Tyler Johnston of the Midas Project discusses applying corporate accountability to the AI industry, focusing on OpenAI's actions, including subpoenas, and the need for transparency and public awareness regarding AI risks.
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William MacAskill discusses his Better Futures essay series, arguing that improving the future's quality deserves equal priority to preventing catastrophe. The conversation explores moral error risks, AI character design, space governance, and ethical reasoning for AI systems.
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Karl Koch discusses the AI Whistleblower Initiative, focusing on transparency and protections for AI insiders who identify safety risks. The episode explores current policies, legal gaps, and practical guidance for potential whistleblowers.
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Maya Ackerman discusses human and machine creativity, exploring its definition, how AI alignment impacts it, and the role of hallucination. The conversation also covers strategies for human-AI collaboration.
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Parmy Olson discusses the transformation of AI companies from research labs to product businesses. The episode explores how funding pressures impact company missions, the role of personalities, safety challenges, and industry power consolidation.
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Adam Gleave, CEO of FAR.AI, discusses post-AGI scenarios, risks of gradual disempowerment, defense-in-depth safety strategies, scalable oversight for AI deception, and the challenges of interpretability, as well as FAR.AI's integrated research and policy work.
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Beatrice Erkers discusses the AI pathways project, focusing on approaches to maintain human oversight and control over AI, including tool AI and decentralized development, and examines trade-offs and strategies for safer AI futures.
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Nate Soares discusses his book on the risks of superintelligent AI, arguing that current approaches make AI unpredictable and uncontrollable, and advocates for an international ban on research toward superintelligence.
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Luke Drago discusses the potential societal and economic impacts of AI dominance, including changes in workplace structures, privacy concerns, and the importance of taking career risks during technological transitions.
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Basil Halperin discusses how financial markets and economic indicators, such as interest rates, can provide insights into AI development timelines and the potential economic impact of transformative AI.
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Benjamin Todd discusses the evolution of reasoning models in AI, potential bottlenecks in compute and robotics, and offers advice on personal preparation for AGI, including skills, networks, and resilience, with projections through 2030.
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Calum Chace discusses the potential for AI to transform employment, exploring universal income, fully-automated economies, AI-driven education, and the ethical challenges of attributing consciousness to machines.
View episodeNo matter your level of experience or seniority, there is something you can do to help us ensure the future of life is positive.
