Ethical Machines

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/

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!

Chapter Six: Dream Teams for Ethical Nightmares

• Three Types of ENC Teams
• ENC Teams as Emergency Response
• Tools for Teams
• ENC Teams in Bloom

Chapter Seven: ENC: An Approach So Flexible It Makes Simone

• Biles Look Like C-3PO
• Hands Off!
• You Do You
• Marrying ENC to Existing Practices
• Folding Existing Resources into ENC Teams
• Folding ENC Teams into Existing Resources
• The Ethical Nightmare Challenge for... Everyone

Chapter 4: The Standard Approach to Responsible AI Is Crumbling

• The Standard Approach
• The Madness in the Method
• Turn That Smile Upside Down
• Cats and Tigers, Oh My!

Chapter 5: Why I Like Nightmares and You Should, Too

• The Power of Nightmares
• What Good Nightmares Look Like
• And Now the Moment You've Been Waiting For

Chapter Two: Things Get Complicated with Generative AI

• So Now We’re Going to Lose My Grandmother, Again
• The Creators’ Version of a Rough Draft
• The Creators Align (Kind of)
• BigBusinessAI
• The Master Prompter
• The Changing AI Risk Landscape

Chapter Three: Humans Had a Good Run, but Now I Bring You... AI Agents!

• How to Build an AI Agent
• AI Agent Ecosystems
• Agentic Sources of Ethical Nightmares
• The Classic “But Humans Make Errors, Too!” Objection
• The Ground Exploded Beneath Our Feet
• After the Earthquake

Interlude: Get a Grip, Man!

My new book released just two days. It’s about how insanely complex the AI risk landscape has become, why the standard approach to Responsible AI is broken, and develops a novel approach to avoiding the worst of AI. In this episode I offer you the Introduction and Chapter 1 of the audiobook. If you don’t laugh at least once, I consider the book a failure.

ISO 42001 sounds serious. It's got a serious (and boring) name, it's backed by 60+ countries, and some companies seek ISO 42001 certification. But is the standard any good? Does it actually prevent harms? Can we have generic standards? And how can the standards be flexible enough to account for the fast paced change in the AI world? I’m a bit of a skeptic about all this, but my guest, Patrick Sullivan, VP of Strategy and Innovation at A-lign, is a true believer. And he makes a strong case. You decide if my skepticism is unwarranted.

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.

My guest today, Josh Gellers, Dean at the University of North Florida, argues that AI has more awards. More specifically, he thinks that AI has been used to create new biological organisms that meet the criteria for moral worth. Does that mean that AI itself has moral worth? Should we think that if something is not natural it lacks moral worth? All this and more in today’s episode

My guests today - Professor Kate Vredenburgh and VR specialist Lauren Wong - argue that there are at least two strong reasons for calming down: first, AI isn’t good enough to replace us at our jobs. Second, even if they were, it’s up to us to develop AI in a way that supports rather than replaces us. We also talk about whether AI adoption is suffering for the same reasons the metaverse was never successful: we’re failing to appreciate how to get people to justifiably buy in to the technology.