Ethical Machines

My guest, Fabio Tollen, a postdoctoral researcher on the BRAID programme at the University of Edinburgh, argues that answering that question is more difficult than it first appears. Traditional theories of moral responsibility suggest that people should only be blamed for actions they understand and control. But AI systems seem to challenge both requirements.
We discuss responsibility gaps, the problem of many hands, whether AI developers are more like parents or engineers, and Fabio's distinction between moral responsibility and moral answerability. Along the way, we explore whether answerability can help us make sense of AI harms when blame is difficult to assign.

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Aligning an AI traditionally looks like a matter of giving it rules to obey. But my guest, Gillian Hadfield, Professor of AI Alignment and Governance at Johns Hopkins University, thinks that’s the wrong approach. She argues that we need to think about what it means to have a normative capacity - an ability to categorize behavior as (un)acceptable in a given context by observing that context - and then think about what it would mean to give that capacity to an AI. Lots to dig into here, including especially our disagreement about whether she’s focused on an ethical normative capacity vs. a prudential normative capacity.

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Technologist’s are racing to create AGI, artificial general intelligence. They also say we must align the AGI’s moral values with our own. But Professors Ariela Tubert and Justin Tiehen argue that’s impossible. Once you create an AGI, they say, you also give them the intellectual capacity needed for freedom, including the freedom to reject your given values. Originally aired in season 2.

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The Thomson Reuters Foundation recently conducted a global survey and found that most companies are lagging in their attempts to govern AI. For me the most surprising stat is that 85% of companies don’t have any training on AI risks for their employees. I think that’s just insane. Today my guests are Antonio Zappulla, CEO of the Thomson Reuters Foundation, and Katie Fowler, Director of Responsible Business. We talk about how they conducted their research, their results, and what incentives there are for businesses to do better.
To get in touch with Thomson Reuters Foundation to participate in their next survey, please go to: https://www.trust.org/newsletter/

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My guest, Carissa Véliz, is author of the new book “Prophecy: Prediction, Power, and the Fight for the Future, from Ancient Oracles to AI.” Her thesis is that when leaders in AI say things like “AI adoption is inevitable,” they’re not making a prediction, but rather giving us a command and attempting to legitimize their power. Is she right? Have a listen!

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