Ethical Machines

People, especially kids under 18, are forming emotional attachments with AI chatbots. At a minimum, this is…weird. Is it also unethical? Does it harm users? Is it, as my guest Robert Mahari argues, an affront to human dignity? Have a listen and find out.Advertising Inquiries: https://redcircle.com/brands

You might want more online content moderation so insane conspiracy theories don’t flourish. Sex slaves in Democrat pizza shops, climate change is a hoax, and so on. But is it irrational to believe these things? Is content moderation - whether in the form of censoring or labelling something as false - the morally right and/or effective strategy? In this discussion Neil Levy and I go back to basics about what it is to be rational and how that helps us answer our questions. Neil’s fascinating answer in a nutshell: they’re not irrational and content moderation isn’t a good strategy. This is, I have to say, great stuff. Enjoy!Advertising Inquiries: https://redcircle.com/brands

From the best of season 1. Part 2 of my conversation with Alex. There’s good reason to think AI doesn’t understand anything. It’s just moving around words according to mathematical rules, predicting the words that come next. But in this episode, philosopher Alex Grzankowski argues that AI may not understand what it’s saying but it does understand language. In this episode we do a deep dive into the nature of human and AI understanding, ending with strategies for how AI researchers could pursue AI that has genuine understanding of the world.Advertising Inquiries: https://redcircle.com/brands

In a captivating discussion, Alex Grzankowski, a philosophy professor at Birkbeck College and director of the London AI Humanity and AI Project, dives into the depths of understanding in AI versus human cognition. He critiques the common perception that models like ChatGPT truly comprehend language. Exploring the Chinese Room Argument, Alex raises essential questions about machine comprehension, the ethical implications in tech, and the distinction between symbol manipulation and genuine understanding. Get ready to rethink what ‘understanding’ actually means!

One person driving one car creates a negligible amount of pollution. The problem arises when we have lots of people driving cars. Might this kind of issue arise with AI use as well? What if everyone uses the same hiring or lending or diagnostic algorithm? My guest, Kathleen Creel, argues that this is bad for society and bad for the companies using these algorithms. The solution, in broad strokes, is to introduce randomness into the AI system. But is this a good idea? If so, do we need regulation to pull it off? This and more on today’s episode.Advertising Inquiries: https://redcircle.com/brands

Abdi Adid, a visiting associate professor of law at Yale and co-author of "The Legal Singularity," dives into the transformative potential of AI in law. He discusses how AI can synthesize dense legal texts to provide clarity and accessibility for the average person. The conversation touches on AI's role in navigating property rights, its impact on the legal landscape, and the balance between technology and human judgment. The ethical implications of AI in justice are explored, alongside the challenges of making legal advice accessible while avoiding frivolous lawsuits.

Greg Epstein, the humanist chaplain at Harvard and MIT and author of "Tech Agnostic," dives deep into the notion of technology as a contemporary religion. He explores how technology shapes societal norms and rituals, questioning its ethical implications. Discussions include the existential risks of AI, likening its worship-like fervor to traditional beliefs. Epstein advocates for a much-needed reformation in tech practices, emphasizing accountability among leaders and the necessity for a more equitable approach in the digital landscape.

In this insightful discussion, Carissa Valise, an Oxford philosophy professor and author of "Privacy is Power," dives deep into the implications of data collection. She argues that the mere possession of data infringes on privacy, highlighting its impact on autonomy and democracy. Carissa also tackles the risks of data brokers and the ethical pitfalls of trading personal information. With powerful analogies like the sniper example, she emphasizes the importance of control over data, advocating for robust protections and policy reforms to safeguard individual privacy.

Shannon Vallor, the Bailey Gifford Chair in the Ethics of Data and AI at the University of Edinburgh and author of "The AI Mirror," reframes our understanding of AI. She argues against seeing AI as a human-like entity and instead proposes viewing it as a mirror reflecting our biases and intentions. Vallor critiques how AI perpetuates stereotypes and suggests we prioritize addressing human-centered risks over speculative AI threats. Her insights advocate for a more ethical approach to AI development, emphasizing genuine engagement and innovation.

In this intriguing discussion, philosopher Emma Borg delves into the accountability of AI chatbots after Canada Air lost a lawsuit involving misinformation. She explores the notion of responsibility in AI outputs, questioning whether chatbots should be held accountable for what they say. Through thought experiments, Borg highlights the complex interplay between intention, meaning, and communication, challenging our understanding of AI's role as a responsible entity. This conversation raises profound philosophical queries about the essence of meaning and intentionality in digital dialogues.