New releases

Randomised experiment: If you’re genuinely unsure whether to quit your job or break up, then you probably should

Blog post by · Published August 25th, 2018

One of my favourite studies ever is ‘Heads or Tails: The Impact of a Coin Toss on Major Life Decisions and Subsequent Happiness’ by economist Steven Levitt of ‘Freakonomics’.

Levitt collected tens of thousands of people who were deeply unsure whether to make a big change in their life. After offering some advice on how to make hard choices, those who remained truly undecided were given the chance to use a flip of a coin to settle the issue. 22,500 did so. Levitt then followed up two and six months later to ask people whether they had actually made the change, and how happy they were out of 10.

People who faced an important decision and got heads – which indicated they should quit, break up, propose, or otherwise mix things up – were 11 percentage points more likely to do so.

It’s very rare to get a convincing experiment that can help us answer as general and practical a question as ‘if you’re undecided, should you change your life?’ But this experiment can!

I wish there were much more social science like this, for example, to figure out whether or not people should explore a wider variety of different jobs during their career (for more on that one see our articles on how to find the right career for you and what job characteristics really make people happy).

The widely reported headline result was that people who made a change in their life as a result of the coin flip were 0.48 points happier out of 10,

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#40 – How well can we actually predict the future? Katja Grace on why expert opinion isn’t a great guide to AI’s impact and how to do better

Podcast by and · Published August 21st, 2018

Experts believe that artificial intelligence will be better than humans at driving trucks by 2027, working in retail by 2031, writing bestselling books by 2049, and working as surgeons by 2053. But how seriously should we take these predictions?

Katja Grace, lead author of ‘When Will AI Exceed Human Performance?’, thinks we should treat such guesses as only weak evidence. But she also says there might be much better ways to forecast transformative technology, and that anticipating such advances could be one of our most important projects.

Note: Katja’s organisation AI Impacts is currently hiring part- and full-time researchers.

There’s often pessimism around making accurate predictions in general, and some areas of artificial intelligence might be particularly difficult to forecast.

But there are also many things we’re now able to predict confidently — like the climate of Oxford in five years — that we no longer give ourselves much credit for.

Some aspects of transformative technologies could fall into this category. And these easier predictions could give us some structure on which to base the more complicated ones.

One controversial debate surrounds the idea of an intelligence explosion; how likely is it that there will be a sudden jump in AI capability?

And one way to tackle this is to investigate a more concrete question: what’s the base rate of any technology having a big discontinuity?

A significant historical example was the development of nuclear weapons. Over thousands of years, the energy density of explosives didn’t increase by much. Then within a few years, it got thousands of times better. Discovering what leads to such anomalies may allow us to better predict the possibility of a similar jump in AI capabilities.

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Should you play to your comparative advantage when choosing your career?

Article by · Published August 2018

“Do the job that’s your comparative advantage” might sound like obvious advice, but it turns out to be more complicated.

In this article, we sketch a naive application of comparative advantage to choosing between two career options, and show that it doesn’t apply. Then we give a more complex example where comparative advantage comes back into play, and show how it’s different from “personal fit”.

In brief, we think comparative advantage matters when you’re closely coordinating with a community to fill a limited number of positions, like we are in the effective altruism community. Otherwise, it’s better to do whatever seems highest-impact at the margin.

In the final section, we give some thoughts on how to assess your comparative advantage, and some mistakes people might be making in the effective altruism community.

The following are some research notes on our current thoughts, which we’re publishing for feedback. We’re pretty uncertain about many of the findings, and even how to best define the terms, and could easily see ourselves changing our minds if we did more research.

Reading time: 10 minutes

When does comparative advantage matter?
A simple example where it doesn’t

Here’s a case where you might think comparative advantage applies, but it actually doesn’t. (We’ll define terms more carefully in the next section.)

Imagine there are two types of role, research and outreach. There are also two people,

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#39 – How much should you change your beliefs based on new evidence? Spencer Greenberg on the scientific approach to solving difficult everyday questions

Podcast by and · Published August 7th, 2018

Will Trump be re-elected? Will North Korea give up their nuclear weapons? Will your friend turn up to dinner?

Spencer Greenberg, founder of ClearerThinking.org, has a process for working out such real life problems.

Let’s work through one here: how likely is it that you’ll enjoy listening to this episode?

The first step is to figure out your ‘prior probability’: your estimate of how likely you are to enjoy the interview before getting any further evidence.

Other than applying common sense, one way to figure this out is ‘reference class forecasting’. That is, looking at similar cases and seeing how often something is true, on average.

Spencer is our first ever return guest (Dr Anders Sandberg appeared on episodes 29 and 33 – but only because his one interview was so fascinating that we split it into two).

So one reference class might be, how many Spencer Greenberg episodes of the 80,000 Hours Podcast have you enjoyed so far? Being this specific limits bias in your answer, but with a sample size of just one – you’ll want to add more data points to reduce the variance of the answer (100% or 0% are both too extreme answers).

Zooming out, how many episodes of the 80,000 Hours Podcast have you enjoyed? Let’s say you’ve listened to 10, and enjoyed 8 of them. If so 8 out of 10 might be a reasonable prior.

If we want a bigger sample we can zoom out further: what fraction of long-form interview podcasts have you ever enjoyed?

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#38 – Yew-Kwang Ng on ethics and how to create a much happier world

Podcast by and · Published July 26th, 2018

Will people who think carefully about how to maximize welfare eventually converge on the same views?

The effective altruism community has spent the past 10 years debating how best to increase happiness and reduce suffering, and gradually narrowed in on the world’s poorest people, all sentient animals, and future generations.

Yew-Kwang Ng, Professor of Economics at Nanyang Technological University in Singapore, worked totally independently on this exact question since the 70s. Many of his early conclusions are now conventional wisdom within effective altruism – though other views he holds remain controversial or little-known.

For instance, he thinks we ought to explore increasing pleasure via direct brain stimulation, and that genetic engineering may be an important tool for increasing happiness in the future.

His work has suggested that the welfare of most wild animals is on balance negative and he hopes that in the future this is a problem humanity will work to solve. Yet he thinks that greatly improved conditions for farm animals could eventually justify eating meat.

And he has spent most of his life forcefully advocating for the view that happiness, broadly construed, is the only intrinsically valuable thing.

If it’s true that careful researchers will converge as Prof Ng believes, these ideas may prove as prescient as his other, now widely accepted, opinions.

See below for our summary and appreciation of Kwang’s top publications and insights throughout a lifetime of research.

Born in Japanese-occupied Malaya during WW2, Kwang has led an exceptional life. While in high school he was drawn to physics, mathematics, and philosophy, yet he chose to study economics because of his dream: to establish communism in an independent Malaysia.

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#37 – Finding the best charity requires estimating the unknowable. Here’s how GiveWell tries to do that, according to researcher James Snowden.

Podcast by and · Published July 16th, 2018

What’s the value of preventing the death of a 5-year-old child, compared to a 20-year-old, or an 80-year-old?

The global health community has generally regarded the value as proportional to the number of health-adjusted life-years the person has remaining – but GiveWell, one of the world’s foremost charity evaluators, no longer uses that approach. They found that contrary to the years-remaining’ method, many of their staff actually value preventing the death of an adult more than preventing the death of a young child. But there’s plenty of disagreement, with the team’s estimates spanning a four-fold range.

As James Snowden – a research consultant at GiveWell – explains in this episode, there’s no way around making these controversial judgement calls based on limited information. If you try to ignore a question like this, you just implicitly take an unreflective stance on it instead. And for each charity they investigate there’s 1 or 2 dozen of these highly uncertain parameters that need to be estimated.

GiveWell has been working to find the best way to make these decisions since its inception in 2007. Lives hang in the balance, so they want their staff to say what they really believe and bring whatever private knowledge they have to the table, rather than just defer to their managers, or an imaginary consensus.

Their strategy is to have a massive spreadsheet that lists dozens of things they need to know, and to ask every staff member to give a figure and justification. Then once a year, the GiveWell team gets together to identify what they really disagree about and think through what evidence it would take to change their minds.

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#36 – Tanya Singh on ending the operations management bottleneck in effective altruism

Podcast by and · Published July 11th, 2018

Almost nobody is able to do groundbreaking physics research themselves, and by the time his brilliance was appreciated, Einstein was hardly limited by funding. But what if you could find a way to unlock the secrets of the universe like Einstein nonetheless?

Today’s guest, Tanya Singh, sees herself as doing something like that every day. She’s Executive Assistant to one of her intellectual heroes who she believes is making a huge contribution to improving the world: Professor Bostrom at Oxford University’s Future of Humanity Institute (FHI).

She couldn’t get more work out of Bostrom with extra donations, as his salary is already easily covered. But with her superior abilities as an Executive Assistant, Tanya frees up hours of his time every week, essentially ‘buying’ more Bostrom in a way nobody else can. She also help manage FHI more generally, in so doing freeing up more than an hour of staff time for each hour she works. This gives her the leverage to do more good than other people or other positions.

In our previous episode, Tara Mac Aulay objected to viewing operations work as predominately a way of freeing up other people’s time:

“A good ops person doesn’t just allow you to scale linearly, but also can help figure out bottlenecks and solve problems such that the organization is able to do qualitatively different work, rather than just increase the total quantity”, Tara said.

Tara’s right that buying time for people at the top of their field is just one path to impact, though it’s one Tanya says she finds highly motivating. Other paths include enabling complex projects that would otherwise be impossible, allowing you to hire and grow much faster, and preventing disasters that could bring down a whole organisation – all things that Tanya does at FHI as well.

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#35 – How the audacity to fix things without asking permission can change the world, demonstrated by Tara Mac Aulay

Podcast by and · Published June 22nd, 2018

How broken is the world? How inefficient is a typical organisation? Looking at Tara Mac Aulay’s life, the answer seems to be ‘very’.

At 15 she took her first job – an entry-level position at a chain restaurant. Rather than accept her place, Tara took it on herself to massively improve the store’s shambolic staff scheduling and inventory management. After cutting staff costs 30% she was quickly promoted, and at 16 sent in to overhaul dozens of failing stores in a final effort to save them from closure.

That’s just the first in a startling series of personal stories that take us to a hospital drug dispensary where pharmacists are wasting a third of their time, a chemotherapy ward in Bhutan that’s killing its patients rather than saving lives, and eventually the Centre for Effective Altruism, where Tara becomes CEO and leads it through start-up accelerator Y Combinator.

In this episode – available in audio and summary or transcript below – Tara demonstrates how the ability to do practical things, avoid major screw-ups, and design systems that scale, is both rare and precious.

People with an operations mindset spot failures others can’t see and fix them before they bring an organisation down. This kind of resourcefulness can transform the world by making possible critical projects that would otherwise fall flat on their face.

But as Tara’s experience shows they need to figure out what actually motivates the authorities who often try to block their reforms.

We explore how people with this skill set can do as much good as possible, what 80,000 Hours got wrong in our article ‘Why operations management is one of the biggest bottlenecks in effective altruism’, as well as:

  • Tara’s biggest mistakes and how to deal with the delicate politics of organizational reform.
  • How a student can save a hospital millions with a simple spreadsheet model.
  • The sociology of Bhutan and how medicine in the developing world often makes things worse rather than better.
  • What most people misunderstand about operations, and how to tell if you have what it takes.
  • And finally, operations jobs people should consider applying for, such as those open now at the Centre for Effective Altruism.

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#34 – Politics is so much worse because we use an atrocious 18th century voting system. Aaron Hamlin has a viable plan to fix it.

Podcast by and · Published May 31st, 2018

In 1991 Edwin Edwards won the Louisiana gubernatorial election. In 2001, he was found guilty of racketeering and received a 10 year invitation to Federal prison. The strange thing about that election? By 1991 Edwards was already notorious for his corruption. Actually, that’s not it.

The truly strange thing is that Edwards was clearly the good guy in the race. How is that possible?

His opponent was former Ku Klux Klan Grand Wizard David Duke.

How could Louisiana end up having to choose between a criminal and a Nazi sympathiser?

It’s not like they lacked other options: the state’s moderate incumbent governor Buddy Roemer ran for re-election. Polling showed that Roemer was massively preferred to both the career criminal and the career bigot, and would easily win a head-to-head election against either.

Unfortunately, in Louisiana every candidate from every party competes in the first round, and the top two then go on to a second – a so-called ‘jungle primary’. Vote splitting squeezed out the middle, and meant that Roemer was eliminated in the first round.

Louisiana voters were left with only terrible options, in a run-off election mostly remembered for the proliferation of bumper stickers reading “Vote for the Crook. It’s Important.”

We could look at this as a cultural problem, exposing widespread enthusiasm for bribery and racism that will take generations to overcome. But according to Aaron Hamlin, Executive Director of The Center for Election Science (CES), there’s a simple way to make sure we never have to elect someone hated by more than half the electorate: change how we vote.

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#33 – Oxford’s Anders Sandberg on solar flares, the annual risk of nuclear war, and what if dictators could live forever?

Podcast by and · Published May 29th, 2018

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.

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:

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#32 – Economist Bryan Caplan thinks education is mostly pointless showing off. We test the strength of his case.

Podcast by and · Published May 22nd, 2018

Bryan Caplan’s claim in The Case Against Education is striking: education doesn’t teach people much, we use little of what we learn, and college is mostly about trying to seem smarter than other people – so the government should slash education funding.

It’s a dismaying – almost profane – idea, and one most are inclined to dismiss out of hand. But having read the book, I have to admit that Bryan can point to a surprising amount of evidence in his favour.

After all, imagine this dilemma: you can have either a Princeton education without a diploma, or a Princeton diploma without an education. Which is the bigger benefit of going to Princeton – learning, or convincing people you’re smart? It’s not so easy to say.

For this interview, I searched for the best counterarguments I could find and challenged Bryan on what seem like the book’s weakest or most controversial claims.

Wouldn’t defunding education be especially bad for capable but low income students? Shouldn’t we just make incremental rather than radical changes to policy? If you reduced funding for education, wouldn’t that just lower prices, and not actually change the number of years people study? Is it really true that students who drop out in their final year of college earn about the same as people who never go to college at all?

And while we’re at it, don’t Bryan and I actually use what we learned at college every day? What about studies that show that extra years of education boost IQ scores? And surely the early years of primary school, when you learn reading and arithmetic, are useful even if college isn’t.

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#31 – Allan Dafoe on trying to prepare the world for the possibility that AI will destabilise global politics

Podcast by and · Published May 18th, 2018

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 – Senior Research Fellow in the International Politics of AI at Oxford 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 Director of the Center for the Governance of AI, 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. 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?

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Congressional staffing

Career review by and · Published May 2018

As a congressional staffer you’ll be able to improve how the government uses its enormous power, while also building knowledge of how Congress works and the network to go with it. While some senior positions in the executive branch might be more impactful, Congress is a good place to start out, especially if you don’t have a master’s in policy, security studies or international relations.

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#30 – Eva Vivalt’s research suggests social science findings don’t generalize. So evidence-based development – what is it good for?

Podcast by and · Published May 15th, 2018

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 an education program find that it improves test scores by 0.5 standard deviations – the next result is as likely to be negative or greater than 1 standard deviation, as it is to be between 0-1 standard deviations.

She also observed that results from smaller studies conducted by NGOs – often pilot studies – would often 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 we invest more in collecting evidence to try to get reliable results?

Or, as some critics say, is interest in impact evaluation distracting us from more important issues, like national economic reforms that can’t be tested in randomised controlled trials?

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#29 – Where are the aliens? Anders Sandberg on three new resolutions to the Fermi Paradox and how we could easily colonise the whole universe

Podcast by and · Published May 8th, 2018

Update April 2019: The key theory Dr Sandberg puts forward for why aliens may delay their activities has been strongly disputed in a new paper, which claims it is based on an incorrect understanding of the physics of computation.

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.

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.

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#28 – Owen Cotton-Barratt on why daring scientists should have to get liability insurance

Podcast by and · Published April 27th, 2018

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.

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.

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#27 – The careers and policies that can prevent global catastrophic biological risks, according to world-leading health security expert Dr Tom Inglesby

Podcast by and · Published April 18th, 2018

How about this for a movie idea: a main character has to prevent a new contagious strain of Ebola spreading around the world. She’s the best of the best. So good in fact, that her work on early detection systems contains the strain at its source. Ten minutes into the movie, we see the results of her work – nothing happens. Life goes on as usual. She continues to be amazingly competent, and nothing continues to go wrong. Fade to black. Roll credits.

If your job is to prevent catastrophes, success is when nobody has to pay attention to you. But without regular disasters to remind authorities why they hired you in the first place, they can’t tell if you’re actually achieving anything. And when budgets come under pressure you may find that success condemns you to the chopping block.

Dr. Tom Inglesby, Director of the Center for Health Security at the Johns Hopkins Bloomberg School of Public Health, worries this may be about to happen to the scientists working on the ‘Global Health Security Agenda’.

In 2014 Ebola showed the world why we have to detect and contain new diseases before they spread, and that when it comes to contagious diseases the nations of the world sink or swim together. Fifty countries decided to work together to make sure all their health systems were up to the challenge. Back then Congress provided 5 years’ funding to help some of the world’s poorest countries build the basic health security infrastructure necessary to control pathogens before they could reach the US.

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#26 – How exactly clean meat is created & the advances needed to get it into every supermarket, according to food scientist Marie Gibbons

Podcast by , and · Published April 10th, 2018

First, decide on the type of animal. Next, pick the cell type. Then take a small, painless biopsy, and put the cells in a solution that makes them feel like they’re still in the body. Once the cells are in this comfortable state, they’ll proliferate. One cell becomes two, two becomes four, four becomes eight, and so on. Continue until you have enough cells to make a burger, a nugget, a sausage, or a piece of bacon, then concentrate them until they bind into solid meat.

It’s all surprisingly straightforward in principle according to Marie Gibbons, a research fellow with The Good Food Institute, who has been researching how to improve this process at Harvard Medical School. We might even see clean meat sold commercially within a year.

The real technical challenge is developing large bioreactors and cheap solutions so that we can make huge volumes and drive down costs.

This interview covers the science and technology involved at each stage of clean meat production, the challenges and opportunities that face cutting-edge researchers like Marie, and how you could become one of them.

Marie’s research focuses on turkey cells. But as she explains, with clean meat the possibilities extend well beyond those of traditional meat. Chicken, cow, pig, but also panda – and even dinosaurs could be on the menus of the future.

Today’s episode is hosted by Natalie Cargill, a barrister in London with a background in animal advocacy. Natalie and Marie also discuss:

  • Why Marie switched from being a vet to developing clean meat
  • For people who want to dedicate themselves to animal welfare, how does working in clean meat fare compared to other career options? How can people get jobs in the area?
  • How did this become an established field?
  • How important is the choice of animal species and cell type in this process?
  • What are the biggest problems with current production methods?
  • Is this kind of research best done in an academic setting, a commercial setting, or a balance between the two?
  • How easy will it be to get consumer acceptance?
  • How valuable would extra funding be for cellular agriculture?
  • Can we use genetic modification to speed up the process?
  • Is it reasonable to be sceptical of the possibility of clean meat becoming financially competitive with traditional meat any time in the near future?

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#25 – Why we have to lie to ourselves about why we do what we do, according to economist Robin Hanson

Podcast by and · Published March 28th, 2018

On February 2, 1685, England’s King Charles II was struck by a sudden illness. Fortunately his physicians were the best of the best. To reassure the public they were kept abreast of the King’s treatment regimen. King Charles was made to swallow a toxic metal; had blistering agents applied to his scalp; had pigeon droppings attached to his feet; was prodded with a red-hot poker; given forty drops of ooze from “the skull of a man that was never buried”; and, finally, had crushed stones from the intestines of an East Indian goat forced down his throat. Sadly, despite these heroic efforts, he passed away the following week.

Why did the doctors go this far?

Prof Robin Hanson – Associate Professor of Economics at George Mason University – suspects that on top of any medical beliefs the doctors had a hidden motive: it needed to be clear, to the King and the public, that the physicians cared enormously about saving His Royal Majesty. Only extreme measures could make it undeniable that they had done everything they could.

If you believe Hanson, the same desire to prove we care about our family and friends explains much of what’s perverse about our medical system today.

And not only what’s perverse about medicine – Robin thinks we’re mostly kidding ourselves when we say our charities exist to help others, our schools exist to educate students, and our political expression is about choosing wise policies.

So important are hidden motives for navigating our social world that we have to deny them to ourselves, lest we accidentally reveal them to others.

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