
Sign up to save your podcasts
Or


Based on Podcast App listening data
Joseph Stalin had a life-extension program dedicated to making himself immortal. What if he had succeeded?
According to our last guest, Bryan Caplan, there’s an 80% chance that Stalin would still be ruling Russia today. Today’s guest disagrees.
Like Stalin he has eyes for his own immortality - including an insurance plan that will cover the cost of cryogenically freezing himself after he dies - and thinks the technology to achieve it might be around the corner.
Fortunately for humanity though, that guest is probably one of the nicest people on the planet: Dr Anders Sandberg of Oxford University.
Full transcript of the conversation, summary, and links to learn more.
The potential availability of technology to delay or even stop ageing means this disagreement matters, so he has been trying to model what would really happen if both the very best and the very worst people in the world could live forever - among many other questions.
Anders, who studies low-probability high-stakes risks and the impact of technological change at the Future of Humanity Institute, is the first guest to appear twice on the 80,000 Hours Podcast and might just be the most interesting academic at Oxford.
His research interests include more or less everything, and bucking the academic trend towards intense specialization has earned him a devoted fan base.
***Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: type *80,000 Hours* into your podcasting app.***
Last time we asked him why we don’t see aliens, and how to most efficiently colonise the universe. In today’s episode we ask about Anders’ other recent papers, including:
* Is it worth the money to freeze your body after death in the hope of future revival, like Anders has done?
* How much is our perception of the risk of nuclear war biased by the fact that we wouldn’t be alive to think about it had one happened?
* If biomedical research lets us slow down ageing would culture stagnate under the crushing weight of centenarians?
* What long-shot drugs can people take in their 70s to stave off death?
* Can science extend human (waking) life by cutting our need to sleep?
* How bad would it be if a solar flare took down the electricity grid? Could it happen?
* If you’re a scientist and you discover something exciting but dangerous, when should you keep it a secret and when should you share it?
* Will lifelike robots make us more inclined to dehumanise one another?
Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: search for '80,000 Hours' in your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
The debate around the impacts of artificial intelligence often centres on ‘superintelligence’ - a general intellect that is much smarter than the best humans, in practically every field.
But according to Allan Dafoe - Assistant Professor of Political Science at Yale University - even if we stopped at today's AI technology and simply collected more data, built more sensors, and added more computing capacity, extreme systemic risks could emerge, including:
* Mass labor displacement, unemployment, and inequality;
* The rise of a more oligopolistic global market structure, potentially moving us away from our liberal economic world order;
* Imagery intelligence and other mechanisms for revealing most of the ballistic missile-carrying submarines that countries rely on to be able to respond to nuclear attack;
* Ubiquitous sensors and algorithms that can identify individuals through face recognition, leading to universal surveillance;
* Autonomous weapons with an independent chain of command, making it easier for authoritarian regimes to violently suppress their citizens.
Allan is Co-Director of the Governance of AI Program, at the Future of Humanity Institute within Oxford University. His goals have been to understand the causes of world peace and stability, which in the past has meant studying why war has declined, the role of reputation and honor as drivers of war, and the motivations behind provocation in crisis escalation.
Full transcript, links to learn more, and summary of key points.
His current focus is helping humanity safely navigate the invention of advanced artificial intelligence.
I ask Allan:
* What are the distinctive characteristics of artificial intelligence from a political or international governance point of view?
* Is Allan’s work just a continuation of previous research on transformative technologies, like nuclear weapons?
* How can AI be well-governed?
* How should we think about the idea of arms races between companies or countries?
* What would you say to people skeptical about the importance of this topic?
* How urgently do we need to figure out solutions to these problems? When can we expect artificial intelligence to be dramatically better than today?
* What’s the most urgent questions to deal with in this field?
* What can people do if they want to get into the field?
* Is there anything unusual that people can look for in themselves to tell if they're a good fit to do this kind of research?
Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: search for '80,000 Hours' in your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
If we have a study on the impact of a social program in a particular place and time, how confident can we be that we’ll get a similar result if we study the same program again somewhere else?
Dr Eva Vivalt is a lecturer in the Research School of Economics at the Australian National University. She compiled a huge database of impact evaluations in global development - including 15,024 estimates from 635 papers across 20 types of intervention - to help answer this question.
Her finding: not confident at all.
The typical study result differs from the average effect found in similar studies so far by almost 100%. That is to say, if all existing studies of a particular education program find that it improves test scores by 10 points - the next result is as likely to be negative or greater than 20 points, as it is to be between 0-20 points.
She also observed that results from smaller studies done with an NGO - often pilot studies - were more likely to look promising. But when governments tried to implement scaled-up versions of those programs, their performance would drop considerably.
For researchers hoping to figure out what works and then take those programs global, these failures of generalizability and ‘external validity’ should be disconcerting.
Is ‘evidence-based development’ writing a cheque its methodology can’t cash? Should this make us invest less in empirical research, or more to get actually reliable results?
Or as some critics say, is interest in impact evaluation distracting us from more important issues, like national or macroeconomic reforms that can’t be easily trialled?
We discuss this as well as Eva’s other research, including Y Combinator’s basic income study where she is a principal investigator.
Full transcript, links to related papers, and highlights from the conversation.
Links mentioned at the start of the show:
* 80,000 Hours Job Board
* 2018 Effective Altruism Survey
**Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: type *80,000 Hours* into your podcasting app.**
Questions include:
* What is the YC basic income study looking at, and what motivates it?
* How do we get people to accept clean meat?
* How much can we generalize from impact evaluations?
* How much can we generalize from studies in development economics?
* Should we be running more or fewer studies?
* Do most social programs work or not?
* The academic incentives around data aggregation
* How much can impact evaluations inform policy decisions?
* How often do people change their minds?
* Do policy makers update too much or too little in the real world?
* How good or bad are the predictions of experts? How does that change when looking at individuals versus the average of a group?
* How often should we believe positive results?
* What’s the state of development economics?
* Eva’s thoughts on our article on social interventions
* How much can we really learn from being empirical?
* How much should we really value RCTs?
* Is an Economics PhD overrated or underrated?
Get this episode by subscribing to our podcast: search for '80,000 Hours' in your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
Part 2 out now: #33 - Dr Anders Sandberg on what if we ended ageing, solar flares & the annual risk of nuclear war
The universe is so vast, yet we don’t see any alien civilizations. If they exist, where are they? Oxford University’s Anders Sandberg has an original answer: they’re ‘sleeping’, and for a very compelling reason.
Because of the thermodynamics of computation, the colder it gets, the more computations you can do. The universe is getting exponentially colder as it expands, and as the universe cools, one Joule of energy gets worth more and more. If they wait long enough this can become a 10,000,000,000,000,000,000,000,000,000,000x gain. So, if a civilization wanted to maximize its ability to perform computations – its best option might be to lie in wait for trillions of years.
Why would a civilization want to maximise the number of computations they can do? Because conscious minds are probably generated by computation, so doing twice as many computations is like living twice as long, in subjective time. Waiting will allow them to generate vastly more science, art, pleasure, or almost anything else they are likely to care about.
Full transcript, related links, and key quotes.
But there’s no point waking up to find another civilization has taken over and used up the universe’s energy. So they’ll need some sort of monitoring to protect their resources from potential competitors like us.
It’s plausible that this civilization would want to keep the universe’s matter concentrated, so that each part would be in reach of the other parts, even after the universe’s expansion. But that would mean changing the trajectory of galaxies during this dormant period. That we don’t see anything like that makes it more likely that these aliens have local outposts throughout the universe, and we wouldn’t notice them until we broke their rules. But breaking their rules might be our last action as a species.
This ‘aestivation hypothesis’ is the invention of Dr Sandberg, a Senior Research Fellow at the Future of Humanity Institute at Oxford University, where he looks at low-probability, high-impact risks, predicting the capabilities of future technologies and very long-range futures for humanity.
In this incredibly fun conversation we cover this and other possible explanations to the Fermi paradox, as well as questions like:
* Should we want optimists or pessimists working on our most important problems?
* How should we reason about low probability, high impact risks?
* Would a galactic civilization want to stop the stars from burning?
* What would be the best strategy for exploring and colonising the universe?
* How can you stay coordinated when you’re spread across different galaxies?
* What should humanity decide to do with its future?
Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: search for '80,000 Hours' in your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
A researcher is working on creating a new virus – one more dangerous than any that exist naturally. They believe they’re being as careful as possible. After all, if things go wrong, their own life and that of their colleagues will be in danger. But if an accident is capable of triggering a global pandemic – hundreds of millions of lives might be at risk. How much additional care will the researcher actually take in the face of such a staggering death toll?
In a new paper Dr Owen Cotton-Barratt, a Research Fellow at Oxford University’s Future of Humanity Institute, argues it’s impossible to expect them to make the correct adjustments. If they have an accident that kills 5 people – they’ll feel extremely bad. If they have an accident that kills 500 million people, they’ll feel even worse – but there’s no way for them to feel 100 million times worse. The brain simply doesn’t work that way.
So, rather than relying on individual judgement, we could create a system that would lead to better outcomes: research liability insurance.
Links to learn more, summary and full transcript.
Once an insurer assesses how much damage a particular project is expected to cause and with what likelihood – in order to proceed, the researcher would need to take out insurance against the predicted risk. In return, the insurer promises that they’ll pay out – potentially tens of billions of dollars – if things go really badly.
This would force researchers think very carefully about the cost and benefits of their work – and incentivize the insurer to demand safety standards on a level that individual researchers can’t be expected to impose themselves.
***Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: type '80,000 Hours' into your podcasting app.***
Owen is currently hiring for a selective, two-year research scholars programme at Oxford.
In this wide-ranging conversation Owen and I also discuss:
* Are academics wrong to value personal interest in a topic over its importance?
* What fraction of research has very large potential negative consequences?
* Why do we have such different reactions to situations where the risks are known and unknown?
* The downsides of waiting for tenure to do the work you think is most important.
* What are the benefits of specifying a vague problem like ‘make AI safe’ more clearly?
* How should people balance the trade-offs between having a successful career and doing the most important work?
* Are there any blind alleys we’ve gone down when thinking about AI safety?
* Why did Owen give to an organisation whose research agenda he is skeptical of?
Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: search for '80,000 Hours' in your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
From the publisher's feed
Ranked by our users in the last 21 days

26,249 Listeners

2,451 Listeners

1,087 Listeners

606 Listeners

123 Listeners

288 Listeners

1,621 Listeners

204 Listeners

98 Listeners

565 Listeners

510 Listeners

5,557 Listeners

140 Listeners

145 Listeners

89 Listeners