Ethical Machines

Tech companies are racing to build and sell agentic. The vision is one in which countless AI agents are acting on our behalf: searching the web, making transactions, interacting with other AI agents. But my guest Avijit Ghosh, Applied Policy Researcher at Hugging Face, explains why we’re not even close to having the appropriate safeguards in place. What are the massive gaps and what would it take to close them? That’s the topic of our discussion.

AI Agent Framework: SmolAgents: https://huggingface.co/blog/smolagents

AI Agents Course: https://huggingface.co/learn/agents-course/en/unit0/introduction

Position paper: https://huggingface.co/papers/2502.02649

Op Ed! : https://www.technologyreview.com/2025/03/24/1113647/why-handing-over-total-control-to-ai-agents-would-be-a-huge-mistake/

We’re told that algorithms on social media are manipulating us. But is that true? What is manipulation? Can an AI really do it? And is it necessarily a bad thing? These questions and more with philosopher Michael Klenk. Originally aired in season one.

We often defer to the judgment of experts. I usually defer to my doctor’s judgment when he diagnoses me, I defer to quantum physicists when they talk to me about string theory, etc. I don’t say “well, that’s interesting, I’ll take it under advisement” and then form my own beliefs. Any beliefs I have on those fronts I replace with their beliefs. But what if an AI “knows” more than us? It is an authority in the field in which we’re questioning it. Should we defer to the AI? Should we replace our beliefs with whatever it believes? On the one hand, hard pass! On the other, it does know better than us. What to do? That’s the issue that drives this conversation with my guest, Benjamin Lange, Research Assistant Professor in the Ethics of AI and ML at the Ludwig Maximilians University of Munich.

Are claims about AI destroying humanity just more AI hype we should ignore? My guests today, Risto Uuk and Torben Swoboda assess three popular arguments for why we should dismiss them and focus solely on the AI risks that are here today. But they find each argument flawed, arguing that, unless some fourth powerful argument comes along, we should devote resources to identifying and avoiding potential existential risks to humanity posed by AI.

I have to admit, AI can do some amazing things. More specifically, it looks like it can perform some impressive intellectual feats. But is it actually intelligent? Does it understand? Or is it just really good at statistics? This and more in my conversation with Lisa Titus, former professor of philosophy at the University of Denver and now AI Policy Manager at Meta. Originally aired in season one.

By the end of this crash course, you’ll understand a lot about the AI ethics landscape. Not only will it give you your bearings, but it will also enable you to identify what parts of the landscape you find interesting so you can do a deeper dive.

People want AI developed ethically, but is there actually a business case for it? The answer better be yes since, after all, it’s businesses that are developing AI in the first place. Today I talk with Dennis Hirsch, Professor of Law and Computer Science at Ohio State University, who is conducting empirical research on this topic. He argues that AI ethics - or as he prefers to call it, Responsible AI - delivers a lot of bottom line business value. In fact, his research revealed something about its value that he didn’t even expect to see. We’re in the early days of businesses taking AI ethics seriously, but if he’s right, we’ll see a lot more of it. Fingers crossed.

Automation is great, right? It speeds up what needs to get done. But is that always a good thing? What about in the process of scientific discovery? Yes, AI can automate a lot of science by running thousands of virtual experiments and generating results - but is something lost in the process? My guest, Ramón Alvarado a professor of philosophy and a member of the Philosophy and Data Science Initiative at the University of Oregon, thinks something crucial is missing: serendipity. Many significant scientific discoveries occurred by happenstance. Penicillin, for instance, was discovered by Alexander Fleming who accidentally left a petri dish on a bench before going off for vacation. Exactly what is the scientific value of serendipity, how important is it, and how does AI potentially impinge on it? That’s today’s conversation.

Behind all those algorithms are the people who create them and embed them into our lives. How did they get that power? What should they do with it? What are their responsibilities? This and more with my guest Chris Wiggins, Chief Data Scientist at the New York Times, Associate Professor of Applied Mathematics at Columbia University, and author of the book “How Data Happened: A History from the Age of Reason to the Age of Algorithms”. Originally aired in season one.

People in the AI safety community are laboring under an illusion, perhaps even a self-deception, my guest argues. They think they can align AI with our values and control it so that the worst doesn’t happen. But that’s impossible. We can never know how AI will act in the wild any more than we can know how our children will act once they leave the house. Thus, we should never give more control to an AI than we would give an individual person. This is a fascinating discussion with Marcus Arvan, professor of philosophy at The University of Tampa and author of three books on ethics and political theory. You might just leave this conversation wondering if giving more and more capabilities to AI is a huge, potentially life-threatening mistake.