On this episode, Calum Chace joins me to discuss the transformative impact of AI on employment, comparing the current wave of cognitive automation to historical technological revolutions. We talk about "universal generous income", fully-automated luxury capitalism, and redefining education with AI tutors. We end by examining verification of artificial agents and the ethics of attributing consciousness to machines.  

Learn more about Calum's work here: https://calumchace.com  

Timestamps:  

00:00:00  Preview and intro 

00:03:02  Past tech revolutions and AI-driven unemployment 

00:05:43  Cognitive automation: from secretaries to every job 

00:08:02  The “peak horse” analogy and avoiding human obsolescence 

00:10:55  Infinite demand and lump of labor 

00:18:30  Fully-automated luxury capitalism 

00:23:31  Abundance economy and a potential employment cliff 

00:29:37  Education reimagined with personalized AI tutors 

00:36:22  Real-world uses of LLMs: memory, drafting, emotional insight 

00:42:56  Meaning beyond jobs: aristocrats, retirees, and kids 

00:49:51  Four futures of superintelligence 

00:57:20  Conscious AI and empathy as a safety strategy 

01:10:55  Verifying AI agents 

01:25:20  Over-attributing vs under-attributing machine consciousness

On this episode, Tom Davidson joins me to discuss the emerging threat of AI-enabled coups, where advanced artificial intelligence could empower covert actors to seize power. We explore scenarios including secret loyalties within companies, rapid military automation, and how AI-driven democratic backsliding could differ significantly from historical precedents. Tom also outlines key mitigation strategies, risk indicators, and opportunities for individuals to help prevent these threats.  

Learn more about Tom's work here: https://www.forethought.org  

Timestamps:  

00:00:00  Preview: why preventing AI-enabled coups matters 

00:01:24  What do we mean by an “AI-enabled coup”? 

00:01:59  Capabilities AIs would need (persuasion, strategy, productivity) 

00:02:36  Cyber-offense and the road to robotized militaries 

00:05:32  Step-by-step example of an AI-enabled military coup 

00:08:35  How AI-enabled coups would differ from historical coups 

00:09:24  Democratic backsliding (Venezuela, Hungary, U.S. parallels) 

00:12:38  Singular loyalties, secret loyalties, exclusive access 

00:14:01  Secret-loyalty scenario: CEO with hidden control 

00:18:10  From sleeper agents to sophisticated covert AIs 

00:22:22  Exclusive-access threat: one project races ahead 

00:29:03  Could one country outgrow the rest of the world? 

00:40:00  Could a single company dominate global GDP? 

00:47:01  Autocracies vs democracies 

00:54:43  Mitigations for singular and secret loyalties 

01:06:25  Guardrails, monitoring, and controlled-use APIs 

01:12:38  Using AI itself to preserve checks-and-balances 

01:24:53  Risk indicators to watch for AI-enabled coups 

01:33:05  Tom’s risk estimates for the next 5 and 30 years 

01:46:50  How you can help – research, policy, and careers

Anders Sandberg joins me to discuss superintelligence and its profound implications for human psychology, markets, and governance. We talk about physical bottlenecks, tensions between the technosphere and the biosphere, and the long-term cultural and physical forces shaping civilization. We conclude with Sandberg explaining the difficulties of designing reliable AI systems amidst rapid change and coordination risks.  

Learn more about Anders's work here: https://mimircenter.org/anders-sandberg  

Timestamps:  

00:00:00 Preview and intro 

00:04:20 2030 superintelligence scenario 

00:11:55 Status, post-scarcity, and reshaping human psychology 

00:16:00 Physical limits: energy, datacenter, and waste-heat bottlenecks 

00:23:48 Technosphere vs biosphere 

00:28:42 Culture and physics as long-run drivers of civilization 

00:40:38 How superintelligence could upend markets and governments 

00:50:01 State inertia: why governments lag behind companies 

00:59:06 Value lock-in, censorship, and model alignment 

01:08:32 Emergent AI ecosystems and coordination-failure risks 

01:19:34 Predictability vs reliability: designing safe systems 

01:30:32 Crossing the reliability threshold 

01:38:25 Personal reflections on accelerating change

On this episode, Daniel Kokotajlo joins me to discuss why artificial intelligence may surpass the transformative power of the Industrial Revolution, and just how much AI could accelerate AI research. We explore the implications of automated coding, the critical need for transparency in AI development, the prospect of AI-to-AI communication, and whether AI is an inherently risky technology. We end by discussing iterative forecasting and its role in anticipating AI's future trajectory.  

You can learn more about Daniel's work at: https://ai-2027.com and https://ai-futures.org  

Timestamps:  

00:00:00 Preview and intro 

00:00:50 Why AI will eclipse the Industrial Revolution  

00:09:48 How much can AI speed up AI research?  

00:16:13 Automated coding and diffusion 

00:27:37 Transparency in AI development  

00:34:52 Deploying AI internally  

00:40:24 Communication between AIs  

00:49:23 Is AI inherently risky? 

00:59:54 Iterative forecasting

On this episode, Daniel Susskind joins me to discuss disagreements between AI researchers and economists, how we can best measure AI’s economic impact, how human values can influence economic outcomes, what meaningful work will remain for humans in the future, the role of commercial incentives in AI development, and the future of education.  

You can learn more about Daniel's work here: https://www.danielsusskind.com  

Timestamps:  

00:00:00 Preview and intro  

00:03:19 AI researchers versus economists  

00:10:39 Measuring AI's economic effects  

00:16:19 Can AI be steered in positive directions?  

00:22:10 Human values and economic outcomes 

00:28:21 What will remain for people to do?  

00:44:58 Commercial incentives in AI 

00:50:38 Will education move towards general skills? 

00:58:46 Lessons for parents

Ed Newton-Rex joins me to discuss the issue of AI models trained on copyrighted data, and how we might develop fairer approaches that respect human creators. We talk about AI-generated music, Ed’s decision to resign from Stability AI, the industry’s attitude towards rights, authenticity in AI-generated art, and what the future holds for creators, society, and living standards in an increasingly AI-driven world.  

Learn more about Ed's work here: https://ed.newtonrex.com  

Timestamps:  

00:00:00 Preview and intro  

00:04:18 AI-generated music  

00:12:15 Resigning from Stability AI  

00:16:20 AI industry attitudes towards rights 

00:26:22 Fairly Trained  

00:37:16 Special kinds of training data  

00:50:42 The longer-term future of AI  

00:56:09 Will AI improve living standards?  

01:03:10 AI versions of artists  

01:13:28 Authenticity and art  

01:18:45 Competitive pressures in AI 

01:24:06 Priorities going forward

On this episode, Sarah Hastings-Woodhouse joins me to discuss what benchmarks actually measure, AI’s development trajectory in comparison to other technologies, tasks that AI systems can and cannot handle, capability profiles of present and future AIs, the notion of alignment by default, and the leading AI companies’ vague AGI plans. We also discuss the human psychology of AI, including the feelings of living in the "fast world" versus the "slow world", and navigating long-term projects given short timelines.  

Timestamps:  

00:00:00 Preview and intro

00:00:46 What do benchmarks measure?  

00:08:08 Will AI develop like other tech?  

00:14:13 Which tasks can AIs do? 

00:23:00 Capability profiles of AIs  

00:34:04 Timelines and social effects 

00:42:01 Alignment by default?  

00:50:36 Can vague AGI plans be useful? 

00:54:36 The fast world and the slow world 

01:08:02 Long-term projects and short timelines

On this episode, Michael Nielsen joins me to discuss how humanity's growing understanding of nature poses dual-use challenges, whether existing institutions and governance frameworks can adapt to handle advanced AI safely, and how we might recognize signs of dangerous AI. We explore the distinction between AI as agents and tools, how power is latent in the world, implications of widespread powerful hardware, and finally touch upon the philosophical perspectives of deep atheism and optimistic cosmism.

Timestamps:  

00:00:00 Preview and intro 

00:01:05 Understanding is dual-use  

00:05:17 Can we handle AI like other tech?  

00:12:08 Can institutions adapt to AI?  

00:16:50 Recognizing signs of dangerous AI 

00:22:45 Agents versus tools 

00:25:43 Power is latent in the world 

00:35:45 Widespread powerful hardware 

00:42:09 Governance mechanisms for AI 

00:53:55 Deep atheism and optimistic cosmism

On this episode, Ben Goertzel joins me to discuss what distinguishes the current AI boom from previous ones, important but overlooked AI research, simplicity versus complexity in the first AGI, the feasibility of alignment, benchmarks and economic impact, potential bottlenecks to superintelligence, and what humanity should do moving forward.   

Timestamps:  

00:00:00 Preview and intro  

00:01:59 Thinking about AGI in the 1970s  

00:07:28 What's different about this AI boom?  

00:16:10 Former taboos about AGI 

00:19:53 AI research worth revisiting  

00:35:53 Will the first AGI be simple?  

00:48:49 Is alignment achievable?  

01:02:40 Benchmarks and economic impact  

01:15:23 Bottlenecks to superintelligence 

01:23:09 What should we do?

On this episode, Jeff Sebo joins me to discuss artificial consciousness, substrate-independence, possible tensions between AI risk and AI consciousness, the relationship between consciousness and cognitive complexity, and how intuitive versus intellectual approaches guide our understanding of these topics. We also discuss AI companions, AI rights, and how we might measure consciousness effectively.  

You can follow Jeff’s work here: https://jeffsebo.net/  

Timestamps:  

00:00:00 Preview and intro 

00:02:56 Imagining artificial consciousness  

00:07:51 Substrate-independence? 

00:11:26 Are we making progress?  

00:18:03 Intuitions about explanations  

00:24:43 AI risk and AI consciousness  

00:40:01 Consciousness and cognitive complexity  

00:51:20 Intuition versus intellect 

00:58:48 AIs as companions  

01:05:24 AI rights  

01:13:00 Acting under time pressure 

01:20:16 Measuring consciousness  

01:32:11 How can you help?