Future of Life Institute Podcast

Fr. Michael Baggot joins the podcast to provide a Catholic perspective on transhumanism and superintelligence. We also discuss the meta-narratives, the value of cultural diversity in attitudes toward technology, and how Christian communities deal with advanced AI.   You can learn more about Michael's work here:   https://catholic.tech/academics/faculty/michael-baggot  Timestamps:  00:00 Meta-narratives and transhumanism  15:28 Advanced AI and religious communities  27:22 Superintelligence  38:31 Countercultures and technology  52:38 Christian perspectives and tradition 01:05:20 God-like artificial intelligence  01:13:15 A positive vision for AI

David "davidad" Dalrymple joins the podcast to explore Safeguarded AI — an approach to ensuring the safety of highly advanced AI systems. We discuss the structure and layers of Safeguarded AI, how to formalize more aspects of the world, and how to build safety into computer hardware.  You can learn more about David's work at ARIA here:   https://www.aria.org.uk/opportunity-spaces/mathematics-for-safe-ai/safeguarded-ai/   Timestamps:  00:00 What is Safeguarded AI?  16:28 Implementing Safeguarded AI 22:58 Can we trust Safeguarded AIs?  31:00 Formalizing more of the world  37:34 The performance cost of verified AI  47:58 Changing attitudes towards AI  52:39 Flexible‬‭ Hardware-Enabled‬‭ Guarantees 01:24:15 Mind uploading  01:36:14 Lessons from David's early life

Nick Allardice joins the podcast to discuss how GiveDirectly uses AI to target cash transfers and predict natural disasters. Learn more about Nick's work here: https://www.nickallardice.com  Timestamps: 00:00 What is GiveDirectly? 15:04 AI for targeting cash transfers 29:39 AI for predicting natural disasters 46:04 How scalable is GiveDirectly's AI approach? 58:10 Decentralized vs. centralized data collection 1:04:30 Dream scenario for GiveDirectly

Nathan Labenz joins the podcast to provide a comprehensive overview of AI progress since the release of GPT-4. You can find Nathan's podcast here: https://www.cognitiverevolution.ai   Timestamps: 00:00 AI progress since GPT-4  10:50 Multimodality  19:06 Low-cost models  27:58 Coding versus medicine/law  36:09 AI agents  45:29 How much are people using AI?  53:39 Open source  01:15:22 AI industry analysis  01:29:27 Are some AI models kept internal?  01:41:00 Money is not the limiting factor in AI  01:59:43 AI and biology  02:08:42 Robotics and self-driving  02:24:14 Inference-time compute  02:31:56 AI governance  02:36:29 Big-picture overview of AI progress and safety

Connor Leahy joins the podcast to discuss the motivations of AGI corporations, how modern AI is "grown", the need for a science of intelligence, the effects of AI on work, the radical implications of superintelligence, open-source AI, and what you might be able to do about all of this.   Here's the document we discuss in the episode:   https://www.thecompendium.ai  Timestamps: 00:00 The Compendium 15:25 The motivations of AGI corps  31:17 AI is grown, not written  52:59 A science of intelligence 01:07:50 Jobs, work, and AGI  01:23:19 Superintelligence  01:37:42 Open-source AI  01:45:07 What can we do?

Suzy Shepherd joins the podcast to discuss her new short film "Writing Doom", which deals with AI risk. We discuss how to use humor in film, how to write concisely, how filmmaking is evolving, in what ways AI is useful for filmmakers, and how we will find meaning in an increasingly automated world.   Here's Writing Doom:   https://www.youtube.com/watch?v=xfMQ7hzyFW4   Timestamps: 00:00 Writing Doom  08:23 Humor in Writing Doom 13:31 Concise writing  18:37 Getting feedback 27:02 Alternative characters 36:31 Popular video formats 46:53 AI in filmmaking49:52 Meaning in the future

Andrea Miotti joins the podcast to discuss "A Narrow Path" — a roadmap to safe, transformative AI. We talk about our current inability to precisely predict future AI capabilities, the dangers of self-improving and unbounded AI systems, how humanity might coordinate globally to ensure safe AI development, and what a mature science of intelligence would look like.   Here's the document we discuss in the episode:   https://www.narrowpath.co  Timestamps: 00:00 A Narrow Path 06:10 Can we predict future AI capabilities? 11:10 Risks from current AI development 17:56 The benefits of narrow AI  22:30 Against self-improving AI  28:00 Cybersecurity at AI companies  33:55 Unbounded AI  39:31 Global coordination on AI safety 49:43 Monitoring training runs  01:00:20 Benefits of cooperation  01:04:58 A science of intelligence  01:25:36 How you can help

Tamay Besiroglu joins the podcast to discuss scaling, AI capabilities in 2030, breakthroughs in AI agents and planning, automating work, the uncertainties of investing in AI, and scaling laws for inference-time compute. Here's the report we discuss in the episode:  https://epochai.org/blog/can-ai-scaling-continue-through-2030  Timestamps: 00:00 How important is scaling?  08:03 How capable will AIs be in 2030?  18:33 AI agents, reasoning, and planning 23:39 Automating coding and mathematics  31:26 Uncertainty about investing in AI 40:34 Gap between investment and returns  45:30 Compute, software and data 51:54 Inference-time compute 01:08:49 Returns to software R&D  01:19:22 Limits to expanding compute

Ryan Greenblatt, a researcher focused on AI control and safety, dives deep into the complexities of AI alignment. He discusses the critical challenges of ensuring that powerful AI systems align with human values, stressing the need for robust safeguards against potential misalignments. Greenblatt explores the implications of AI's rapid advancements, including the risks of deception and manipulation. He emphasizes the importance of transparency in AI development while contemplating the timeline and takeoff speeds toward achieving human-level AI.

Tom Barnes, an expert on AI capabilities and safety, shares insights on the critical imbalance in funding between AI safety and capabilities. He discusses the importance of robust safety protocols amidst rapid advancements. Barnes also explores global coordination challenges, particularly between the US and China, in navigating AI governance. He emphasizes the value of preparedness through war gaming, highlights the psychological defenses needed against AI manipulation, and advocates for patient philanthropy to foster a resilient world against AI risks.