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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Esben Kran joins the podcast to discuss why securing AGI requires more than traditional cybersecurity, exploring new attack surfaces, adaptive malware, and the societal shifts needed for resilient defenses.
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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.
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Tom Davidson discusses the risks of AI-enabled coups, examining how advanced artificial intelligence could facilitate covert power grabs, alter democratic processes, and outlining strategies to mitigate these emerging threats.
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Anders Sandberg discusses the societal, psychological, and physical impacts of superintelligence, including challenges in AI reliability, market and governance disruption, and the interplay between technology and the biosphere.
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Daniel Kokotajlo discusses the potential for AI to surpass the impact of the Industrial Revolution, the acceleration of AI research, automated coding, transparency, AI-to-AI communication, risks of AI, and the use of iterative forecasting to predict AI's future.
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Daniel Susskind discusses the differing perspectives of AI researchers and economists, the measurement of AI's economic impact, the influence of human values, the future of work, commercial incentives in AI, and changes in education.
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Ed Newton-Rex discusses the challenges of AI models trained on copyrighted material, his resignation from Stability AI, and the future of creator rights and authenticity in an AI-driven world.
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Sarah Hastings-Woodhouse discusses AI benchmarks, development trajectories, current and future capabilities, alignment issues, AGI plans, and the psychological impact of rapid technological change on long-term planning.
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