{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"80,000 Hours Podcast","title":"#40 - Katja Grace on forecasting future technology & how much we should trust expert predictions","html":"","width":"100%","height":180,"duration":7878,"description":"Experts believe that artificial intelligence will be better than humans at driving trucks by 2027, working in retail by 2031, writing bestselling books by 2049, and working as surgeons by 2053. But how seriously should we take these predictions?\n\nKatja Grace, lead author of ‘When Will AI Exceed Human Performance?’, thinks we should treat such guesses as only weak evidence. But she also says there might be much better ways to forecast transformative technology, and that anticipating such advances could be one of our most important projects.\n\nNote: Katja's organisation AI Impacts is currently hiring part- and full-time researchers.\n\nThere’s often pessimism around making accurate predictions in general, and some areas of artificial intelligence might be particularly difficult to forecast. \n\nBut there are also many things we’re able to predict confidently today -- like the climate of Oxford in five years -- that we no longer give ourselves much credit for.\n\nSome aspects of transformative technologies could fall into this category. And these easier predictions could give us some structure on which to base the more complicated ones.\n\nLinks to learn more, summary and full transcript.\n\nOne controversial debate surrounds the idea of an intelligence explosion; how likely is it that there will be a sudden jump in AI capability?\n\nAnd one way to tackle this is to investigate a more concrete question: what’s the base rate of any technology having a big discontinuity?\n\nA significant historical example was the development of nuclear weapons. Over thousands of years, the efficacy of explosives didn’t increase by much. Then within a few years, it got thousands of times better. Discovering what leads to such anomalies may allow us to better predict the possibility of a similar jump in AI capabilities.\n\nIn today’s interview we also discuss:\n\n* Why is AI impacts one of the most important projects in the world? \n* How do you structure important surveys? Why do you get such different...","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}