53:02 - Is data-mining and monetisation exploitative? * 56:14 - Is it possible to explore other economic models for the data economy? * 59:44 - Can regulatory frameworks (e.g. the GDPR) incentivise alternative business models? * 1:01:50 - Is there hope for the future?
Relevant Links* Michele on Twitter * Michele on Research Gate * 'If data is the new oil, when is the extraction of value from data unjust?' by Loi and Dehaye * 'Technological Unemployment and Human Disenhancement' by Michele Loi * 'The Digital Phenotype: A Philosophical and Ethical Exploration' by Michele Loi * 'A Blueprint for content governance and enforcement' by Mark Zuckerberg * 'Should libertarians hate the internet? A Nozickian Argument Against Social Networks' by John Danaher * John Rawls's Two Principles of Justice, explained
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In this episode I talk to Francesca Minerva. Francesca is a postdoctoral fellow at the University of Ghent. Her research focuses on applied philosophy, specifically lookism, conscientious objection, abortion, academic freedom, and cryonics. She has published many articles on these topics in some of the leading academic journals in ethics and philosophy, including the Journal of Medical Ethics, Bioethics, Cambridge Quarterly Review of Ethicsand the Hastings Centre Report. We talk about life, death and the wisdom and ethics of cryonics.
You can download the episode here or listen below. You can also subscribe on iTunes or Stitcher (the RSS feed is here).
Show Notes:* 0:00 - Introduction * 1:34 - What is cryonics anyway? * 6:54 - The tricky logistics of cryonics: you need to die in the right way * 10:30 - Is cryonics too weird/absurd to take seriously? Analogies with IVF and frozen embryos * 16:04 - The opportunity cost of cryonics * 18:18 - Is death bad? Why? * 22:51 - Is life worth living at all? Is it better never to have been born? * 24:44 - What happens when live is no longer worth living? The attraction of cryothanasia * 30:28 - Should we want to live forever? Existential tiredness and existential boredom * 37:20 - Is immortality irrelevant to the debate about cryonics? * 41:42 - Even if cryonics is good for me might it be the unethical choice? * 45:00 (ish) - Egalitarianism and the distribution of life years * 49:39 - Would future generations want to revive us? * 52:34 - Would we feel out of place in the distant future?
Relevant Links Francesca's webpage * The Ethics of Cryonics: Is it immoral to be immortal? by Francesca * 'Cryopreservation of Embryos and Fetuses as a Future Option for Family Planning Purposes' by Francesca and Anders Sandberg * 'Euthanasia and Cryothanasia' by Francesca and Anders Sandberg * 'The Badness of Death and the Meaning of Life' (Series) - pretty much everything I've ever written about the philosophy of life and death * Alcor Life Extension Foundation * Cryonics Institute * To be a Machine* by Mark O'Connell
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In this episode I talk to Matthijs Maas. Matthijs is a doctoral researcher at the University of Copenhagen's 'AI and Legal Disruption' research unit, and a research affiliate with the Governance of AI Program at Oxford University's Future of Humanity Institute. His research focuses on safe and beneficial global governance strategies for emerging, transformative AI systems. This involves, in part, a study of the requirements and pitfalls of international regimes for technology arms control, non-proliferation and the conditions under which these are legitimate and effective. We talk about the phenomenon of 'globally disruptive AI' and the effect it will have on the international legal order.
You can download the episode here or listen below. You can also subscribe via iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 2:11 - International Law 101 * 6:38 - How technology has repeatedly shaped the content of international law * 10:43 - The phenomenon of 'globally disruptive artificial intelligence' (GDAI) * 15:20 - GDAI and the development of international law * 18:05 - Will we need new laws? * 19:50 - Will GDAI result in lots of legal uncertainty? * 21:57 - Will the law be under/over-inclusive of GDAI? * 25:21 - Will GDAI render international law obsolete? * 31:00 - Could we have a tech-neutral international law? * 34:10 - Could we automate the monitoring and enforcement of international law? * 44:35 - Could we replace international legal institutions with technological systems of management? * 47:35 - Could GDAI lead to the end of the international legal order? * 57:23 - Could GDAI result in more isolationism and less multi-lateralism * 1:00:40 - So what will the future be?
Relevant Links* Follow Matthijs on Twitter * Artificial Intelligence and Legal Disruption research group (University of Copenhagen) * Governance of AI Program (University of Oxford) * Dafoe, Allan. “AI Governance: A Research Agenda.” Oxford: Governance of AI Program, Future of Humanity Institute, 2018. * On history of technology and international law: Picker, Colin B. “A View from 40,000 Feet: International Law and the Invisible Hand of Technology.” Cardozo Law Review 23 (2001): 151–219. * Brownsword, Roger. “In the Year 2061: From Law to Technological Management.” Law, Innovation and Technology 7, no. 1 (January 2, 2015): 1–51. * Boutin, Berenice. “Technologies for International Law & International Law for Technologies.” Groningen Journal of International Law (blog), October 22, 2018. * Moses, Lyria Bennett. “Recurring Dilemmas: The Law’s Race to Keep Up With Technological Change.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, April 11, 2007. * On establishing legal 'artificially intelligent entities', etc: Burri, Thomas. “International Law and Artificial Intelligence.” SSRN Electronic Journal, 2017.
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In this episode I talk to David Gunkel. David is a repeat guest, having first appeared on the show in Episode 10. David a Professor of Communication Studies at Northern Illinois University. He is a leading scholar in the philosophy of technology, having written extensively about cyborgification, robot rights and responsibilities, remix cultures, new political structures in the information age and much much more. He is the author of several books, including Hacking Cyberspace, The Machine Question, Of Remixology, Gaming the System and, most recently, Robot Rights. We have a long debate/conversation about whether or not robots should/could have rights.
You can download the episode here or listen below. You can also subscribe to the show on iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00- Introduction * 1:52 - Isn't the idea of robot rights ridiculous? * 3:37 - What is a robot anyway? Is the concept too nebulous/diverse? * 7:43 - Has science fiction undermined our ability to think about robots clearly? * 11:01 - What would it mean to grant a robot rights? (A precis of Hohfeld's theory of rights) * 18:32 - The four positions/modalities one could take on the idea of robot rights * 21:32 - The First Modality: Robots Can't Have Rights therefore Shouldn't * 23:37 - The EPSRC guidelines on robotics as an example of this modality * 26:04 - Criticisms of the EPSRC approach * 28:27 - Other problems with the first modality * 31:32 - Europe vs Japan: why the Japanese might be more open to robot 'others' * 34:00 - The Second Modality: Robots Can Have Rights therefore Should (some day) * 39:53 - A debate between myself and David about the second modality (why I'm in favour it and he's against it) * 47:17 - The Third Modality: Robots Can Have Rights but Shouldn't (Bryson's view) * 53:48 - Can we dehumanise/depersonalise robots? * 58:10 - The Robot-Slave Metaphor and its Discontents * 1:04:30 - The Fourth Modality: Robots Cannot Have Rights but Should (Darling's view) * 1:07:53 - Criticisms of the fourth modality * 1:12:05 - The 'Thinking Otherwise' Approach (David's preferred approach) * 1:16:23 - When can robots take on a face? * 1:19:44 - Is there any possibility of reconciling my view with David's? * 1:24:42 - So did David waste his time writing this book?
Relevant Links David's Homepage * Robot Rights* from MIT Press, 2018 (and on Amazon) * Episode 10 - Gunkel on Robots and Cyborgs * 'The other question: can and should robots have rights?' by David Gunkel * 'Facing Animals: A Relational Other-Oriented Approach to Moral Standing' by Gunkel and Coeckelbergh * The Robot Rights Debate (Index) - everything I've written or said on the topic of robot rights * EPSRC Principles of Robotics * Episode 24 - Joanna Bryson on Why Robots Should be Slaves * 'Patiency is not a virtue: the design of intelligent systems and systems of ethics' by Joanna Bryson * Robo Sapiens Japanicus - by Jennifer Robertson
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In this episode I talk to Virginia Eubanks. Virginia is an Associate Professor of Political Science at the University at Albany, SUNY. She is the author of several books, including Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor and Digital Dead End: Fighting for Social Justice in the Information Age. Her writing about technology and social justice has appeared in The American Prospect, The Nation, Harper’s and Wired. She has worked for two decades in community technology and economic justice movements. We talk about the history of poverty management in the US and how it is now being infiltrated and affected by tools for algorithmic governance.
You can download the episode here or listen below. You can also subscribe to the show on iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:39 - The future is unevenly distributed but not in the way you might think * 7:05 - Virginia's personal encounter with the tools for automating inequality * 12:33 - Automated helplessness? * 14:11 - The history of poverty management: denial and moralisation * 22:40 - Technology doesn't disrupt our ideology of poverty; it amplifies it * 24:16 - The problem of poverty myths: it's not just something that happens to other people * 28:23 - The Indiana Case Study: Automating the system for claiming benefits * 33:15 - The problem of automated defaults in the Indiana Case * 37:32 - What happened in the end? * 41:38 - The L.A. Case Study: A "match.com" for the homeless * 45:40 - The Allegheny County Case Study: Managing At-Risk Children * 52:46 - Doing the right things but still getting it wrong? * 58:44 - The need to design an automated system that addresses institutional bias * 1:07:45 - The problem of technological solutions in search of a problem * 1:10:46 - The key features of the digital poorhouse
Relevant Links Virginia's Homepage * Virginia on Twitter * Automating Inequality * 'A Child Abuse Prediction Model Fails Poor Families' by Virginia in Wired* * The Allegheny County Family Screening Tool (official webpage - includes a critical response to Virginia's Wired article) * 'Can an Algorithm Tell when Kids Are in Danger?' by Dan Hurley (generally positive story about the family screening tool in the New York Times). * 'A Response to Allegheny County DHS' by Virginia (a response to Allegheny County's defence of the family screening tool) * Episode 41 with Reuben Binns on Fairness in Algorithmic Decision-Making * Episode 19 with Andrew Ferguson about Predictive Policing
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In this episode I talk to Shannon Vallor. Shannon is the Regis and Diane McKenna Professor in the Department of Philosophy at Santa Clara University, where her research addresses the ethical implications of emerging science and technology, especially AI, robotics and new media. Professor Vallor received the 2015 World Technology Award in Ethics from the World Technology Network. She has served as President of the Society for Philosophy and Technology, sits on the Board of Directors of the Foundation for Responsible Robotics, and is a member of the IEEE Standards Association's Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems. We talk about the problem of techno-social opacity and the value of virtue ethics in an era of rapid technological change.
You can download the episode here or listen below. You can also subscribe to the podcast on iTunes or Stitcher (the RSS feed is here).
Show Notes 0:00 - Introduction * 1:39 - How students encouraged Shannon to write Technology and the Virtues* * 6:30 - The problem of acute techno-moral opacity * 12:34 - Is this just the problem of morality in a time of accelerating change? * 17:16 - Why can't we use abstract moral principles to guide us in a time of rapid technological change? What's wrong with utilitarianism or Kantianism? * 23:40 - Making the case for technologically-sensitive virtue ethics * 27:27 - The analogy with education: teaching critical thinking skills vs providing students with information * 31:19 - Aren't most virtue ethical traditions too antiquated? Aren't they rooted in outdated historical contexts? * 37:54 - Doesn't virtue ethics assume a relatively fixed human nature? What if human nature is one of the things that is changed by technology? * 42:34 - Case study on Social Media: Defending Mark Zuckerberg * 46:54 - The Dark Side of Social Media * 52:48 - Are we trapped in an immoral equilibrium? How can we escape? * 57:17 - What would the virtuous person do right now? Would he/she delete Facebook? * 1:00:23 - Can we use technological to solve problems created by technology? Will this help to cultivate the virtues? * 1:05:00 - The virtue of self-regard and the problem of narcissism in a digital age
Relevant Links Shannon's Homepage * Shannon's profile at Santa Clara University * Shannon's Twitter profile * Technology and the Virtues* (Now in Paperback!) - by Shannon * 'Social Networking Technology and the Virtues' by Shannon * 'Moral Deskilling and Upskilling in a New Machine Age' by Shannon * 'The Moral Problem of Accelerating Change' by John Danaher
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In this episode I chat to Diana Fleischman. Diana is a senior lecturer in evolutionary psychology at the University of Portsmouth. Her research focuses on hormonal influences on behavior, human sexuality, disgust and, recently, the interface of evolutionary psychology and behaviorism. She is a utilitarian, a promoter of effective altruism, and a bivalvegan. We have a long and detailed chat about the evolved psychology of sex and how it may affect the social acceptance and use of sex robots. Along the way we talk about Mills and Boons novels, the connection between sexual stimulation and the brain, and other, no doubt controversial, topics.
You can download the episode here or listen below. You can also subscribe on iTunes or Stitcher (the RSS feed is here).
Show Notes* 0:00 - Introduction * 1:42 - Evolutionary Psychology and the Investment Theory of Sex * 5:54 - What's the evidence for the investment theory in humans? * 8:40 - Does the evidence for the theory hold up? * 11:45 - Studies on the willingness to engage in casual sex: do men and women really differ? * 18:33 - The ecological validity of these studies * 20:20 - Evolutionary psychology and the replication crisis * 23:29 - Are there better alternative explanations for sex differences? * 26:25 - Ethical criticisms of evolutionary psychology * 28:14 - Sex robots and evolutionary psychology * 29:33 - Argument 1: The rising costs of courtship will drive men into the arms of sexbots * 34:12 - Not all men... * 39:08 - Couldn't something similar be true for women? * 46:00 - Aren't the costs of courtship much higher for women? * 48:27 - Argument 2: Sex robots could be used as treatment for dangerous men * 51:50 - Would this stigmatise other sexbot users? * 53:31 - Would this embolden rather than satiate? * 55:53 - Could the logic of this argument be flipped, e.g. the Futurama argument? * 58:05 - Isn't this an ethically sub-optimal solution to the problem? * 1:00:42 - Argument 3: This will also impact on women's sexual behaviour * 1:07:01 - Do ethical objectors to sex robots underestimate the constraints of our evolved psychology?
Relevant Links Diana's personal webpage * Diana on Twitter * Diana's academic homepage * 'Uncanny Vulvas' in Jacobite Magazine - this is the basis for much of our discussion in the podcast * 'Disgust Trumps Lust: Women’s Disgust and Attraction Towards Men Is Unaffected by Sexual Arousal' by Zsok, Fleischman, Borg and Morrison * Beyond Human Nature* by Jesse Prinz * 'Which people would agree to have sex with a stranger?' by David Schmitt * 'Sex Work, Technological Unemployment and the Basic Income Guarantee' by John Danaher
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