Lehua closed down her fundraising startup after reading our blog: plan change story


Learning about ‘counterfactual analysis’ threw some puts on sunglasses cold water on Lehua’s startup idea.

Lehua Gray’s story is an interesting ‘significant plan change’ because she increased her social impact simply by realising what she was doing was not accomplishing anything when the true counterfactual was taken into account.

Lehua is an entrepreneur in Texas who studied environmental sciences but afterwards taught herself coding. In late 2014, along with two co-founders she had just met at the eBay Hackathon, she founded a company that offered charities an innovative fundraising platform and took a cut of the money raised. Her role in the startup was a combination of coding, UX and sales.

The team’s hope was to make the viral nature of the ‘ice-bucket challenge’ replicable. In their platform, someone would donate money to a charity, but it would only actually be delivered if, say, 3 friends who they nominated matched their donation. They might also be offered the option to do a public challenge on social media that would spread the fundraiser instead of donating the full amount, as in the ‘ice-bucket challenge’.

Over a period of 9 months they had built this platform and were improving it while some charities tested it out.

However, in the first half of 2015 Lehua started following me on Facebook and so started regularly encountering and reading new 80,000 Hours’ blog posts about how to have more social impact.

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Stop assuming ‘declining returns’ in small charities

Amazon is one of the world’s largest companies and is still achieving lower marginal costs as it gets larger. Organisations with just a few people will frequently do much better as they get larger.

We often hear people in our community state, as if obvious, that becoming the 5th employee of an organisation creates less impact than becoming the 4th employee. Similarly, later donations are thought to create less impact than earlier donations. This sentiment was widespread in recent discussion about whether to donate to Giving What We Can, discussions on the EA forum about where to donate, and in discussions I’ve had with people about where to work.

The reason stated is “diminishing marginal returns”. The first staff members take the best opportunities, so the extra opportunities available at the margin are worse, so each extra staff member has less impact.

The problem is, assuming diminishing returns to small organisations contradicts basic economic theory.

According to economics, as an organisation scales up, there’s two opposing forces:

  1. Economies of scale.
  2. Diminishing returns.

Economies of scale are a force for increasing returns, and they win out while still at a small scale, so the impact of the 5th staff member can easily be greater than the 4th.

Economies of scale are caused by:

  1. Gains from specialisation. In a one person organisation,

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‘Replaceability’ isn’t as important as you might think (or we’ve suggested)

Often if you turn down a skilled job, the role simply won’t be filled at all because there’s no suitable substitute available. For this and other reasons we don’t place as much weight as we used to on the idea of ‘replaceability’.

When we started 80,000 Hours, one of the key ideas we presented was the replaceability argument:

Suppose you become a surgeon and perform 100 life saving operations. Naively it seems like your impact is to save 100 people’s lives. If you hadn’t taken the job, however, someone else likely would have taken it instead. So your true (counterfactual) impact is less than the good you do directly.

I still think this is a good argument, but I’m not sure how relevant it is when comparing real career options.

In particular, I see the argument often being used incorrectly in the following two ways:

  1. Ignoring direct harm: Suppose you’re considering taking a job that some people think is harmful (e.g. certain parts of the financial sector) in order to donate, do advocacy or build skills. You reason “if I don’t take the job, someone else will instead, so the potential harm I’ll do directly doesn’t matter”.

  2. Ignoring direct impact: Suppose you’re considering working at a high-impact nonprofit. You reason “if I don’t take the job, someone else will instead, so I won’t have much impact.”

I disagree with both of these claims in most circumstances. Why?

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What does economics tell us about replaceability?


‘Replaceability’ has become a core concept in discussions of career choice among Effective Altruists (EAs) – put simply, people should not simply consider the ‘direct impact’ from doing a job, but instead the difference in outcomes resulting from taking that job, relative to not taking it. Ben Todd and Seb Farquhar have both written blogs introducing this concept, and the importance of counterfactual reasoning in general (read these first if you’re not familiar with replaceability!); Paul Christiano and Ben Kuhn (among others) have written blogs further exploring the concept, and its various representations and applications. Some Effective Altruists (EAs) have noted that representations of replaceability have varied in their sophistication, and Will MacAskill summarises this nicely as the ‘simple view’, ‘simplistic replaceability’ and ‘correct replaceability’.

‘Correct replaceability’ is particularly nuanced and complicated, and comprises taking into account the full set of counterfactual outcomes not only in your (potential) job, but in any other jobs affected by the employment decision, through knock-on and labour market effects. Given this, and that ‘replaceability’ varies significantly across different industries and jobs, Will MacAskill and Ben Todd asked me to think about what Economics has to tell us about the concept. For clarity, rather than think about the ethical considerations of ‘replaceability’ as a whole, they asked me to answer a sub-question, namely: “according to mainstream economics, if I add myself to the labour pool for job type X (being a doctor, or an aid worker, or a banker), then how many more type X jobs come into being (on average)?”. Although these issues have been discussed before, this blog post is a first attempt at providing a thorough analysis of this question.


  • I set out the classical, Econ 101 supply and demand model and discuss the assumptions it makes. I argue that this is a useful framework for considering our question, then show how the answer depends crucially on the elasticities of labour supply and demand. Unfortunately, empirical economic research cannot tell us much about these elasticities for individual industries.

  • There is no ‘one-size-fits-all’ answer to our question – it will vary considerably across different industries and we must try to understand how each industry functions in order to make an informed estimate.
    I believe that the supply and demand framework, or some variant of it, is useful for analysing our question for most jobs and industries, particularly those that are not highly specialised.

  • I discuss how (and whether) this framework should be applied in a few industries, most of which are seen as viable EA career paths. This framework can lead us to some (tentative) conclusions:

    • Entrance into industries with a quantity restriction (e.g. through a limited number of occupational licences) is likely to have (close to) zero impact on the number of jobs in that industry. This may apply to medical school and licensed professional industries (e.g. becoming a barrister in the UK).
    • Entrance into (narrowly defined) industries which require relatively transferable skills is likely to result in less than 0.5 additional jobs in this industry, as (potential) workers can easily substitute into other industries (labour supply is elastic). This may apply to banking and consultancy.
    • Entrance into industries in which (potential) workers have a strong preference to work is likely to result in more additional jobs (perhaps between 0.5 and 1), as workers will not substitute into other industries at such a high rate (labour supply is inelastic). This may apply to jobs in the charity sector.
    • In highly specialised industries/jobs, applying this framework may not be appropriate, as the hiring process will not resemble a competitive market. This may apply, for example, to taking a job with Givewell, who likely follow a process more akin to ‘threshold hiring’.In this case, it seems likely that taking this job may increase the number of overall jobs by close to 1.
  • This post only discusses one aspect of replaceability, and does not consider other issues related to the (direct) impact of a job, effects on the quality of employees, or long term effects of a job, such as creating social value.

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The replaceability effect: working in unethical industries part 1

High earning careers are often perceived as unethical careers. It’s not just that people think earning lots of money is bad, it’s also that a lot of the careers that make you really rich involve things that also seem immoral… This article will look at something called the replaceability effect. It’s the idea that, often, if you don’t take a job, someone else will take it. For some types of jobs, this is a very safe assumption, and it makes the harm you do by taking a job in an unethical industry much smaller than you might first guess.

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Just what is making a difference: counterfactuals and career choice

When we think about how to make a difference in our careers, it is natural to think about what we can do directly. We think about the children we could build schools for, the homeless person we could help, what campaigns we might take part in, and so on.

But what we do directly is not the only thing that matters. We also need to think about what would have happened if we hadn’t acted – which is called a counterfactual…

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