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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: How I Formed My Own Views About AI Safety, published by Neel Nanda on February 27, 2022 on The AI Alignment Forum. Disclaimer: I work as a researcher at Anthropic, but this post entirely represents my own views, rather than the views of my own employer Introduction I’ve spent the past two years getting into the field of AI Safety. One important message I heard as I was entering the field was that I needed to “form an inside view about AI Safety”, that I needed to form my own beliefs and think for myself rather than just working on stuff because people smarter than me cared about it. And this was incredibly stressful! I think the way I interpreted this was pretty unhealthy, caused me a lot of paralysing uncertainty and anxiety, and almost caused me to give up on getting into the field. But I feel like I’ve now reached a point I’m comfortable with, and where I somewhat think I have my own inside views on things and understand how to form them. In this post, I try to explain the traps I fell into and why, what my journey actually looked like, and my advice for how to think about inside views, now I’ve seen what not to do. This is a complex topic and I think there are a lot of valid perspectives, but hopefully my lens is novel and useful for some people trying to form their own views on confusing topics (AI Safety or otherwise)! (Note: I don’t discuss why I do now think AI Safety is important and worth working on - that’s a topic for a future post!) The Message of Inside Views First, context to be clear about what I mean by inside views. As I understand it, this is a pretty fuzzily defined concept, but roughly means “having a clear model and argument in my head, starting from some basic and reasonable beliefs about the world, that get to me to a conclusion like ‘working on AI Safety is important’ without needing to rely on deferring to people”. This feels highly related to the concept of gears-level models. This is in comparison to outside views, or deferring to people, where the main reason I believe something is because smart people I respect believe it. In my opinion, there’s a general vibe in the rationality community that inside views are good and outside views are bad (see Greg Lewis’ In Defence of Epistemic Modesty for a good argument for the importance of outside views and deferring!). Note that this is not the Tetlockian sense of the words, used in forecasting, where outside view means ‘look up a base rate’ and inside view means ‘use my human intuition, which is terribly calibrated’, where the standard wisdom is outside view > inside view. Good examples of this kind of reasoning: Buck Shlegeris’ My Personal Cruxes for Working on AI Safety, Richard Ngo’s AGI Safety from First Principles, Joseph Carlsmith’s report on Existential Risk from Power-Seeking AI. Note that, while these are all about the question of ‘is AI Safety a problem at all’, the notion of an inside view also applies well to questions like ‘de-confusion research/reinforcement learning from human feedback/interpretability is the best way to reduce existential risk from AI’, arguing for specific research agendas and directions. How I Interpreted the Message of Inside Views I’m generally a pretty anxious person and bad at dealing with uncertainty, and sadly, this message resulted in a pretty unhealthy dynamic in my head. It felt like I had to figure out for myself the conclusive truth of ‘is AI Safety a real problem worth working on’ and which research directions were and were not useful, so I could then work on the optimal one. And that it was my responsibility to do this all myself, that it was bad and low-status to work on something because smart people endorsed it. This was hard and overwhelming because there are a lot of agendas, and a lot of smart people with different and somewhat contradictory ...