{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"80,000 Hours Podcast","title":"#150 – Tom Davidson on how quickly AI could transform the world","html":"","width":"100%","height":180,"duration":10919,"description":"It’s easy to dismiss alarming AI-related predictions when you don’t know where the numbers came from. \r\n\r\nFor example: what if we told you that within 15 years, it’s likely that we’ll see a 1,000x improvement in AI capabilities in a single year? And what if we then told you that those improvements would lead to explosive economic growth unlike anything humanity has seen before? \r\n\r\nYou might think, “Congratulations, you said a big number — but this kind of stuff seems crazy, so I’m going to keep scrolling through Twitter.” \r\n\r\nBut this 1,000x yearly improvement is a prediction based on *real economic models* created by today’s guest Tom Davidson, Senior Research Analyst at Open Philanthropy. By the end of the episode, you’ll either be able to point out specific flaws in his step-by-step reasoning, or have to at least *consider* the idea that the world is about to get — at a minimum — incredibly weird. \r\n\r\nLinks to learn more, summary and full transcript. \r\n\r\nAs a teaser, consider the following: \r\n\r\n\r\nDeveloping artificial general intelligence (AGI) — AI that can do 100% of cognitive tasks at least as well as the best humans can — could very easily lead us to an unrecognisable world. \r\n\r\nYou might think having to train AI systems individually to do every conceivable cognitive task — one for diagnosing diseases, one for doing your taxes, one for teaching your kids, etc. — sounds implausible, or at least like it’ll take decades. \r\n\r\nBut Tom thinks we might not need to train AI to do every single job — we might just need to train it to do one: AI research. \r\n\r\nAnd building AI capable of doing research and development might be a much easier task — especially given that the researchers training the AI are AI researchers themselves. \r\n\r\nAnd once an AI system is as good at accelerating future AI progress as the best humans are today — and we can run billions of copies of it round the clock — it’s hard to make the case that we won’t achieve AGI very quickly. \r\n\r\nTo...","thumbnail_url":"https://img.transistorcdn.com/VO1STE7hN95RRg9QdLo4soV2VhhbR9PF5ZZlRhDYcwE/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxNDAyLzE2ODM1/NDQ1NDAtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}