How to get good at something useful: Part 7 Career capital: how to invest in yourself

Kate wanted to make a difference, so she did the obvious thing — she went to work at a nonprofit straight out of university. However, she quickly hit a ceiling in terms of how far she could advance.

When we talk to leaders in the nonprofit sector, they often recommend getting trained up elsewhere first. Kate ended up returning to the corporate sector for several years, and thinks she would have ended up ahead if she’d done that straight away. We know many other people who feel like they wasted years of their career.

Don’t make these mistakes. Although it’s great to make a difference right away, you also need to invest in yourself to maximise your impact and fulfilment in the long term. This requires building what we call career capital: skills, connections, and credentials that put you in a better position to make a difference in the future.

However, it’s also possible to make the opposite mistake: generically accumulating credentials for years when it would have been possible to do something meaningful much sooner. Given the urgency of the world’s problems, and how rapidly the world could change due to AI, you need to balance these two types of error.

Here we’ll cover three common mistakes people make when building their careers, and explain how to strike the right balance between investing in yourself and doing your dream job as soon as possible.

Reading time: 10 minutes

The bottom line:

How to invest in yourself without wasting years

What is career capital? Career capital is anything that puts you in a better position to make a difference in the future. It includes skills, connections, credentials, character, and financial runway. To build maximum career capital, avoid these three common mistakes:

  • Mistake 1: Failing to invest in yourself. Most people’s productivity peaks at age 40–50, and it’s possible to become far more productive over time. This means it’s important to compare potential jobs both in terms of their immediate impact and how much career capital they’ll build.

  • Mistake 2: Not figuring out what will advance you most efficiently. Ask people a few steps ahead of you in your target field how to progress fastest. This often reveals jobs that advance you more quickly than generic, prestigious options like consulting, finance, or unnecessary degrees.

  • Mistake 3: Waiting too long to have an impact. Sometimes the more impactful option will also get you better career capital, which means there’s no point taking a detour. If you’re uncertain, consider your time horizon and how large the boost to your career capital will be relative to the directly impactful path. Which option will let you help more overall?

Mistake 1: Failing to invest in yourself

Child prodigy
Mozart is one of the most famous child prodigies, but it’s less widely known that his father was a world-famous music teacher and started training him from age three. Mozart’s sister was also an accomplished player. This is a painting of all three practicing together. Great skill requires lots of practice.

People like to lionise the Mozarts, Malala Yousafzais, and Mark Zuckerbergs of the world: those who achieved great success while young. There are all sorts of awards for young leaders, like the Forbes 30 Under 30 and Time‘s Next Generation Leaders.

But these stories are interesting precisely because they’re the exception. Most people reach the peak of their impact in middle age. Income usually peaks in your forties or fifties — on average at more than double what it was at age 25 — suggesting that it takes around 20 years for most people to reach peak productivity.1

Similarly, expert researchers and creatives tend to peak somewhere between the age of 30 and 60, producing several times as many important works per year as they did age 25.2 The peak is earlier in more conceptual fields, and later in those that are more experimental or require accumulated knowledge. If anything, the age of peak output seems to be increasing over time.3

Even among software startups — famous for their young founders — if you look across the entire industry, the average age at which people start companies is 40,4 and older founders are about twice as likely to succeed.5 In part this is about skills, but it’s also about accumulating connections. That’s why fields like politics and management take longest to peak. It’s rare for anyone to make it to Congress in their twenties, and your odds are over four times higher in your sixties than your thirties.6

Here’s a rough estimate of the age of peak output in a variety of fields:7

FieldAge of peak output
Theoretical physics, lyric poetry, pure mathematicsAround 30
Psychology, chemistryAround 40
Novel writing, history, philosophy, medicineAround 50
Business — average age of S&P500 CEOs55
Politics — average age of first-term (US) president55

The study of expert performance was pioneered by late Swedish psychologist K. Anders Ericsson. After 30 years of research, he concluded:

I have never found a convincing case for anyone developing extraordinary abilities without intense, extended practice.8

For Mozart to succeed so young, he needed to start young. Mozart’s father was a famous music teacher and trained him intensely from the time he was a toddler.

This may sound like a bit of a downer: becoming skilled takes time, especially in established fields. But consider the flip side: it also means you can become much more skilled than you are today.

Lots of people come to us and say, “I’m not sure I have any useful skills to contribute.” That’s often somewhat true — especially if you’ve just graduated. More than likely, you’ve spent the last four years studying Moby Dick, metaphysics, or Molière, and your future job is unlikely to involve any of those.

But Ericsson’s research also suggests that anyone can improve at most things with focused practice. Sure, other factors are important too — if you’re seven feet tall it’s going to be a lot easier to get good at basketball — but that doesn’t mean short people can’t improve their game.

In fact, it’s likely there are ways you can improve a lot, especially if you can find something that matches your talents. We’ve already seen that output rises 2–5 times as people advance in a career path. But you can increase your ability to contribute even more by opening up career paths that are entirely new.

Imagine you’re stuck in a path you don’t think is very impactful, but by doing a master’s you could open up research jobs you think contribute far more. Sometimes the right job, crash course, or connections can increase your impact many times over.

Among people we advise, we’ve seen lots of examples where people become far more successful, happy, and capable by investing in themselves, often in areas they never thought they could succeed in.

Despite the high returns that come from investing in yourself, we also meet many people who want to skip it to do something important and meaningful as soon as possible. I was the same when I first graduated — I wanted to do whatever seemed most likely to have an impact in the next few years.

But as we saw with Kate, that can mean getting stuck in a path where it’s hard to advance. Treading water for a couple of years doesn’t only mean you lose those years, it also delays when you reach your peak impact. So, the first key point is to compare the next job you could take both in terms of its immediate value, and in terms of how much it’ll improve your career capital.

Five components of career capital

What is career capital? At 80,000 Hours we use the term to mean anything that accumulates to put you in a better position to make a difference or find a fulfilling career in the future.

Your skills are the most important part of your career capital, but I use the broader term to make clear that it’s not only about skills.9 When we advise, we often find it helpful to break the concept down into the following factors. Thinking this way provides a lens to assess prospective jobs you might have otherwise dismissed:

  • Skills and knowledge: Your skills are what you fundamentally have to offer. To assess a potential new job, find out what skills you’ll learn in the role and think about how useful they could be now and in the future. A job will be best for learning when you are pushed to improve and get lots of feedback from mentors and colleagues.

  • Connections: Many jobs are found through connections, and they’re a big part of your ability to make things happen. Who will you meet through the job? Could they be potential future collaborators, supportive friends, mentors, influential people, or links to new fields?

  • Credentials: You don’t only need to gain skills, you also need to be able to prove you have them to future employers. This could be with formal credentials, like a law degree, but it could also be past achievements, a reference, or your reputation — anything that acts as a good signal. If you’re a writer, it could be the quality of your blog. If you’re a coder, it might be your GitHub. Ask yourself what you might achieve in the role that would be convincing to people you’d like to work with in the future. (If you want to learn more about selling yourself to employers, take a look at part 14 of this guide.)

  • Character: Traits like integrity, honesty, compassion, humility, respect of group norms, and wise judgement are vital to being trusted, working well with others(/articles/coordination/), and not doing harm. They also determine whether, when faced with a high-stakes decision in the future, you’ll have the strength to do what’s best for the world. Your character is shaped by how you spend your time, and especially the people around you, so carefully consider the character of your colleagues. Also consider whether the role’s built-in incentives will push you in a good or bad direction. Will this job make you into a better version of yourself?

  • Runway: Your ‘runway’ is how long you could comfortably live with no income. It depends on both your savings and how much you could reduce your expenses if necessary. Runway is important because it makes it easier to take risks and make big career changes in the future. Ask how much you’ll be able to save in this job, considering both the salary and the cost of living it’ll encourage.

Mistake 2: Not figuring out what will advance you most efficiently

After finishing a psychology master’s in Amsterdam, and despite a nagging concern it wasn’t right for her, Lauren Kuhns continued into a PhD in the same subject. And indeed, she didn’t enjoy it, leaving academia as soon as it was finished. To make things worse, she then discovered the PhD wasn’t especially helpful in getting her jobs she was interested in.

We’ve advised a lot of people who have started a PhD and gone on to realise they hate academia and that their PhD won’t help much when pursuing other options. They end up feeling like they’ve wasted several years.

It’s common to get sucked into other generally prestigious, ‘safe’ options, most classically things like consulting, finance, law, professional services, and even socially-focused programmes like Teach First or Teach for America. A good test is to imagine you can never tell anyone you’ve done the job. Would you still want to do it? If not, you’re probably pursuing it for prestige, rather than the skills you will actually learn.

Often these kinds of options are really just an expensive form of procrastination, because there are usually much more direct routes into the most impactful careers. For instance, we often come across people who already have a graduate degree, or a lot of work experience, and want to transfer into policy. But they mistakenly think they need to get another degree, this time in policy, before entering.

Instead it’s usually possible to transition after several months of well-targeted reading and networking by applying directly to fellowships and other positions. Rashida Polk was a nurse for eight years before she got inspired to work on pandemic prevention. She was able to join the Horizon Fellowship, which helps people transition into technology policy. In under two years, she was able to work on committee hearings on the origins of COVID-19 and oversight of high-risk virus research.10

Ask yourself, for the options you’re actually interested in, which steps will get you there most efficiently? For the global problems you think matter most, what do they most badly need, and how could you help with those needs the fastest?

The best way to figure this out is to speak to people a few steps ahead of you in the field. Ask them what you could do over the next year that would enable you to contribute most. If you can speak to people who themselves advanced unusually quickly, and ask how they did it, that’s even better.

Usually this means doing something as close as possible to actually doing the work, rather than generic skill-building. Fresh out of college, Daniel Ziegler knew how to code, and wanted to do research on technical AI safety. Instead of finding a normal software engineering job, he emailed Dario Amodei — at the time a leading AI researcher at OpenAI — about how he could most effectively enter the field.

Based on their conversation, Daniel spent six weeks studying deep reinforcement learning intensively with a housemate. They read 20–30 key papers together and practised implementing core algorithms. At the end of the sprint, he had enough knowledge, and evident determination, to start a research engineering position on OpenAI’s safety team, and has since advanced from there, publishing several papers in the field.11

Daniel’s story illustrates principles anyone can apply: he identified the skills most essential to the role (real-world ML engineering), devised an efficient way to learn them (co-working with a housemate), and found a way to demonstrate his skills to employers (GitHub projects). By doing this, he was able to accelerate his career by at least several years.

What about if you’re not yet sure where you’d like to end up in the long term? Then ask yourself, “Where could I maximise my overall rate of learning?” Any position where you’ll learn a tonne can be a good call, even if you’re not sure where it’ll lead. It’s usually better to be in a random organisation with an amazing mentor and co-workers than at a fancy graduate school with a supervisor who hates students.

Mistake 3: Waiting too long to have an impact

Finally ready to do good.

It’s rare to have a big impact right out of college, so at the very start of your career, gaining career capital should (normally) be your biggest priority. However, it’s also possible to make the opposite mistake: accumulating generic credentials or lingering in your corporate job for years when you could have done something meaningful much sooner.

Consider two options:

  1. Work at a nonprofit for two years.
  2. Work at Deloitte for two years, then switch to a nonprofit.

You should only do the second if you’ll end up in a significantly more senior nonprofit role as a result. Otherwise, you’ve missed out on two years of impact for nothing.

People often fail to appreciate that the career capital they’ll gain from the impactful option can sometimes be better than the safe corporate path. By working at the nonprofit, you’ll learn more about how to tackle an important global problem and make connections with others who want to do the same, rather than with random accountants.

But let’s suppose you believe the Deloitte option will in fact help you build better career capital than the more impactful job. Should you take the detour?

The answer depends on your situation. If you’re facing this tradeoff, here are two key questions you can ask yourself.

First, how long is your time horizon? The earlier you are in your career, the more time you have to use your career capital in the future. Learn public speaking at age 22 and you can give talks for decades. Learn it one year before retirement, and you’ll be the most charismatic person at Bingo night.

Not only do younger people have more time ahead of them, people’s work skills usually increase the most from about 25–35, then slow down as they approach their peak.12 This suggests the first few investments in career capital pay off the most, and the returns diminish once you’re already experienced.

Your time horizon can also be shorter depending on issues you think are most pressing. The best opportunities to help in global health or climate change are gradually disappearing as more progress is made, making it important to help sooner than later.13

However, the rate they’re disappearing is relatively slow, so if the world remains relatively normal, it could easily be justified to spend a decade investing in yourself in order to contribute on a greater scale later.

But if you think everything is going to change due to AI in the next five years, and that will create never-to-be-repeated opportunities for impact, then your time horizon could be a lot shorter. And that means your bar for delaying your impact will need to be a lot higher.14

The second question is simply how much career capital do you expect to gain from taking the detour compared to the immediately impactful path? If you can put yourself in a far better position, that will often be the deciding factor. But if the potential career capital is around equal, you should choose the impactful option instead.

In other cases, it will be unclear which side wins. But note that even if you have a very short five-year time horizon, it can still be worth a delay. If you can spend one year to make yourself 30% more productive for the next four, then, roughly speaking, you’ll come out ahead. For example, people who finish college earn around 50% more than high school graduates.15 Income isn’t a perfect measure, but it definitely suggests that finishing college increases your career capital significantly.

In the case of AI specifically, it’s likely that the most consequential moments will come when truly advanced systems are deployed in society, perhaps irreversibly, or key treaties are signed. Therefore your focus should be on getting to the best possible position to be useful in those transitions before they happen. Additionally, you shouldn’t be certain AGI will arrive soon, so you still need to consider the other scenarios where your time horizon is longer.

A final note: if you do decide to do something that temporarily disconnects you from the impact you want to make, try to stay involved in other, small ways, such as by attending conferences, donating 1% of your income, or volunteering. Otherwise, it can be all too easy to drift, losing sight of the good intentions you had at the start of your career.

How can you get the best possible career capital?

Researchers disagree about what’s most crucial for developing valuable expertise, but if you read what they say carefully, they pretty much all agree that the following are all important:

  1. Talent match. You’ll be able to learn some skills much faster than others, and reach higher peaks of performance. This is so important it’s the subject of all of part 10.

  2. Learning environment. Ericsson finds that almost every expert had a great mentor, and also emphasises the importance of clear feedback.

  3. Time spent practising. Your skills improve over time, especially in the first 10 years learning them.

  4. Being in the right place at the right time.

The last point is also important. My career was totally shaped by meeting Toby Ord in 2009 when I (Benjamin) was an undergraduate. I discovered Toby because I used to go to a lot of talks outside of my course. In hindsight, that greatly increased my chances of coming across someone interesting.

High-flyers with unusual success have often got lucky somewhere in their story. They found a company, scene, industry, or technology that was taking off and got in early. This gave them valuable skills and connections that might otherwise have taken much longer to build.

Although luck isn’t something we control, there are steps you can take to increase your chances of getting lucky. Ask yourself the following:

  • Who are the most talented people you know? What are they into?
  • What areas are new and rapidly growing?
  • Have you found a project or idea that feels like it has natural momentum? One that keeps succeeding more than you expect?
  • What are people unfairly biased against working on?

All of these can be signs to work on an area, even if you’re not sure where it’ll lead. In contrast, if you go into an established field like law, academia, or the arts, then you’re going to be in for a long slog competing against many other qualified people.

In order to gain valuable skills, then, you want to find a skill that matches your talents, an environment that helps you learn rapidly, and conditions that maximise your chances of getting lucky.

Once you have some skills, you can use them to notch up achievements to impress employers, to earn and save money, and to make connections with inspiring people of good character — giving you the other aspects of career capital. In short, the goal is to get good, and get known.

But before you start building skills, which skills are actually worth having?

Put into practice

  1. For the roles you’d like to end up in, which steps could most accelerate you towards them?
  • Is there someone in the field you could ask for advice on how to most efficiently enter, given your background?
  • Which skills are most crucial for success in these roles?
  1. Which step might maximise your overall rate of learning over the next few years? List any ideas.

  2. Where are the most talented people you know hanging out? How could you get involved with and learn from them?

  3. What’s the most valuable career capital you already have? This can give you clues about what you’ll be best at and how to convince employers to hire you. Review each of the categories:

  • Skills and knowledge
  • Connections
  • Credentials & reputation
  • Character
  • Runway

If you’re stuck, list out 2–5 achievements you’re most proud of and ask yourself what enabled you to achieve them.

  1. Do you have a longer time horizon? Consider your age and which problems you think are most pressing. Given this, how much should you focus on career capital compared to the immediate value of potential next steps?

Take a break

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Notes and references

  1. One large study in the US found:


    The average life-cycle profile is obtained from panel data or repeated cross sections by regressing log individual earnings on a full set of age and (year-of-birth) cohort dummies. The estimated age dummies are plotted as circles in Figure 3 and represent the average life-cycle profile of log earnings. It has the usual hump-shaped pattern that peaks around age 50.

    One of the most important aspects of a life-cycle profile is the implied growth in average earnings over the life cycle (e.g. from ages 25 to 55). It is well understood that the magnitude of this rise matters greatly for many economic questions, because it is a strong determinant of borrowing and saving motives. In our data, this rise is about 80 log points, which is about 127%.

    We expect the figures to be similar in other countries. The peak could be 10 years lower, but that doesn’t change the basic conclusion.

    Guvenen, Fatih, et al. “What do data on millions of US workers reveal about lifecycle earnings dynamics?” Econometrica, vol. 89, no. 5, 25 June 2021, pp. 2303–2339, onlinelibrary.wiley.com/doi/10.3982/ECTA14603.

  2. One review on the effects of age on outstanding achievement summarises the research as follows:

    At one extreme, some fields are characterised by relatively early peaks, usually around the early 30s or even late 20s in chronological units, with somewhat steep descents thereafter, so that the output rate becomes less than one quarter the maximum. This agewise pattern apparently holds for such endeavors as lyric poetry, pure mathematics, and theoretical physics, for example (Adams, 1946; Dennis, 1966; Lehman, 1953a; Moulin, 1955; Roe, 1972b; Simonton, 1975a; Van Heeringen & Dijkwel, 1987). At the contrary extreme, the typical trends in other endeavors may display a leisurely rise to a comparatively late peak, in the late 40s or even 50s chronologically, with a minimal if not largely absent drop-off afterward. This more elongated curve holds for such domains as novel writing, history, philosophy, medicine, and general scholarship, for instance (Adams, 1946; Richard A. Davis, 1987; Dennis, 1966; Lehman, 1953a; Simonton, 1975a). Of course, many disciplines exhibit age curves somewhat between these two outer limits, with a maximum output rate around chronological age 40 and a notable yet moderate decline thereafter (see, e.g., Fulton & Trow, 1974; Hermann, 1988; McDowell, 1982; Zhao & Jiang, 1986).

    Simonton, Dean K. “Age and outstanding achievement: What do we know after a century of research?” Psychological Bulletin, vol. 104, no. 2, October 1988, pp. 251–267, researchgate.net/publication/20101281_Age_and_Outstanding_Achievement_What_Do_We_Know_After_a_Century_of_Research.

  3. A review paper on the relationship between age and scientific genius:

    For example, Nobel Prize winning research is performed at an average age that is 6 years older at the end of the 20th century than it was at the beginning.

    Jones, Benjamin F., E. J. Reedy, and Bruce A. Weinberg. “Age and scientific genius.” NBER Working Paper Series, January 2014, nber.org/system/files/working_papers/w19866/w19866.pdf.

  4. One survey by the HBR from 2018 found the following:

    In software startups, the average age is 40, and younger founders aren’t uncommon. However, young people are less common in other industries such as oil and gas or biotechnology, where the average age is closer to 47. The preeminent place of young founders in the popular imagination may therefore reflect disproportionate exposure to a handful of consumer-facing IT industries, such as social media, rather than equally consequential pursuits in heavy industry or business-to-business sectors.

    They also found the most successful 0.1% of founders (in terms of their first 5 years of growth) were five years older than average.

    Azoulay, Pierre, et al. “Research: The average age of a successful startup founder is 45.” Harvard Business Review, 11 July 2018, hbr.org/2018/07/research-the-average-age-of-a-successful-startup-founder-is-45.

  5. A founder at age 50 is approximately twice as likely to experience a successful exit compared to a founder at age 30.

    Azoulay et al.

    The average founder at a high-potential startup has 14 years of work experience, although the standard deviation is high. Mid-career professionals are more likely to found a successful startup than people early or late in their careers.

    Azoulay, Pierre, et al. “Age and high-growth entrepreneurship.” American Economic Review: Insights, vol. 2, no. 1, 2020, pp. 65–82, mitsloan.mit.edu/shared/ods/documents?PublicationDocumentID=6212.
    Wasserman, Noam. The founders dilemmas – anticipating and avoiding the pitfalls that can sink a startup. Princeton University Press, 2013.

  6. The 118th Congress had 150 people in their sixties and 37 people in their thirties. About 0.8 out of a million people in their thirties are Congresspeople, compared to 3.69 out of a million people in their sixties.

    Blazina, Carrie, and Drew Desilver. “House gets younger, Senate gets older: A look at the age and generation of lawmakers in the 118th Congress.” Pew Research Center, 30 January 2023, pewresearch.org/short-reads/2023/01/30/house-gets-younger-senate-gets-older-a-look-at-the-age-and-generation-of-lawmakers-in-the-118th-congress/.

    “Age and sex.” American Community Survey 1-year estimates, U.S. Census Bureau, Table S0101, 2023, data.census.gov/table/ACSST5Y2022.S0101?q=people.

  7. The figure for chemistry is taken from the average age people do Nobel Prize-winning work in the field, which is 39.

    Jones, Benjamin F., E. J. Reedy, and Bruce A. Weinberg. “Age and scientific genius.” NBER Working Paper Series, January 2014, nber.org/system/files/working_papers/w19866/w19866.pdf.

    “2024 CEO transitions: The measure of the market.” Spencer Stuart, February 2025, spencerstuart.com/research-and-insight/2024-ceo-transitions.

  8. Ericsson shows that world-class performance, especially at skills like chess, music, or science, usually requires 10–30 years of focused practice. It’s debated whether this level of practice is enough to guarantee expertise, but everyone agrees that it’s usually always necessary for extraordinary abilities. This research is summarised in:
    Peak: Secrets from the New Science of Expertise.

    This said, in rapidly changing, unpredictable fields like disaster response, it’s harder to learn from experience, so practice may be less important. Likewise in brand new fields not much expertise exists, so it’s also faster to get to the forefront. One meta-analysis also found that deliberate practice explains a small amount of performance in professions and education. But Ericsson argues some of this is because few people in these areas engage in deliberate practice, rather than it not being useful.

    Macnamara, Brooke N., et al. “Deliberate practice and performance in music, games, sports, education, and professions: A meta-analysis.” Psychological Science, vol. 25, no. 8, 1 July 2014, pp. 1608–1618, doi.org/10.1177/0956797614535810.

  9. The term originally came from So Good They Can’t Ignore You: Why Skills Trump Passion in the Quest for Work You Love.

  10. These included:

    “Origins of COVID-19: An examination of available evidence.” Committee on Homeland Security & Governmental Affairs, 18 June 2024, hsgac.senate.gov/hearings/origins-of-covid-19-an-examination-of-available-evidence/.

    “Risky research: Oversight of U.S. taxpayer funded high-risk virus research.” Committee on Homeland Security & Governmental Affairs, 11 July 2024, hsgac.senate.gov/hearings/risky-research-oversight-of-u-s-taxpayer-funded-high-risk-virus-research/.

  11. Daniel Ziegler described this path in an interview on our podcast.

    Ziegler has contributed to key research on AI alignment, including work on reinforcement learning from human feedback.

    He has also written about adversarial training for improving AI reliability.
    Ziegler, Daniel M., et al. “Fine-tuning language models from human preferences.” arXiv, 18 September 2019, arxiv.org/abs/1909.08593.

    Ziegler, Daniel M., et al. “Adversarial training for high-stakes reliability.” arXiv, 22 September 2021, arxiv.org/abs/2205.01663.

  12. This pattern of rapidly-increasing output is shown by the studies of income and creative output in the studies covered earlier. For example with income in particular, studies conducted by the U.S. Bureau of Labor Statistics following individuals between 1978 and 2022 found that workers experienced annual earnings growth of approximately 6.5% in ages 18–24, 3.3% in ages 25–34, 1.9% in ages 35–44, and 0.1% in ages 45–54. These patterns vary by education level: workers with bachelor’s degrees see earnings grow 9.2% annually at ages 18–24 versus 2.4% for those without high school diplomas.

    U.S. Bureau of Labor Statistics. “Number of jobs, labor market experience, marital status, and health: Results from a National Longitudinal Survey.” U.S. Bureau of Labor Statistics, News Release USDL-24-1538, August 2024, bls.gov/news.release/nlsoy.nr0.htm.

  13. As discussed in part four, the most effective global health interventions have gradually been taken over time, reflected in a gradual increase in the cost to save a life. This means that efforts to help with global health in 2050 will probably achieve less per year of work (or per dollar) than those in 2030. A similar dynamic likely exists in climate change, too. For example, past efforts to kickstart the solar panel industry were highly effective, much more so than additional investments in solar panels today. In general, we should expect mitigation efforts to focus on the cheapest ways to reduce emissions first, which will make the cost to avoid a tonne of CO2 gradually increase over time.

  14. Talking about a single time horizon is a simplification. A more sophisticated model would take account of how your opportunities for impact could change year-by-year (for instance, declining as opportunities are taken, but maybe increasing as we get closer to crucial turning points). However, you can roughly average these to estimate a single ‘effective’ time horizon (determined mainly by which years you think are more crucial). You may also want to break this down into several scenarios (e.g. AI arrives soon vs. AI arrives later), and then think about how your time horizon would look in each scenario, and take an average of the two.

    The equation can also differ by career path — for instance, communicators and movement builders get compounding returns from their work, creating stronger reasons for urgency; while for something like research into AI alignment, what most matters is how much gets done in total before AGI is created.

  15. Across lifetime earnings, male bachelor’s degree holders earn $900,000 more than high school graduates. For women, the figure is around $630,000. This represents a difference in lifetime earnings of 58% and 79%, respectively. After controlling for socio-demographic factors like family background and high school preparation, these premiums are $655,000 for men and $450,000 for women, representing lifetime earnings increases of 43% and 51% respectively. These controls won’t be perfect, but most researchers in the field agree there’s a significant causal effect of finishing college on earnings (though they disagree about whether it’s from skill acquisition or the signalling benefits of having a degree or the so-called “sheepskin effect”).

    Bryan Caplan argues that simply possessing a degree — regardless of the skills acquired — can significantly boost earnings. Illustrating what he calls the “sheepskin effect,” Caplan shows that the final year of college alone produces a roughly 30% increase in earnings, whereas the first three years combined contribute only about 6% each.

    Caplan, Bryan Douglas. The case against education: Why the education system is a waste of time and money. Princeton University Press, 2019.

    Tamborini, Christopher R., et al. “Education and lifetime earnings in the United States.” Demography, vol. 52, no. 4, 23 June 2015, pp. 1383–1407, doi.org/10.1007/s13524-015-0407-0.