Artwork

Content provided by The 80,000 Hours Podcast, The 80, and 000 Hours team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The 80,000 Hours Podcast, The 80, and 000 Hours team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Player FM - Podcast App
Go offline with the Player FM app!

#188 – Matt Clancy on whether science is good

2:40:15
 
Share
 

Manage episode 419874418 series 1531348
Content provided by The 80,000 Hours Podcast, The 80, and 000 Hours team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The 80,000 Hours Podcast, The 80, and 000 Hours team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

"Suppose we make these grants, we do some of those experiments I talk about. We discover, for example — I’m just making this up — but we give people superforecasting tests when they’re doing peer review, and we find that you can identify people who are super good at picking science. And then we have this much better targeted science, and we’re making progress at a 10% faster rate than we normally would have. Over time, that aggregates up, and maybe after 10 years, we’re a year ahead of where we would have been if we hadn’t done this kind of stuff.

"Now, suppose in 10 years we’re going to discover a cheap new genetic engineering technology that anyone can use in the world if they order the right parts off of Amazon. That could be great, but could also allow bad actors to genetically engineer pandemics and basically try to do terrible things with this technology. And if we’ve brought that forward, and that happens at year nine instead of year 10 because of some of these interventions we did, now we start to think that if that’s really bad, if these people using this technology causes huge problems for humanity, it begins to sort of wash out the benefits of getting the science a little bit faster." —Matt Clancy

In today’s episode, host Luisa Rodriguez speaks to Matt Clancy — who oversees Open Philanthropy’s Innovation Policy programme — about his recent work modelling the risks and benefits of the increasing speed of scientific progress.

Links to learn more, highlights, and full transcript.

They cover:

  • Whether scientific progress is actually net positive for humanity.
  • Scenarios where accelerating science could lead to existential risks, such as advanced biotechnology being used by bad actors.
  • Why Matt thinks metascience research and targeted funding could improve the scientific process and better incentivise outcomes that are good for humanity.
  • Whether Matt trusts domain experts or superforecasters more when estimating how the future will turn out.
  • Why Matt is sceptical that AGI could really cause explosive economic growth.
  • And much more.

Chapters:

  • Is scientific progress net positive for humanity? (00:03:00)
  • The time of biological perils (00:17:50)
  • Modelling the benefits of science (00:25:48)
  • Income and health gains from scientific progress (00:32:49)
  • Discount rates (00:42:14)
  • How big are the returns to science? (00:51:08)
  • Forecasting global catastrophic biological risks from scientific progress (01:05:20)
  • What’s the value of scientific progress, given the risks? (01:15:09)
  • Factoring in extinction risk (01:21:56)
  • How science could reduce extinction risk (01:30:18)
  • Are we already too late to delay the time of perils? (01:42:38)
  • Domain experts vs superforecasters (01:46:03)
  • What Open Philanthropy’s Innovation Policy programme settled on (01:53:47)
  • Explosive economic growth (02:06:28)
  • Matt’s favourite thought experiment (02:34:57)

Producer and editor: Keiran Harris
Audio engineering lead: Ben Cordell
Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong
Additional content editing: Katy Moore and Luisa Rodriguez
Transcriptions: Katy Moore

  continue reading

250 episodes

Artwork
iconShare
 
Manage episode 419874418 series 1531348
Content provided by The 80,000 Hours Podcast, The 80, and 000 Hours team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The 80,000 Hours Podcast, The 80, and 000 Hours team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

"Suppose we make these grants, we do some of those experiments I talk about. We discover, for example — I’m just making this up — but we give people superforecasting tests when they’re doing peer review, and we find that you can identify people who are super good at picking science. And then we have this much better targeted science, and we’re making progress at a 10% faster rate than we normally would have. Over time, that aggregates up, and maybe after 10 years, we’re a year ahead of where we would have been if we hadn’t done this kind of stuff.

"Now, suppose in 10 years we’re going to discover a cheap new genetic engineering technology that anyone can use in the world if they order the right parts off of Amazon. That could be great, but could also allow bad actors to genetically engineer pandemics and basically try to do terrible things with this technology. And if we’ve brought that forward, and that happens at year nine instead of year 10 because of some of these interventions we did, now we start to think that if that’s really bad, if these people using this technology causes huge problems for humanity, it begins to sort of wash out the benefits of getting the science a little bit faster." —Matt Clancy

In today’s episode, host Luisa Rodriguez speaks to Matt Clancy — who oversees Open Philanthropy’s Innovation Policy programme — about his recent work modelling the risks and benefits of the increasing speed of scientific progress.

Links to learn more, highlights, and full transcript.

They cover:

  • Whether scientific progress is actually net positive for humanity.
  • Scenarios where accelerating science could lead to existential risks, such as advanced biotechnology being used by bad actors.
  • Why Matt thinks metascience research and targeted funding could improve the scientific process and better incentivise outcomes that are good for humanity.
  • Whether Matt trusts domain experts or superforecasters more when estimating how the future will turn out.
  • Why Matt is sceptical that AGI could really cause explosive economic growth.
  • And much more.

Chapters:

  • Is scientific progress net positive for humanity? (00:03:00)
  • The time of biological perils (00:17:50)
  • Modelling the benefits of science (00:25:48)
  • Income and health gains from scientific progress (00:32:49)
  • Discount rates (00:42:14)
  • How big are the returns to science? (00:51:08)
  • Forecasting global catastrophic biological risks from scientific progress (01:05:20)
  • What’s the value of scientific progress, given the risks? (01:15:09)
  • Factoring in extinction risk (01:21:56)
  • How science could reduce extinction risk (01:30:18)
  • Are we already too late to delay the time of perils? (01:42:38)
  • Domain experts vs superforecasters (01:46:03)
  • What Open Philanthropy’s Innovation Policy programme settled on (01:53:47)
  • Explosive economic growth (02:06:28)
  • Matt’s favourite thought experiment (02:34:57)

Producer and editor: Keiran Harris
Audio engineering lead: Ben Cordell
Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong
Additional content editing: Katy Moore and Luisa Rodriguez
Transcriptions: Katy Moore

  continue reading

250 episodes

Kaikki jaksot

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Quick Reference Guide