#116 – Luisa Rodriguez on why global catastrophes seem unlikely to kill us all

#116 – Luisa Rodriguez on why global catastrophes seem unlikely to kill us all

If modern human civilisation collapsed — as a result of nuclear war, severe climate change, or a much worse pandemic than COVID-19 — billions of people might die.

That's terrible enough to contemplate. But what’s the probability that rather than recover, the survivors would falter and humanity would actually disappear for good?

It's an obvious enough question, but very few people have spent serious time looking into it -- possibly because it cuts across history, economics, and biology, among many other fields. There's no Disaster Apocalypse Studies department at any university, and governments have little incentive to plan for a future in which their country probably no longer even exists.

The person who may have spent the most time looking at this specific question is Luisa Rodriguez — who has conducted research at Rethink Priorities, Oxford University's Future of Humanity Institute, the Forethought Foundation, and now here, at 80,000 Hours.

Links to learn more, summary and full transcript.

She wrote a series of articles earnestly trying to foresee how likely humanity would be to recover and build back after a full-on civilisational collapse.

There are a couple of main stories people put forward for how a catastrophe like this would kill every single human on Earth — but Luisa doesn’t buy them.

Story 1: Nuclear war has led to nuclear winter. There's a 10-year period during which a lot of the world is really inhospitable to agriculture. The survivors just aren't able to figure out how to feed themselves in the time period, so everyone dies of starvation or cold.

Why Luisa doesn’t buy it:

Catastrophes will almost inevitably be non-uniform in their effects. If 80,000 people survive, they’re not all going to be in the same city — it would look more like groups of 5,000 in a bunch of different places.

People in some places will starve, but those in other places, such as New Zealand, will be able to fish, eat seaweed, grow potatoes, and find other sources of calories.

It’d be an incredibly unlucky coincidence if the survivors of a nuclear war -- likely spread out all over the world -- happened to all be affected by natural disasters or were all prohibitively far away from areas suitable for agriculture (which aren’t the same areas you’d expect to be attacked in a nuclear war).

Story 2: The catastrophe leads to hoarding and violence, and in addition to people being directly killed by the conflict, it distracts everyone so much from the key challenge of reestablishing agriculture that they simply fail. By the time they come to their senses, it’s too late -- they’ve used up too much of the resources they’d need to get agriculture going again.

Why Luisa doesn’t buy it:

We‘ve had lots of resource scarcity throughout history, and while we’ve seen examples of conflict petering out because basic needs aren’t being met, we’ve never seen the reverse.

And again, even if this happens in some places -- even if some groups fought each other until they literally ended up starving to death — it would be completely bizarre for it to happen to every group in the world. You just need one group of around 300 people to survive for them to be able to rebuild the species.

In this wide-ranging and free-flowing conversation, Luisa and Rob also cover:

• What the world might actually look like after one of these catastrophes
• The most valuable knowledge for survivors
• How fast populations could rebound
• ‘Boom and bust’ climate change scenarios
• And much more

Chapters:

  • Rob’s intro (00:00:00)
  • The interview begins (00:02:37)
  • Recovering from a serious collapse of civilization (00:11:41)
  • Existing literature (00:14:52)
  • Fiction (00:20:42)
  • Types of disasters (00:23:13)
  • What the world might look like after a catastrophe (00:29:09)
  • Nuclear winter (00:34:34)
  • Stuff that might stick around (00:38:58)
  • Grace period (00:42:39)
  • Examples of human ingenuity in tough situations (00:48:33)
  • The most valuable knowledge for survivors (00:57:23)
  • Would people really work together? (01:09:00)
  • Radiation (01:27:08)
  • Learning from the worst pandemics (01:31:40)
  • Learning from fallen civilizations (01:36:30)
  • Direct extinction (01:45:30)
  • Indirect extinction (02:01:53)
  • Rapid recovery vs. slow recovery (02:05:01)
  • Risk of culture shifting against science and tech (02:15:33)
  • Resource scarcity (02:23:07)
  • How fast could populations rebound (02:37:07)
  • Implications for what we ought to do right now (02:43:52)
  • How this work affected Luisa’s views (02:54:00)
  • Boom and bust climate change scenarios (02:57:06)
  • Stagnation and cold wars (03:01:18)
  • How Luisa met her biological father (03:18:23)
  • If Luisa had to change careers (03:40:38)

Producer: Keiran Harris
Audio mastering: Ben Cordell
Transcriptions: Katy Moore

Avsnitt(300)

#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 Juli 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 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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