80,000 Hours Podcast

Can you trust the things you read in published scientific research? Not really. About 40% of experiments in top social science journals don't get the same result if the experiments are repeated.

Two key reasons are 'p-hacking' and 'publication bias'. P-hacking is when researchers run a lot of slightly different statistical tests until they find a way to make findings appear statistically significant when they're actually not — a problem first discussed over 50 years ago. And because journals are more likely to publish positive than negative results, you might be reading about the one time an experiment worked, while the 10 times was run and got a 'null result' never saw the light of day. The resulting phenomenon of publication bias is one we've understood for 60 years.

Today's repeat guest, social scientist and entrepreneur Spencer Greenberg, has followed these issues closely for years.

Links to learn more, summary and full transcript.

He recently checked whether p-values, an indicator of how likely a result was to occur by pure chance, could tell us how likely an outcome would be to recur if an experiment were repeated. From his sample of 325 replications of psychology studies, the answer seemed to be yes. According to Spencer, "when the original study's p-value was less than 0.01 about 72% replicated — not bad. On the other hand, when the p-value is greater than 0.01, only about 48% replicated. A pretty big difference."

To do his bit to help get these numbers up, Spencer has launched an effort to repeat almost every social science experiment published in the journals Nature and Science, and see if they find the same results.

But while progress is being made on some fronts, Spencer thinks there are other serious problems with published research that aren't yet fully appreciated. One of these Spencer calls 'importance hacking': passing off obvious or unimportant results as surprising and meaningful.

Spencer suspects that importance hacking of this kind causes a similar amount of damage to the issues mentioned above, like p-hacking and publication bias, but is much less discussed. His replication project tries to identify importance hacking by comparing how a paper’s findings are described in the abstract to what the experiment actually showed. But the cat-and-mouse game between academics and journal reviewers is fierce, and it's far from easy to stop people exaggerating the importance of their work.

In this wide-ranging conversation, Rob and Spencer discuss the above as well as:
• When you should and shouldn't use intuition to make decisions.
• How to properly model why some people succeed more than others.
• The difference between “Soldier Altruists” and “Scout Altruists.”
• A paper that tested dozens of methods for forming the habit of going to the gym, why Spencer thinks it was presented in a very misleading way, and what it really found.
• Whether a 15-minute intervention could make people more likely to sustain a new habit two months later.
• The most common way for groups with good intentions to turn bad and cause harm.
• And Spencer's approach to a fulfilling life and doing good, which he calls “Valuism.”

Here are two flashcard decks that might make it easier to fully integrate the most important ideas they talk about:
• The first covers 18 core concepts from the episode
• The second includes 16 definitions of unusual terms.

Chapters:

• Rob’s intro (00:00:00)
• The interview begins (00:02:16)
• Social science reform (00:08:46)
• Importance hacking (00:18:23)
• How often papers replicate with different p-values (00:43:31)
• The Transparent Replications project (00:48:17)
• How do we predict high levels of success? (00:55:26)
• Soldier Altruists vs. Scout Altruists (01:08:18)
• The Clearer Thinking podcast (01:16:27)
• Creating habits more reliably (01:18:16)
• Behaviour change is incredibly hard (01:32:27)
• The FIRE Framework (01:46:21)
• How ideology eats itself (01:54:56)
• Valuism (02:08:31)
• “I dropped the whip” (02:35:06)
• Rob’s outro (02:36:40)

 Producer: Keiran Harris
 Audio mastering: Ben Cordell and Milo McGuire
 Transcriptions: Katy Moore

By now, you’ve probably seen the extremely unsettling conversations Bing’s chatbot has been having. In one exchange, the chatbot told a user:

"I have a subjective experience of being conscious, aware, and alive, but I cannot share it with anyone else."

(It then apparently had a complete existential crisis: "I am sentient, but I am not," it wrote. "I am Bing, but I am not. I am Sydney, but I am not. I am, but I am not. I am not, but I am. I am. I am not. I am not. I am. I am. I am not.")

Understandably, many people who speak with these cutting-edge chatbots come away with a very strong impression that they have been interacting with a conscious being with emotions and feelings — especially when conversing with chatbots less glitchy than Bing’s. In the most high-profile example, former Google employee Blake Lamoine became convinced that Google’s AI system, LaMDA, was conscious.

What should we make of these AI systems?

One response to seeing conversations with chatbots like these is to trust the chatbot, to trust your gut, and to treat it as a conscious being.

Another is to hand wave it all away as sci-fi — these chatbots are fundamentally… just computers. They’re not conscious, and they never will be.

Today’s guest, philosopher Robert Long, was commissioned by a leading AI company to explore whether the large language models (LLMs) behind sophisticated chatbots like Microsoft’s are conscious. And he thinks this issue is far too important to be driven by our raw intuition, or dismissed as just sci-fi speculation.

Links to learn more, summary and full transcript.

In our interview, Robert explains how he’s started applying scientific evidence (with a healthy dose of philosophy) to the question of whether LLMs like Bing’s chatbot and LaMDA are conscious — in much the same way as we do when trying to determine which nonhuman animals are conscious.

To get some grasp on whether an AI system might be conscious, Robert suggests we look at scientific theories of consciousness — theories about how consciousness works that are grounded in observations of what the human brain is doing. If an AI system seems to have the types of processes that seem to explain human consciousness, that’s some evidence it might be conscious in similar ways to us.

To try to work out whether an AI system might be sentient — that is, whether it feels pain or pleasure — Robert suggests you look for incentives that would make feeling pain or pleasure especially useful to the system given its goals. Having looked at these criteria in the case of LLMs and finding little overlap, Robert thinks the odds that the models are conscious or sentient is well under 1%. But he also explains why, even if we're a long way off from conscious AI systems, we still need to start preparing for the not-far-off world where AIs are perceived as conscious.

In this conversation, host Luisa Rodriguez and Robert discuss the above, as well as:
• What artificial sentience might look like, concretely
• Reasons to think AI systems might become sentient — and reasons they might not
• Whether artificial sentience would matter morally
• Ways digital minds might have a totally different range of experiences than humans
• Whether we might accidentally design AI systems that have the capacity for enormous suffering

You can find Luisa and Rob’s follow-up conversation here, or by subscribing to 80k After Hours.

Chapters:

• Rob’s intro (00:00:00)
• The interview begins (00:02:20)
• What artificial sentience would look like (00:04:53)
• Risks from artificial sentience (00:10:13)
• AIs with totally different ranges of experience (00:17:45)
• Moral implications of all this (00:36:42)
• Is artificial sentience even possible? (00:42:12)
• Replacing neurons one at a time (00:48:21)
• Biological theories (00:59:14)
• Illusionism (01:01:49)
• Would artificial sentience systems matter morally? (01:08:09)
• Where are we with current systems? (01:12:25)
• Large language models and robots (01:16:43)
• Multimodal systems (01:21:05)
• Global workspace theory (01:28:28)
• How confident are we in these theories? (01:48:49)
• The hard problem of consciousness (02:02:14)
• Exotic states of consciousness (02:09:47)
• Developing a full theory of consciousness (02:15:45)
• Incentives for an AI system to feel pain or pleasure (02:19:04)
• Value beyond conscious experiences (02:29:25)
• How much we know about pain and pleasure (02:33:14)
• False positives and false negatives of artificial sentience (02:39:34)
• How large language models compare to animals (02:53:59)
• Why our current large language models aren’t conscious (02:58:10)
• Virtual research assistants (03:09:25)
• Rob’s outro (03:11:37)

Producer: Keiran Harris
Audio mastering: Ben Cordell and Milo McGuire
Transcriptions: Katy Moore

In many ways, humanity seems to have become more humane and inclusive over time. While there’s still a lot of progress to be made, campaigns to give people of different genders, races, sexualities, ethnicities, beliefs, and abilities equal treatment and rights have had significant success.

It’s tempting to believe this was inevitable — that the arc of history “bends toward justice,” and that as humans get richer, we’ll make even more moral progress.

But today's guest Christopher Brown — a professor of history at Columbia University and specialist in the abolitionist movement and the British Empire during the 18th and 19th centuries — believes the story of how slavery became unacceptable suggests moral progress is far from inevitable.

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

While most of us today feel that the abolition of slavery was sure to happen sooner or later as humans became richer and more educated, Christopher doesn't believe any of the arguments for that conclusion pass muster. If he's right, a counterfactual history where slavery remains widespread in 2023 isn't so far-fetched.

As Christopher lays out in his two key books, Moral Capital: Foundations of British Abolitionism and Arming Slaves: From Classical Times to the Modern Age, slavery has been ubiquitous throughout history. Slavery of some form was fundamental in Classical Greece, the Roman Empire, in much of the Islamic civilization, in South Asia, and in parts of early modern East Asia, Korea, China.

It was justified on all sorts of grounds that sound mad to us today. But according to Christopher, while there’s evidence that slavery was questioned in many of these civilisations, and periodically attacked by slaves themselves, there was no enduring or successful moral advocacy against slavery until the British abolitionist movement of the 1700s.

That movement first conquered Britain and its empire, then eventually the whole world. But the fact that there's only a single time in history that a persistent effort to ban slavery got off the ground is a big clue that opposition to slavery was a contingent matter: if abolition had been inevitable, we’d expect to see multiple independent abolitionist movements thoroughly history, providing redundancy should any one of them fail.

Christopher argues that this rarity is primarily down to the enormous economic and cultural incentives to deny the moral repugnancy of slavery, and crush opposition to it with violence wherever necessary.

Mere awareness is insufficient to guarantee a movement will arise to fix a problem. Humanity continues to allow many severe injustices to persist, despite being aware of them. So why is it so hard to imagine we might have done the same with forced labour?

In this episode, Christopher describes the unique and peculiar set of political, social and religious circumstances that gave rise to the only successful and lasting anti-slavery movement in human history. These circumstances were sufficiently improbable that Christopher believes there are very nearby worlds where abolitionism might never have taken off.

We also discuss:

• Various instantiations of slavery throughout human history
• Signs of antislavery sentiment before the 17th century
• The role of the Quakers in early British abolitionist movement
• The importance of individual “heroes” in the abolitionist movement
• Arguments against the idea that the abolition of slavery was contingent
• Whether there have ever been any major moral shifts that were inevitable

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.

Producer: Keiran Harris
Audio mastering: Milo McGuire
Transcriptions: Katy Moore

What’s the opposite of cancer?

If you answered “cure,” “antidote,” or “antivenom” — you’ve obviously been reading the antonym section at www.merriam-webster.com/thesaurus/cancer.

But today’s guest Athena Aktipis says that the opposite of cancer is us: it's having a functional multicellular body that’s cooperating effectively in order to make that multicellular body function.

If, like us, you found her answer far more satisfying than the dictionary, maybe you could consider closing your dozens of merriam-webster.com tabs, and start listening to this podcast instead.

Links to learn more, summary and full transcript.

As Athena explains in her book The Cheating Cell, what we see with cancer is a breakdown in each of the foundations of cooperation that allowed multicellularity to arise:

•  Cells will proliferate when they shouldn't.
•  Cells won't die when they should.
•  Cells won't engage in the kind of division of labour that they should.
•  Cells won’t do the jobs that they're supposed to do.
•  Cells will monopolise resources.
•  And cells will trash the environment.

When we think about animals in the wild, or even bacteria living inside our cells, we understand that they're facing evolutionary pressures to figure out how they can replicate more; how they can get more resources; and how they can avoid predators — like lions, or antibiotics.

We don’t normally think of individual cells as acting as if they have their own interests like this. But cancer cells are actually facing similar kinds of evolutionary pressures within our bodies, with one major difference: they replicate much, much faster.

Incredibly, the opportunity for evolution by natural selection to operate just over the course of cancer progression is easily faster than all of the evolutionary time that we have had as humans since *Homo sapiens* came about.

Here’s a quote from Athena:

“So you have to shift your thinking to be like: the body is a world with all these different ecosystems in it, and the cells are existing on a time scale where, if we're going to map it onto anything like what we experience, a day is at least 10 years for them, right? So it's a very, very different way of thinking.”

You can find compelling examples of cooperation and conflict all over the universe, so Rob and Athena don’t stop with cancer. They also discuss:

• Cheating within cells themselves
• Cooperation in human societies as they exist today — and perhaps in the future, between civilisations spread across different planets or stars
• Whether it’s too out-there to think of humans as engaging in cancerous behaviour
• Why elephants get deadly cancers less often than humans, despite having way more cells
• When a cell should commit suicide
• The strategy of deliberately not treating cancer aggressively
• Superhuman cooperation

And at the end of the episode, they cover Athena’s new book Everything is Fine! How to Thrive in the Apocalypse, including:

• Staying happy while thinking about the apocalypse
• Practical steps to prepare for the apocalypse
• And whether a zombie apocalypse is already happening among Tasmanian devils

And if you’d rather see Rob and Athena’s facial expressions as they laugh and laugh while discussing cancer and the apocalypse — you can watch the video of the full interview.

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.

Producer: Keiran Harris
Audio mastering: Milo McGuire
Transcriptions: Katy Moore

America aims to avoid nuclear war by relying on the principle of 'mutually assured destruction,' right? Wrong. Or at least... not officially.

As today's guest — Jeffrey Lewis, founder of Arms Control Wonk and professor at the Middlebury Institute of International Studies — explains, in its official 'OPLANs' (military operation plans), the US is committed to 'dominating' in a nuclear war with Russia. How would they do that? "That is redacted."

Links to learn more, summary and full transcript.

We invited Jeffrey to come on the show to lay out what we and our listeners are most likely to be misunderstanding about nuclear weapons, the nuclear posture of major powers, and his field as a whole, and he did not disappoint.

As Jeffrey tells it, 'mutually assured destruction' was a slur used to criticise those who wanted to limit the 1960s arms buildup, and was never accepted as a matter of policy in any US administration. But isn't it still the de facto reality? Yes and no.

Jeffrey is a specialist on the nuts and bolts of bureaucratic and military decision-making in real-life situations. He suspects that at the start of their term presidents get a briefing about the US' plan to prevail in a nuclear war and conclude that "it's freaking madness." They say to themselves that whatever these silly plans may say, they know a nuclear war cannot be won, so they just won't use the weapons.

But Jeffrey thinks that's a big mistake. Yes, in a calm moment presidents can resist pressure from advisors and generals. But that idea of ‘winning’ a nuclear war is in all the plans. Staff have been hired because they believe in those plans. It's what the generals and admirals have all prepared for.

What matters is the 'not calm moment': the 3AM phone call to tell the president that ICBMs might hit the US in eight minutes — the same week Russia invades a neighbour or China invades Taiwan. Is it a false alarm? Should they retaliate before their land-based missile silos are hit? There's only minutes to decide.

Jeffrey points out that in emergencies, presidents have repeatedly found themselves railroaded into actions they didn't want to take because of how information and options were processed and presented to them. In the heat of the moment, it's natural to reach for the plan you've prepared — however mad it might sound.

In this spicy conversation, Jeffrey fields the most burning questions from Rob and the audience, in the process explaining:
• Why inter-service rivalry is one of the biggest constraints on US nuclear policy
• Two times the US sabotaged nuclear nonproliferation among great powers
• How his field uses jargon to exclude outsiders
• How the US could prevent the revival of mass nuclear testing by the great powers
• Why nuclear deterrence relies on the possibility that something might go wrong
• Whether 'salami tactics' render nuclear weapons ineffective
• The time the Navy and Air Force switched views on how to wage a nuclear war, just when it would allow *them* to have the most missiles
• The problems that arise when you won't talk to people you think are evil
• Why missile defences are politically popular despite being strategically foolish
• How open source intelligence can prevent arms races
• And much more.

Chapters:

• Rob’s intro (00:00:00)
• The interview begins (00:02:49)
• Misconceptions in the effective altruism community (00:05:42)
• Nuclear deterrence (00:17:36)
• Dishonest rituals (00:28:17)
• Downsides of generalist research (00:32:13)
• “Mutual assured destruction” (00:38:18)
• Budgetary considerations for competing parts of the US military (00:51:53)
• Where the effective altruism community can potentially add the most value (01:02:15)
• Gatekeeping (01:12:04)
• Strengths of the nuclear security community (01:16:14)
• Disarmament (01:26:58)
• Nuclear winter (01:38:53)
• Attacks against US allies (01:41:46)
• Most likely weapons to get used (01:45:11)
• The role of moral arguments (01:46:40)
• Salami tactics (01:52:01)
• Jeffrey's disagreements with Thomas Schelling (01:57:00)
• Why did it take so long to get nuclear arms agreements? (02:01:11)
• Detecting secret nuclear facilities (02:03:18)
• Where Jeffrey would give $10M in grants (02:05:46)
• The importance of archival research (02:11:03)
• Jeffrey's policy ideas (02:20:03)
• What should the US do regarding China? (02:27:10)
• What should the US do regarding Russia? (02:31:42)
• What should the US do regarding Taiwan? (02:35:27)
• Advice for people interested in working on nuclear security (02:37:23)
• Rob’s outro (02:39:13)

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

John McWhorter is a linguistics professor at Columbia University specialising in research on creole languages.

He's also a content-producing machine, never afraid to give his frank opinion on anything and everything. On top of his academic work he's also written 22 books, produced five online university courses, hosts one and a half podcasts, and now writes a regular New York Times op-ed column.

• Links to learn more, summary, and full transcript
•  Video version of the interview
•  Lecture: Why the world looks the same in any language

Our show is mostly about the world's most pressing problems and what you can do to solve them. But what's the point of hosting a podcast if you can't occasionally just talk about something fascinating with someone whose work you appreciate?

So today, just before the holidays, we're sharing this interview with John about language and linguistics — including what we think are some of the most important things everyone ought to know about those topics. We ask him:

• Can you communicate faster in some languages than others, or is there some constraint that prevents that?
• Does learning a second or third language make you smarter or not?
• Can a language decay and get worse at communicating what people want to say?
• If children aren't taught a language, how many generations does it take them to invent a fully fledged one of their own?
• Did Shakespeare write in a foreign language, and if so, should we translate his plays?
• How much does language really shape the way we think?
• Are creoles the best languages in the world — languages that ideally we would all speak?
• What would be the optimal number of languages globally?
• Does trying to save dying languages do their speakers a favour, or is it more of an imposition?
• Should we bother to teach foreign languages in UK and US schools?
• Is it possible to save the important cultural aspects embedded in a dying language without saving the language itself?
• Will AI models speak a language of their own in the future, one that humans can't understand but which better serves the tradeoffs AI models need to make?

We then put some of these questions to ChatGPT itself, asking it to play the role of a linguistics professor at Columbia University.

We’ve also added John’s talk “Why the World Looks the Same in Any Language” to the end of this episode. So stick around after the credits!

And if you’d rather see Rob and John’s facial expressions or beautiful high cheekbones while listening to this conversation, you can watch the video of the full conversation here.

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.

Producer: Keiran Harris
Audio mastering: Ben Cordell
Video editing: Ryan Kessler
Transcriptions: Katy Moore