#133 – Max Tegmark on how a 'put-up-or-shut-up' resolution led him to work on AI and algorithmic news selection

#133 – Max Tegmark on how a 'put-up-or-shut-up' resolution led him to work on AI and algorithmic news selection

On January 1, 2015, physicist Max Tegmark gave up something most of us love to do: complain about things without ever trying to fix them.

That “put up or shut up” New Year’s resolution led to the first Puerto Rico conference and Open Letter on Artificial Intelligence — milestones for researchers taking the safe development of highly-capable AI systems seriously.

Links to learn more, summary and full transcript.

Max's primary work has been cosmology research at MIT, but his energetic and freewheeling nature has led him into so many other projects that you would be forgiven for forgetting it. In the 2010s he wrote two best-selling books, Our Mathematical Universe: My Quest for the Ultimate Nature of Reality, and Life 3.0: Being Human in the Age of Artificial Intelligence, and in 2014 founded a non-profit, the Future of Life Institute, which works to reduce all sorts of threats to humanity's future including nuclear war, synthetic biology, and AI.

Max has complained about many other things over the years, from killer robots to the impact of social media algorithms on the news we consume. True to his 'put up or shut up' resolution, he and his team went on to produce a video on so-called ‘Slaughterbots’ which attracted millions of views, and develop a website called 'Improve The News' to help readers separate facts from spin.

But given the stunning recent advances in capabilities — from OpenAI’s DALL-E to DeepMind’s Gato — AI itself remains top of his mind.

You can now give an AI system like GPT-3 the text: "I'm going to go to this mountain with the faces on it. What is the capital of the state to the east of the state that that's in?" And it gives the correct answer (Saint Paul, Minnesota) — something most AI researchers would have said was impossible without fundamental breakthroughs just seven years ago.

So back at MIT, he now leads a research group dedicated to what he calls “intelligible intelligence.” At the moment, AI systems are basically giant black boxes that magically do wildly impressive things. But for us to trust these systems, we need to understand them.

He says that training a black box that does something smart needs to just be stage one in a bigger process. Stage two is: “How do we get the knowledge out and put it in a safer system?”

Today’s conversation starts off giving a broad overview of the key questions about artificial intelligence: What's the potential? What are the threats? How might this story play out? What should we be doing to prepare?

Rob and Max then move on to recent advances in capabilities and alignment, the mood we should have, and possible ways we might misunderstand the problem.

They then spend roughly the last third talking about Max's current big passion: improving the news we consume — where Rob has a few reservations.

They also cover:

• Whether we could understand what superintelligent systems were doing
• The value of encouraging people to think about the positive future they want
• How to give machines goals
• Whether ‘Big Tech’ is following the lead of ‘Big Tobacco’
• Whether we’re sleepwalking into disaster
• Whether people actually just want their biases confirmed
• Why Max is worried about government-backed fact-checking
• And much more

Chapters:

  • Rob’s intro (00:00:00)
  • The interview begins (00:01:19)
  • How Max prioritises (00:12:33)
  • Intro to AI risk (00:15:47)
  • Superintelligence (00:35:56)
  • Imagining a wide range of possible futures (00:47:45)
  • Recent advances in capabilities and alignment (00:57:37)
  • How to give machines goals (01:13:13)
  • Regulatory capture (01:21:03)
  • How humanity fails to fulfil its potential (01:39:45)
  • Are we being hacked? (01:51:01)
  • Improving the news (02:05:31)
  • Do people actually just want their biases confirmed? (02:16:15)
  • Government-backed fact-checking (02:37:00)
  • Would a superintelligence seem like magic? (02:49:50)


Producer: Keiran Harris
Audio mastering: 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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