Artificial Intelligence comes with a litany of ethical risks and dilemmas. Some are universal, but some are unique to particular countries, like South Africa.
When people think about artificial intelligence (AI), they may have visions of the future. But AI is already here. At its base, it is the recreation of aspects of human intelligence in computerised form. Like human intelligence, it has wide application.
Voice-operated personal assistants like Siri, self-driving cars, and text and image generators all use AI. It also curates our social media feeds. It helps companies to detect fraud and hire employees. It’s used to manage livestock, enhance crop yields and aid medical diagnoses.
Alongside its growing power and its potential, AI raises moral and ethical questions. The technology has already been at the centre of multiple scandals: the infringement of laws and rights, as well as racial and gender discrimination. In short, it comes with a litany of ethical risks and dilemmas.
But what exactly are these risks? And how do they differ among countries? To find out, I undertook a thematic review of literature from wealthier countries to identify six high-level, universal ethical risk themes. I then interviewed experts involved in or associated with the AI industry in South Africa and assessed how their perceptions of AI risk differed from or resonated with those themes.
The findings reflect marked similarities in AI risks between the global north and South Africa as an example of a global south nation. But there were some important differences. These reflect South Africa’s unequal society and the fact that it is on the periphery of AI development, utilisation and regulation.
Other developing countries that share similar features – a vast digital divide, high inequality and unemployment and low-quality education – likely have a similar risk profile to South Africa.
Knowing what ethical risks may play out at a country level is important because it can help policymakers and organisations to adjust their risk management policies and practices accordingly.
Universal themes
The six universal ethical risk themes I drew from reviewing global north literature were:
Accountability: It is unclear who is accountable for the outputs of AI models and systems.
Bias: Shortcomings of algorithms, data or both entrench bias.
Transparency: AI systems operate as a “black box”. Developers and end users have a limited ability to understand or verify the output.
Autonomy: Humans lose the power to make their own decisions.
Socio-economic risks: AI may result in job losses and worsen inequality.
Maleficence: It could ...