#147 – Spencer Greenberg on stopping valueless papers from getting into top journals

You can get your result in a top journal by tricking the reviewers into thinking that it was a valuable or interesting finding when in fact it was essentially a valueless or completely uninteresting finding.

And this only works if you can trick the peer reviewers, because it’s not like they want to publish everything. Peer reviewers can be brutal; a lot of peer reviewers reject stuff. So unless you’ve tricked them into thinking there’s value when there’s not, this method won’t work. So it has to be pretty subtle.

Spencer Greenberg

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.

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. (So far they’re two for three.)

According to Spencer, things are gradually improving. For example he sees more raw data and experimental materials being shared, which makes it much easier to check the work of other researchers.

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.

For instance, do you remember the sensational paper that claimed government policy was driven by the opinions of lobby groups and ‘elites,’ but hardly affected by the opinions of ordinary people? Huge if true! It got wall-to-wall coverage in the press and on social media. But unfortunately, the whole paper could only explain 7% of the variation in which policies were adopted. Basically the researchers just didn’t know what made some campaigns succeed while others didn’t — a point one wouldn’t learn without reading the paper and diving into confusing tables of numbers. Clever writing made their result seem more important and meaningful than it really was.

Another paper Spencer describes claimed to find that people with a history of trauma explore less. That experiment actually featured an “incredibly boring apple-picking game: you had an apple tree in front of you, and you either could pick another apple or go to the next tree. Those were your only options. And they found that people with histories of trauma were more likely to stay on the same tree. Does that actually prove anything about real-world behaviour?” It’s at best unclear.

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 what Spencer calls “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.
  • Spencer’s experiment to see 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 low-guilt approach to a fulfilling life and doing good, which he calls “Valuism.”

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.

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

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In which career can you make the biggest contribution?

One of the most common career paths for people who want to do good is healthcare. So we worked with a doctor, Greg Lewis, to estimate the number of lives saved by a typical clinical doctor in the UK. Greg estimated that the average doctor enables the people they treat to live several hundred years of extra healthy life over the course of their career — equivalent to saving several lives.

This is a lot of impact compared to most jobs, but it’s less than many expect (and we think less than many of the careers we recommend most highly).

One reason has already been covered in this series: issues like health in rich countries already receive a (relatively) large amount of attention.

In this article, we’ll touch on another reason: the impact of a clinical doctor is limited by the number of people they can treat with their own two hands, which puts a cap on the potential size of their contribution.

For instance, Greg decided to switch from clinical medicine to research into health policy, since an improvement to key government policies could affect millions of people — far more than he could ever treat himself.

This illustrates a broader point: careers that do good are often associated with certain job titles — doctor, teacher, charity worker, and so on. Intuitively, people group careers into those that ‘help’ and everything else.

But your job title isn’t what matters —

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Why you should think about virtues — even if you’re a consequentialist

The idea this week: virtues are helpful shortcuts for making moral decisions — but think about consequences to decide what counts as a virtue.

Your career is really ethically important, but it’s not a single, discrete choice. To build a high-impact career you need to make thousands of smaller choices over many years — to take on this particular project, to apply for that internship, to give this person a positive reference, and so on.

How do you make all those little decisions?

If you want to have an impact, you hope to make the decisions that help you have a bigger impact rather than a smaller one. But you can’t go around explicitly estimating the consequences of all the different possible actions you could take — not only would that take too long, you’d probably get it wrong most of the time.

This is where the idea of virtues — lived moral traits like courage, honesty, and kindness — can really come in handy. Instead of calculating out the consequences of all your different possible actions, try asking yourself, “What’s the honest thing to do? What’s the kind thing to do?”

A few places I find ‘virtues thinking’ motivating and useful:

  • When I am facing a difficult work situation,

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    Luisa and Robert Long on how to make independent research more fun

    I felt very impostery. I felt like I should know more maths. I should know more probability. I should know more about how probability distributions worked.

    But basically, whenever I was like incredibly uncertain, I’d try a uniform distribution — which is basically where you put equal probability on all of the possible outcomes. And then I was like, “Do I really believe that’s true?” And if the answer was no, I’d try to add some probability to the things I think are more likely.

    Luisa Rodriguez

    In this episode of 80k After Hours, Luisa Rodriguez and Robert Long have an honest conversation about the challenges of independent research.

    They cover:

    • Assigning probabilities when you’re really uncertain
    • Struggles around self-belief and imposter syndrome
    • The importance of sharing work even when it feels terrible
    • Balancing impact and fun in a job
    • And some mistakes researchers often make

    Who this episode is for:

    • People pursuing independent research
    • People who struggle with self-belief
    • People who feel a pull towards pursuing a career they don’t actually want

    Who this episode isn’t for:

    • People convinced that their research is perfect
    • Angus Hübelschmidt — the president and sole member of the Rob Wiblin Fan Club who refuses to listen to another Rob speak

    You can find their longer conversation on why large language models like GPT (probably) aren’t conscious over on the original 80,000 Hours Podcast feed.

    Get this episode by subscribing to our more experimental podcast on the world’s most pressing problems and how to solve them: type ’80k After Hours’ into your podcasting app. Or read the transcript below.

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

    Gershwin – Rhapsody in Blue, original 1924 version” by Jason Weinberger is licensed under creative commons

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    #146 – Robert Long on why large language models like GPT (probably) aren’t conscious

    This is a general thought I have when working on AI sentience: you notice the lack of certainty we have in the animal case, and you just multiply that times 100. But I think it’s for similar reasons.

    The reason it’s hard with animals is that they’re built in a different way. They have different needs and different environments. They have different ways of solving the problems that they face in their lives. And so it’s very hard to just read off from behaviour what it’s like to be them.

    Robert Long

    By now, you’ve probably seen the extremely unsettling conversations Bing’s chatbot has been having (if you haven’t, check it out — it’s wild stuff). 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 Lemoine 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.

    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.

    Robert thinks there are a few different kinds of evidence we can draw from that are more useful than self-reports from the chatbots themselves.

    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. Things like:

    • Having a physical or virtual body that you need to protect from damage
    • Being more of an “enduring agent” in the world (rather than just doing one calculation taking, at most, seconds)
    • Having a bunch of different kinds of incoming sources of information — visual and audio input, for example — that need to be managed

    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.

    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.

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

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    Be more ambitious: a rational case for dreaming big (if you want to do good)

    Self-help advice often encourages people to “dream big,” “be more ambitious,” or “shoot for the moon” — is that good advice?

    Not always. When asked, more than 75% of Division I basketball players thought they would play professionally, but only 2% actually made it. Whether or not the players in the survey were making a good bet, they overestimated their chances of success… by over 37 times.

    This level of overconfidence is common, and means that “be more ambitious” may not always be the right advice. Some people even enjoy taking risks, which explains why they buy lottery tickets even though they lose money on average. Whether to be more ambitious depends on the domain and the person in question.

    However, if your aim is to have positive impact on the world, we think we can make a rational case for setting ambitious goals — based on the concepts in our key ideas series.

    In short, our advice is to do as much as you can to set up your life so that you can afford to fail, eliminate paths that might cause significant harm, and then aim as high as you can. As a slogan: limit downsides, then target upsides.

    The fraction of high school athletes who will go pro is tiny. Even among Division 1 college athletes, 44–76% believe they will go pro (depending on the sport), but typically under 2% actually make it —

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    What is social impact? A definition

    Lots of people say they want to “make a difference,” “do good,” “have a social impact,” or “make the world a better place” — but they rarely say what they mean by those terms.

    By getting clearer about your definition, you can better target your efforts. So how should you define social impact?

    Over two thousand years of philosophy have gone into that question. We’re going to try to sum up that thinking; introduce a practical, rough-and-ready definition of social impact; and explain why we think it’s a good definition to focus on.

    This is a bit ambitious for one article, so to the philosophers in the audience, please forgive the enormous simplifications.

    A simple definition of social impact

    If you just want a quick answer, here’s the simple version of our definition (a more philosophically precise one — and an argument for it — follows below):

    Your social impact is given by the number of people whose lives you improve and how much you improve them, over the long term.

    This shows that you can increase your impact in two ways: by helping more people over time, or by helping the same number of people to a greater extent (pictured below).

    two ways to have impact

    We say “over the long term” because you can help more people either by helping a greater number now, or taking actions with better long-term effects.

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    80,000 Hours two-year review: 2021 and 2022

    We’ve released our review of our programmes for the years 2021 and 2022. The full document is available for the public, and we’re sharing the summary below.

    You can find our previous evaluations here. We have also updated our mistakes page.

    80,000 Hours delivers four programmes: website, job board, podcast, and one-on-one. We also have a marketing team that attracts users to these programmes, primarily by getting them to visit the website.

    Over the past two years, three of four programmes grew their engagement 2-3x:

    • Podcast listening time in 2022 was 2x higher than in 2020
    • Job board vacancy clicks in 2022 were 3x higher than in 2020
    • The number of one-on-one team calls in 2022 was 3x higher than in 2020

    Web engagement hours fell by 20% in 2021, then grew by 38% in 2022 after we increased investment in our marketing.

    From December 2020 to December 2022, the core team grew by 78% from 14 FTEs to 25 FTEs.

    Ben Todd stepped down as CEO in May 2022 and was replaced by Howie Lempel.

    The collapse of FTX in November 2022 caused significant disruption. As a result, Howie went on leave from 80,000 Hours to be Interim CEO of Effective Ventures Foundation (UK). Brenton Mayer took over as Interim CEO of 80,000 Hours. We are also spending substantially more time liaising with management across the Effective Ventures group,

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      What Bing’s chatbot can tell us about AI risk — and what it can’t

      You may have seen the new Bing. It’s impressive — and, reportedly, unhinged: manipulating people, threatening users and even telling one reporter it loved him.

      You may also have seen me writing about the risk of an AI-related catastrophe.

      I’m not just concerned about AI going wrong in minor ways: I think that there’s a small but possible chance of an existential catastrophe caused by AI within the next 100 years.

      Here’s my view on Bing:

      Bing does tell us a little about how careful we can expect large corporations to be when deploying AI systems.

      But Bing isn’t very dangerous, and isn’t an example of the sorts of misaligned AI that we should be most worried about.

      (Before moving on, I should disclose that my brother, Jacob Hilton, used to work for OpenAI, the AI lab behind both Bing and ChatGPT.)

      How does Bing chat work?

      Bing chat (like ChatGPT) is based on a large language model.

      A large language model is a machine learning algorithm that is basically trained to continue whatever text it is given as input. It writes an article from a headline or continues a poem from the first few lines.

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        Expression of interest: headhunting lead

        About 80,000 Hours

        80,000 Hours’ mission is to get talented people working on the world’s most pressing problems. The effective altruism community, which we are part of, is growing in reach. But how do we make sure people are pursuing the right kinds of work in order to turn all those resources into long-term impact? This is the problem 80,000 Hours is trying to solve.

        We’ve had over eight million visitors to our website (with over 100,000 hours of reading time per year), and more than 3,000 people have now told us that they’ve significantly changed their career plans due to our work. 80,000 Hours is also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Survey.

        About the 1-on-1 team

        The 1-on-1 team at 80,000 Hours provides free, personalised career advice via video calls with our advisors. In 2022 we spoke to well over a thousand people who were looking to make a positive impact with their career, and we think offering tailored job recommendations is a key way we can help. Over the last two years we’ve grown the advising team and maintained a small headhunting service, providing shortlists of great candidates for a few especially exciting roles. We are now looking to build headhunting out into a key part of the value that the 1-on-1 team provides. You can learn more about our work and see some examples of people the 1-on-1 team has helped on our website.

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          Expression of interest: systems hire

          Why 80,000 Hours?

          80,000 Hours’ mission is to get talented people working on the world’s most pressing problems. The effective altruism community, which we are part of, is growing in reach. But how do we make sure people are pursuing the right kinds of work in order to turn all those resources into long-term impact? This is the problem 80,000 Hours is trying to solve.

          We’ve had over eight million visitors to our website (with over 100,000 hours of reading time per year), and more than 3,000 people have now told us that they’ve significantly changed their career plans due to our work. 80,000 Hours is also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Survey.

          The 1on1 team at 80,000 Hours takes people from being “interested in the ideas and wanting to help” to “actually working to solve pressing world problems.” You can learn more about our work and see some examples of people the 1on1 team has helped on our website.

          The role

          Your responsibilities could include:

          • Building systems to enable new ways of delivering value to users
          • Prioritising and implementing changes requested by staff
          • Crafting automations to streamline internal and external processes
          • Analysing data to answer strategically relevant questions
          • Hiring and managing contractors
          • Salesforce administration

          Who we’re looking for

          • Operations mindset –

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            How much do solutions to social problems differ in their effectiveness? A collection of all the studies we could find.

            In a 2013 paper, Dr Toby Ord reviewed data compiled in the second edition of the World Bank’s Disease Control Priorities in Developing Countries, which compared about 100 health interventions in developing countries in terms of how many years of illness they prevent per dollar. He discovered some striking facts about the data:

            • The best interventions were around 10,000 times more cost effective than the worst, and around 50 times more cost effective than the median.
            • If you picked two interventions at random, on average the better one would be 100 times more cost effective than the other.
            • The distribution was heavy-tailed, and roughly lognormal. In fact, it almost exactly followed the 80/20 rule — that is, implementing the top 20% of interventions would do about 80% as much good as implementing all of them.
            • The differences between the very best interventions were larger than the differences between the typical ones, so it’s more important to go from ‘very good’ to ‘very best’ than from ‘so-so’ to ‘very good.’

            He published these results in The Moral Imperative towards Cost-Effectiveness in Global Health, which became one of the papers that started the effective altruism movement. (Note that Ord is an advisor to 80,000 Hours.)

            This data appears to have radical implications for people interested in doing good in the world; namely, by working on one of the best interventions in global health,

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            #145 – Christopher Brown on why slavery abolition wasn’t inevitable

            Even in the face of abolitionist and emancipationist movements, there’s no record, at least that I’m aware of, of slave traders or slaveholding societies saying that they had had enough and they weren’t going to do this anymore.

            Slaving is as old as human history, and I think we tend to forget that it was a norm rather than an exception, and it took different shapes in different times. This is big picture, but what happens in the 19th century I really think is quite unusual, and I don’t think it’s the natural consequence of either economic forces or cultural forces.

            Christopher Brown

            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.

            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.

            Think of coal or oil today: we know that climate change is likely to cause huge harms, and we know that our coal and oil consumption contributes to climate change. But just believing that something is wrong doesn’t necessarily mean humanity stops doing it. We continue to use coal and oil because our whole economy is oriented around their use and we see it as too hard to stop.

            Just as coal and oil are fundamental to the world economy now, for millennia slavery was deeply baked into the way the rich and powerful stayed rich and powerful, and it required a creative leap to imagine it being toppled.

            More generally, 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.

            Some disagree with Christopher, arguing that abolitionism was a natural consequence of the industrial revolution, which reduced Great Britain’s need for human labour, among other changes — and that abolitionism would therefore have eventually taken off wherever industrialization did. But as we discuss, Christopher doesn’t find that reply convincing.

            If he’s right and the abolition of slavery was in fact contingent, we shouldn’t expect moral values to keep improving just because humanity continues to become richer. We might have to be much more deliberate than that if we want to ensure we keep moving moral progress forward.

            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
            • Attitudes to slavery in other religions
            • The spread of antislavery in 18th century Britain
            • 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. Or read the transcript below.

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

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            Is the world getting better or worse?

            The question this week: is the world getting better or worse?

            Three ways the world’s getting better
            1. Poverty has decreased.

            Lots of stats about trends in the world – even ones that seem good to some people – are complicated to evaluate overall.

            But here’s a long-term trend, based on solid data, that seems uncontroversially good:

            Living in extreme poverty is exceedingly difficult. And it’s not just the share of the population in extreme poverty that’s fallen. Since 1990, the absolute number has fallen too.

            2. We’re healthier than ever before.

            For a start, child mortality rates have fallen steeply in the last 100 years, as has the absolute number of children dying before reaching the age of five.

            We’re close to eradicating polio and guinea worm disease, and we’re gradually getting a grip on malaria.

            Overall, life expectancy in every continent is at its highest point ever and is increasing.

            3. Renewable energy generation is rising.

            While global temperatures are soaring and carbon dioxide emissions continue to increase, we’re also producing more renewable energy than ever before:

            The share of energy produced by renewables has been increasing since around 2005.

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              #144 – Athena Aktipis on why cancer is actually one of the fundamental phenomena in our universe

              The larger and more complex a group is, all else being equal, the easier it will be for cheating to arise and go undetected and potentially undermine the system — unless you have other mechanisms there that can sort of protect, monitor, or respond.

              Athena Aktipis

              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.

              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 go and kind of put yourself on a different spatial scale and time scale, and just 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. Then once you shift to that, you’re like, “Oh, wow, there’s so much that could be happening in terms of adaptation inside the body, how cells are actually evolving inside the body over the course of our lifetimes.” That shift just opens up all this potential for using evolutionary approaches in adaptationist thinking to generate hypotheses that then you can test.

              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 our anti-contagious-cancer mechanisms are so successful
              • Why elephants get deadly cancers less often than humans, despite having way more cells
              • When a cell should commit suicide
              • When the human body deliberately produces tumours
              • The strategy of deliberately not treating cancer aggressively
              • Superhuman cooperation
              • And much more

              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. Or read the transcript below.

              Producer: Keiran Harris
              Audio mastering: Milo McGuire
              Video editing: Ryan Kessler
              Transcriptions: Katy Moore

              Continue reading →

              Open position: Content associate

              About the 80,000 Hours web team

              80,000 Hours provides free research and support to help people find careers tackling the world’s most pressing problems.

              We’ve had over 10 million visitors to our website (with over 100,000 hours of reading time per year), and more than 3,000 people have told us that they’ve significantly changed their career plans due to our work. We’re also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Community Survey.

              Our articles are read by thousands, and are among the most important ways we help people shift their careers towards higher-impact options.

              The role

              As a content associate, you would:

              • Support the 80,000 Hours web team flexibly across a range of articles and projects.
              • Proofread 80,000 Hours articles before release, suggest style improvements, and check for errors.
              • Upload new articles and make changes to the site.
              • Ensure that our newsletters are sent out error-free and on time to the over 250,000 people on our mailing list.
              • Provide analytical support for the team, improving our ability to use data to measure and increase our impact.
              • Manage the gathering of feedback on our website from both readers and subject matter experts.
              • Generate ideas for new pieces.
              • Generally help grow the impact of the site.

              Some of the types of pieces you could work on include:

              • Career reviews — e.g.

              Continue reading →

                My thoughts on parenting and having an impactful career

                When my husband and I decided to have children, we didn’t put much thought into the broader social impact of the decision. We got together at secondary school and had been discussing the fact we were going to have kids since we were 18, long before we found effective altruism.

                We made the actual decision to have a child much later, but how it would affect our careers or abilities to help others still wasn’t a large factor in the decision. As with most people though, the decision has, in fact, had significant effects on our careers.

                Raising my son, Leo — now three years old — is one of the great joys of my life, and I’m so happy that my husband and I decided to have him. But having kids can be challenging for anyone, and there may be unique challenges for people who aim to have a positive impact with their careers.

                I’m currently the director of the one-on-one programme at 80,000 Hours and a fund manager for the Effective Altruism Infrastructure Fund. So I wanted to share my experience with parenting and working for organisations whose mission I care about deeply. Here are my aims:

                • Give readers an example of a working parent who also thinks a lot about 80,000 Hours’ advice.
                • Discuss some of the ways having kids is likely to affect the impact you have in your career, for people who want to consider that when deciding whether to have kids.

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                The quick, medium, and long versions of career planning

                I think it’s a good idea to consider how you’re feeling about your career each year. At least, intellectually I think it’s good. In practice, I find it really hard. Compared to others I know, I’m not as naturally drawn to personal reflection and goal-setting. I intended to reflect on my own career over the festive period… and ended up bailing because I found it too stressful.

                But it is important! Without making time to check in on the big career questions, you might stay too long at a job, miss opportunities for doing more good, or fail to push yourself to grow — I’ve certainly been there before.

                So I suggest doing a career review this January — but committing to a realistic volume of work. You can start small. You can also try getting help — ask a friend to act as an “accountability buddy” or apply to talk one-on-one with someone from 80,000 Hours.

                I’m committing to do it too this month — that’s one of the reasons I’m writing this newsletter!

                Here are some of our tools and resources that you could use at whatever level of detail works for you:

                The quick version (30–60 minutes)

                Try our annual career review tool

                These guided questions help you reflect on the last year, consider whether to change your job, and make a plan for this year.

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                2022 in review

                As 2023 gets underway, we’re taking a look back at the content we produced in 2022 and highlighting some particular standouts.

                We published a lot of new articles and podcasts to help our readers have impactful careers — below are some of our favourite pieces from the year.

                Standout posts and articles

                My experience with imposter syndrome — and how to (partly) overcome it
                80,000 Hours team member Luisa Rodriguez wrote this powerful and insightful piece on a challenge many people face when trying to have an impactful career. In it, she describes clearly what it’s like to have imposter syndrome from her own first-hand experience and provides a lot of helpful advice and guidance on how to manage it. I think a lot of people will benefit from reading it.

                Know what you’re optimising for
                Alex Lawsen, one of 80,000 Hours’ advisors, has noticed that people often fall into the trap of trying to optimise the wrong things — like students who spend so much time worrying that their homework is neatly written, rather than actually understanding and learning from the material. The piece offers practical advice for overcoming this issue.

                Anonymous advice: If you want to reduce AI risk, should you take roles that advance AI capabilities?
                This is a really challenging question that we are still struggling with, and this post was one way we have grappled with it. We asked 22 people we trust as thoughtful and informed experts in the field of AI safety for their thoughts,

                Continue reading →

                  #143 – Jeffrey Lewis on the most common misconceptions about nuclear weapons

                  John F. Kennedy had ordered a stand down to all U-2 flights during the Cuban Missile Crisis, because he knew this was exactly the kind of thing that could get out of control. And he did not have total control, but a U-2 flight still went off and somebody got shot down.

                  And Kennedy’s response, which is like peak Kennedy, was, “There’s always some son of a bitch who doesn’t get the message.” And I think that’s a really good way of looking at dynamic complex systems.

                  Jeffrey Lewis

                  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.”

                  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.

                  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.

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

                  Continue reading →