#62 – Paul Christiano on messaging the future, increasing compute, & how CO2 impacts your brain

#62 – Paul Christiano on messaging the future, increasing compute, & how CO2 impacts your brain

Imagine that – one day – humanity dies out. At some point, many millions of years later, intelligent life might well evolve again. Is there any message we could leave that would reliably help them out?

In his second appearance on the 80,000 Hours Podcast, machine learning researcher and polymath Paul Christiano suggests we try to answer this question with a related thought experiment: are there any messages we might want to send back to our ancestors in the year 1700 that would have made history likely to go in a better direction than it did? It seems there probably are.

Links to learn more, summary, and full transcript.
Paul's first appearance on the show in episode 44.
An out-take on decision theory.

We could tell them hard-won lessons from history; mention some research questions we wish we'd started addressing earlier; hand over all the social science we have that fosters peace and cooperation; and at the same time steer clear of engineering hints that would speed up the development of dangerous weapons.

But, as Christiano points out, even if we could satisfactorily figure out what we'd like to be able to tell our ancestors, that's just the first challenge. We'd need to leave the message somewhere that they could identify and dig up. While there are some promising options, this turns out to be remarkably hard to do, as anything we put on the Earth's surface quickly gets buried far underground.

But even if we figure out a satisfactory message, and a ways to ensure it's found, a civilization this far in the future won't speak any language like our own. And being another species, they presumably won't share as many fundamental concepts with us as humans from 1700. If we knew a way to leave them thousands of books and pictures in a material that wouldn't break down, would they be able to decipher what we meant to tell them, or would it simply remain a mystery?

That's just one of many playful questions discussed in today's episode with Christiano — a frequent writer who's willing to brave questions that others find too strange or hard to grapple with.

We also talk about why divesting a little bit from harmful companies might be more useful than I'd been thinking. Or whether creatine might make us a bit smarter, and carbon dioxide filled conference rooms make us a lot stupider.

Finally, we get a big update on progress in machine learning and efforts to make sure it's reliably aligned with our goals, which is Paul's main research project. He responds to the views that DeepMind's Pushmeet Kohli espoused in a previous episode, and we discuss whether we'd be better off if AI progress turned out to be most limited by algorithmic insights, or by our ability to manufacture enough computer processors.

Some other issues that come up along the way include:

• Are there any supplements people can take that make them think better?
• What implications do our views on meta-ethics have for aligning AI with our goals?
• Is there much of a risk that the future will contain anything optimised for causing harm?
• An out-take about the implications of decision theory, which we decided was too confusing and confused to stay in the main recording.

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. Or read the transcript below.

The 80,000 Hours Podcast is produced by Keiran Harris.

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#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

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