#150 – Tom Davidson on how quickly AI could transform the world

#150 – Tom Davidson on how quickly AI could transform the world

It’s easy to dismiss alarming AI-related predictions when you don’t know where the numbers came from.

For 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?

You might think, “Congratulations, you said a big number — but this kind of stuff seems crazy, so I’m going to keep scrolling through Twitter.”

But 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.

Links to learn more, summary and full transcript.

As a teaser, consider the following:

Developing 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.

You 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.

But 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.

And 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.

And 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.

To give you some perspective: 17 years ago we saw the launch of Twitter, the release of Al Gore's *An Inconvenient Truth*, and your first chance to play the Nintendo Wii.

Tom thinks that if we have AI that significantly accelerates AI R&D, then it’s hard to imagine not having AGI 17 years from now.

Wild.

Host Luisa Rodriguez gets Tom to walk us through his careful reports on the topic, and how he came up with these numbers, across a terrifying but fascinating three hours.

Luisa and Tom also discuss:

• How we might go from GPT-4 to AI disaster
• Tom’s journey from finding AI risk to be kind of scary to really scary
• Whether international cooperation or an anti-AI social movement can slow AI progress down
• Why it might take just a few years to go from pretty good AI to superhuman AI
• How quickly the number and quality of computer chips we’ve been using for AI have been increasing
• The pace of algorithmic progress
• What ants can teach us about AI
• And much more

Chapters:

  • Rob’s intro (00:00:00)
  • The interview begins (00:04:53)
  • How we might go from GPT-4 to disaster (00:13:50)
  • Explosive economic growth (00:24:15)
  • Are there any limits for AI scientists? (00:33:17)
  • This seems really crazy (00:44:16)
  • How is this going to go for humanity? (00:50:49)
  • Why AI won’t go the way of nuclear power (01:00:13)
  • Can we definitely not come up with an international treaty? (01:05:24)
  • How quickly we should expect AI to “take off” (01:08:41)
  • Tom’s report on AI takeoff speeds (01:22:28)
  • How quickly will we go from 20% to 100% of tasks being automated by AI systems? (01:28:34)
  • What percent of cognitive tasks AI can currently perform (01:34:27)
  • Compute (01:39:48)
  • Using effective compute to predict AI takeoff speeds (01:48:01)
  • How quickly effective compute might increase (02:00:59)
  • How quickly chips and algorithms might improve (02:12:31)
  • How to check whether large AI models have dangerous capabilities (02:21:22)
  • Reasons AI takeoff might take longer (02:28:39)
  • Why AI takeoff might be very fast (02:31:52)
  • Fast AI takeoff speeds probably means shorter AI timelines (02:34:44)
  • Going from human-level AI to superhuman AI (02:41:34)
  • Going from AGI to AI deployment (02:46:59)
  • Were these arguments ever far-fetched to Tom? (02:49:54)
  • What ants can teach us about AI (02:52:45)
  • Rob’s outro (03:00:32)


Producer: Keiran Harris
Audio mastering: Simon Monsour and Ben Cordell
Transcriptions: Katy Moore

Avsnitt(299)

#2 - David Spiegelhalter on risk, stats and improving understanding of science

#2 - David Spiegelhalter on risk, stats and improving understanding of science

Recorded in 2015 by Robert Wiblin with colleague Jess Whittlestone at the Centre for Effective Altruism, and recovered from the dusty 80,000 Hours archives. David Spiegelhalter is a statistician at the University of Cambridge and something of an academic celebrity in the UK. Part of his role is to improve the public understanding of risk - especially everyday risks we face like getting cancer or dying in a car crash. As a result he’s regularly in the media explaining numbers in the news, trying to assist both ordinary people and politicians focus on the important risks we face, and avoid being distracted by flashy risks that don’t actually have much impact. Summary, full transcript and extra links to learn more. To help make sense of the uncertainties we face in life he has had to invent concepts like the microlife, or a 30-minute change in life expectancy. (https://en.wikipedia.org/wiki/Microlife) We wanted to learn whether he thought a lifetime of work communicating science had actually had much impact on the world, and what advice he might have for people planning their careers today.

21 Juni 201733min

#1 - Miles Brundage on the world's desperate need for AI strategists and policy experts

#1 - Miles Brundage on the world's desperate need for AI strategists and policy experts

Robert Wiblin, Director of Research at 80,000 Hours speaks with Miles Brundage, research fellow at the University of Oxford's Future of Humanity Institute. Miles studies the social implications surrounding the development of new technologies and has a particular interest in artificial general intelligence, that is, an AI system that could do most or all of the tasks humans could do. This interview complements our profile of the importance of positively shaping artificial intelligence and our guide to careers in AI policy and strategy Full transcript, apply for personalised coaching to work on AI strategy, see what questions are asked when, and read extra resources to learn more.

5 Juni 201755min

#0 – Introducing the 80,000 Hours Podcast

#0 – Introducing the 80,000 Hours Podcast

80,000 Hours is a non-profit that provides research and other support to help people switch into careers that effectively tackle the world's most pressing problems. This podcast is just one of many things we offer, the others of which you can find at 80000hours.org. Since 2017 this show has been putting out interviews about the world's most pressing problems and how to solve them — which some people enjoy because they love to learn about important things, and others are using to figure out what they want to do with their careers or with their charitable giving. If you haven't yet spent a lot of time with 80,000 Hours or our general style of thinking, called effective altruism, it's probably really helpful to first go through the episodes that set the scene, explain our overall perspective on things, and generally offer all the background information you need to get the most out of the episodes we're making now. That's why we've made a new feed with ten carefully selected episodes from the show's archives, called 'Effective Altruism: An Introduction'. You can find it by searching for 'Effective Altruism' in your podcasting app or at 80000hours.org/intro. Or, if you’d rather listen on this feed, here are the ten episodes we recommend you listen to first: • #21 – Holden Karnofsky on the world's most intellectual foundation and how philanthropy can have maximum impact by taking big risks • #6 – Toby Ord on why the long-term future of humanity matters more than anything else and what we should do about it • #17 – Will MacAskill on why our descendants might view us as moral monsters • #39 – Spencer Greenberg on the scientific approach to updating your beliefs when you get new evidence • #44 – Paul Christiano on developing real solutions to the 'AI alignment problem' • #60 – What Professor Tetlock learned from 40 years studying how to predict the future • #46 – Hilary Greaves on moral cluelessness, population ethics and tackling global issues in academia • #71 – Benjamin Todd on the key ideas of 80,000 Hours • #50 – Dave Denkenberger on how we might feed all 8 billion people through a nuclear winter • 80,000 Hours Team chat #3 – Koehler and Todd on the core idea of effective altruism and how to argue for it

1 Maj 20173min

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