Ethical Machines

The podcast explores the essential role of historians in addressing modern tech challenges. By examining the historical roots of AI and social media, the speakers highlight how past values shape current issues. They argue that understanding these contexts is crucial for effective policymaking and ethical AI development. The discussion emphasizes a humanistic approach to technology that aligns with societal values, urging for solutions that consider historical narratives. Ultimately, it’s a call for a more informed and responsible tech movement.

In this discussion, Avijit Ghosh, an Applied Policy Researcher at Hugging Face focused on AI safety, reveals the perils of deploying agentic AI without proper safeguards. He highlights the gaps in current AI ethical practices and the challenges in managing autonomy within these systems. Ghosh emphasizes the importance of human oversight in communication protocols between AI agents. Their conversation dives into the necessity for robust cybersecurity measures and the ethical implications of AI in critical fields like healthcare.

In this discussion, Michael Klenk, an assistant professor of practical philosophy at Delft University, dives into the complexities of algorithmic manipulation on social media. He unpacks the nuanced distinctions between manipulation and persuasion, emphasizing that not all influence is harmful. Klenk also critiques the ethical implications of algorithms, questioning whether they can guide behavior without crossing moral lines. The conversation explores manipulation in both digital media and personal relationships, highlighting the challenges of honesty amid emotional appeals.

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.Advertising Inquiries: https://redcircle.com/brands

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.Advertising Inquiries: https://redcircle.com/brands

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.Advertising Inquiries: https://redcircle.com/brands

Dive into the intricate world of AI ethics, exploring the vital distinctions between 'AI for good' and 'AI for not bad.' Discover the challenges of bias and discrimination arising from flawed training data, and understand the implications of privacy concerns in AI. The conversation sheds light on managing ethical risks and the importance of balanced training to prevent biased outcomes. Plus, gain insights on automation bias and the necessity of ethical practices for beneficial AI technology.

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.Advertising Inquiries: https://redcircle.com/brands

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.Advertising Inquiries: https://redcircle.com/brands

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.Advertising Inquiries: https://redcircle.com/brands