#212 – Allan Dafoe on why technology is unstoppable & how to shape AI development anyway

#212 – Allan Dafoe on why technology is unstoppable & how to shape AI development anyway

Technology doesn’t force us to do anything — it merely opens doors. But military and economic competition pushes us through.

That’s how today’s guest Allan Dafoe — director of frontier safety and governance at Google DeepMind — explains one of the deepest patterns in technological history: once a powerful new capability becomes available, societies that adopt it tend to outcompete those that don’t. Those who resist too much can find themselves taken over or rendered irrelevant.

Links to learn more, highlights, video, and full transcript.

This dynamic played out dramatically in 1853 when US Commodore Perry sailed into Tokyo Bay with steam-powered warships that seemed magical to the Japanese, who had spent centuries deliberately limiting their technological development. With far greater military power, the US was able to force Japan to open itself to trade. Within 15 years, Japan had undergone the Meiji Restoration and transformed itself in a desperate scramble to catch up.

Today we see hints of similar pressure around artificial intelligence. Even companies, countries, and researchers deeply concerned about where AI could take us feel compelled to push ahead — worried that if they don’t, less careful actors will develop transformative AI capabilities at around the same time anyway.

But Allan argues this technological determinism isn’t absolute. While broad patterns may be inevitable, history shows we do have some ability to steer how technologies are developed, by who, and what they’re used for first.

As part of that approach, Allan has been promoting efforts to make AI more capable of sophisticated cooperation, and improving the tests Google uses to measure how well its models could do things like mislead people, hack and take control of their own servers, or spread autonomously in the wild.

As of mid-2024 they didn’t seem dangerous at all, but we’ve learned that our ability to measure these capabilities is good, but imperfect. If we don’t find the right way to ‘elicit’ an ability we can miss that it’s there.

Subsequent research from Anthropic and Redwood Research suggests there’s even a risk that future models may play dumb to avoid their goals being altered.

That has led DeepMind to a “defence in depth” approach: carefully staged deployment starting with internal testing, then trusted external testers, then limited release, then watching how models are used in the real world. By not releasing model weights, DeepMind is able to back up and add additional safeguards if experience shows they’re necessary.

But with much more powerful and general models on the way, individual company policies won’t be sufficient by themselves. Drawing on his academic research into how societies handle transformative technologies, Allan argues we need coordinated international governance that balances safety with our desire to get the massive potential benefits of AI in areas like healthcare and education as quickly as possible.

Host Rob and Allan also cover:

  • The most exciting beneficial applications of AI
  • Whether and how we can influence the development of technology
  • What DeepMind is doing to evaluate and mitigate risks from frontier AI systems
  • Why cooperative AI may be as important as aligned AI
  • The role of democratic input in AI governance
  • What kinds of experts are most needed in AI safety and governance
  • And much more

Chapters:

  • Cold open (00:00:00)
  • Who's Allan Dafoe? (00:00:48)
  • Allan's role at DeepMind (00:01:27)
  • Why join DeepMind over everyone else? (00:04:27)
  • Do humans control technological change? (00:09:17)
  • Arguments for technological determinism (00:20:24)
  • The synthesis of agency with tech determinism (00:26:29)
  • Competition took away Japan's choice (00:37:13)
  • Can speeding up one tech redirect history? (00:42:09)
  • Structural pushback against alignment efforts (00:47:55)
  • Do AIs need to be 'cooperatively skilled'? (00:52:25)
  • How AI could boost cooperation between people and states (01:01:59)
  • The super-cooperative AGI hypothesis and backdoor risks (01:06:58)
  • Aren’t today’s models already very cooperative? (01:13:22)
  • How would we make AIs cooperative anyway? (01:16:22)
  • Ways making AI more cooperative could backfire (01:22:24)
  • AGI is an essential idea we should define well (01:30:16)
  • It matters what AGI learns first vs last (01:41:01)
  • How Google tests for dangerous capabilities (01:45:39)
  • Evals 'in the wild' (01:57:46)
  • What to do given no single approach works that well (02:01:44)
  • We don't, but could, forecast AI capabilities (02:05:34)
  • DeepMind's strategy for ensuring its frontier models don't cause harm (02:11:25)
  • How 'structural risks' can force everyone into a worse world (02:15:01)
  • Is AI being built democratically? Should it? (02:19:35)
  • How much do AI companies really want external regulation? (02:24:34)
  • Social science can contribute a lot here (02:33:21)
  • How AI could make life way better: self-driving cars, medicine, education, and sustainability (02:35:55)

Video editing: Simon Monsour
Audio engineering: Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong
Camera operator: Jeremy Chevillotte
Transcriptions: Katy Moore

Jaksot(293)

#4 - Howie Lempel on pandemics that kill hundreds of millions and how to stop them

#4 - Howie Lempel on pandemics that kill hundreds of millions and how to stop them

What disaster is most likely to kill more than 10 million human beings in the next 20 years? Terrorism? Famine? An asteroid? Actually it’s probably a pandemic: a deadly new disease that spreads out of control. We’ve recently seen the risks with Ebola and swine flu, but they pale in comparison to the Spanish flu which killed 3% of the world’s population in 1918 to 1920. A pandemic of that scale today would kill 200 million. In this in-depth interview I speak to Howie Lempel, who spent years studying pandemic preparedness for the Open Philanthropy Project. We spend the first 20 minutes covering his work at the foundation, then discuss how bad the pandemic problem is, why it’s probably getting worse, and what can be done about it. Full transcript, apply for personalised coaching to help you work on pandemic preparedness, see what questions are asked when, and read extra resources to learn more. In the second half we go through where you personally could study and work to tackle one of the worst threats facing humanity. Want to help ensure we have no severe pandemics in the 21st century? We want to help. We’ve helped dozens of people formulate their plans, and put them in touch with academic mentors. If you want to work on pandemic preparedness safety, apply for our free coaching service. APPLY FOR COACHING 2m - What does the Open Philanthropy Project do? What’s it like to work there? 16m27s - What grants did OpenPhil make in pandemic preparedness? Did they work out? 22m56s - Why is pandemic preparedness such an important thing to work on? 31m23s - How many people could die in a global pandemic? Is Contagion a realistic movie? 37m05s - Why the risk is getting worse due to scientific discoveries 40m10s - How would dangerous pathogens get released? 45m27s - Would society collapse if a billion people die in a pandemic? 49m25s - The plague, Spanish flu, smallpox, and other historical pandemics 58m30s - How are risks affected by sloppy research security or the existence of factory farming? 1h7m30s - What's already being done? Why institutions for dealing with pandemics are really insufficient. 1h14m30s - What the World Health Organisation should do but can’t. 1h21m51s - What charities do about pandemics and why they aren’t able to fix things 1h25m50s - How long would it take to make vaccines? 1h30m40s - What does the US government do to protect Americans? It’s a mess. 1h37m20s - What kind of people do you know work on this problem and what are they doing? 1h46m30s - Are there things that we ought to be banning or technologies that we should be trying not to develop because we're just better off not having them? 1h49m35s - What kind of reforms are needed at the international level? 1h54m40s - Where should people who want to tackle this problem go to work? 1h59m50s - Are there any technologies we need to urgently develop? 2h04m20s - What about trying to stop humans from having contact with wild animals? 2h08m5s - What should people study if they're young and choosing their major; what should they do a PhD in? Where should they study, and with who? More...

23 Elo 20172h 35min

#3 - Dario Amodei on OpenAI and how AI will change the world for good and ill

#3 - Dario Amodei on OpenAI and how AI will change the world for good and ill

Just two years ago OpenAI didn’t exist. It’s now among the most elite groups of machine learning researchers. They’re trying to make an AI that’s smarter than humans and have $1b at their disposal. Even stranger for a Silicon Valley start-up, it’s not a business, but rather a non-profit founded by Elon Musk and Sam Altman among others, to ensure the benefits of AI are distributed broadly to all of society.  I did a long interview with one of its first machine learning researchers, Dr Dario Amodei, to learn about: * OpenAI’s latest plans and research progress. * His paper *Concrete Problems in AI Safety*, which outlines five specific ways machine learning algorithms can act in dangerous ways their designers don’t intend - something OpenAI has to work to avoid. * How listeners can best go about pursuing a career in machine learning and AI development themselves. Full transcript, apply for personalised coaching to work on AI safety, see what questions are asked when, and read extra resources to learn more. 1m33s - What OpenAI is doing, Dario’s research and why AI is important  13m - Why OpenAI scaled back its Universe project  15m50s - Why AI could be dangerous  24m20s - Would smarter than human AI solve most of the world’s problems?  29m - Paper on five concrete problems in AI safety  43m48s - Has OpenAI made progress?  49m30s - What this back flipping noodle can teach you about AI safety  55m30s - How someone can pursue a career in AI safety and get a job at OpenAI  1h02m30s - Where and what should people study?  1h4m15s - What other paradigms for AI are there?  1h7m55s - How do you go from studying to getting a job? What places are there to work?  1h13m30s - If there's a 17-year-old listening here what should they start reading first?  1h19m - Is this a good way to develop your broader career options? Is it a safe move?  1h21m10s - What if you’re older and haven’t studied machine learning? How do you break in?  1h24m - What about doing this work in academia?  1h26m50s - Is the work frustrating because solutions may not exist?  1h31m35s - How do we prevent a dangerous arms race?  1h36m30s - Final remarks on how to get into doing useful work in machine learning

21 Heinä 20171h 38min

#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 Kesä 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 Kesä 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 Touko 20173min

Suosittua kategoriassa Koulutus

rss-murhan-anatomia
psykopodiaa-podcast
voi-hyvin-meditaatiot-2
jari-sarasvuo-podcast
aamukahvilla
rss-lasnaolon-hetkia-mindfulness-tutuksi
rss-vegaaneista-tykkaan
rss-duodecim-lehti
adhd-podi
rss-elamankoulu
rss-narsisti
rss-vapaudu-voimaasi
psykologiaa-ja-kaikenlaista
ihminen-tavattavissa-tommy-hellsten-instituutti
rss-valo-minussa-2
kehossa
rss-tietoinen-yhteys-podcast-2
rss-koira-haudattuna
aloita-meditaatio
psykologia