Beware surprising and suspicious convergence

Imagine this:

Oliver: … Thus we see that donating to the opera is the best way of promoting the arts.

Eleanor: Okay, but I’m principally interested in improving human welfare.

Oliver: Oh! Well I think it is also the case that donating to the opera is best for improving human welfare too.

Generally, what is best for one thing is usually not the best for something else, and thus Oliver’s claim that donations to opera are best for the arts and human welfare is surprising. We may suspect bias: that Oliver’s claim that the Opera is best for the human welfare is primarily motivated by his enthusiasm for opera and desire to find reasons in favour, rather than a cooler, more objective search for what is really best for human welfare.

The rest of this essay tries to better establish what is going on (and going wrong) in cases like this. It is in three parts: the first looks at the ‘statistics’ of convergence – in what circumstances is it surprising to find one object judged best by the lights of two different considerations? The second looks more carefully at the claim of bias: how it might be substantiated, and how it should be taken into consideration. The third returns to the example given above, and discusses the prevalence of this sort of error ‘within’ EA, and what can be done to avoid it. Continue reading “Beware surprising and suspicious convergence”

At what cost, carnivory?

Summary: Using Animal Charity Evaluator’s figures, I estimate the amount donated to an effective animal charity to equal the harm caused by a typical American diet compared to veganism. This figure is surprisingly low: $2-5 per year. This suggests that personal dietary change, relative to other things we can do, is fairly ineffective. Yet most EAs interested in animal welfare are eager that others, including other EAs, stop using animal products. I explore a variety of means of resolving this tension, and recommend a large downward adjustment to the efficacy of animal charities is the best solution.[ref]This is a follow-on from an earlier attempt. The more involved discussion of non-consequentialist approaches I owe to comments on fb and the EA forum in general, and to Carl Shulman’s helpful remarks in particular.[/ref] Continue reading “At what cost, carnivory?”

Don’t sweat diet?

Summary: Various people (Hurford, Tomasik) have tried to estimate the typical animal welfare cost of a carnivorous diet. These costs have encouraged EAs to become vegetarians or vegans, and EAs particularly focused on animal welfare advocate that others (including EAs) should reduce their consumption of animal products.

Closely following an estimate by Kaufman, I consider the face value of abstaining from dairy or abstaining from all animal products in terms of donations to ACE-recommended animal welfare charities: <1 cent per year given to The Humane League would offset typical dairy consumption, and <$1 year would offset a typical American’s consumption of all animal products. Thus the emphasis on dietary change intra-EA seems misplaced: it is extraordinarily low impact compared to other means to helping animals.  Continue reading “Don’t sweat diet?”

Log-normal lamentations

[Morose. Also very roughly drafted.]

Normally, things are distributed normally. Human talents may turn out to be one of these things. Some people are lucky enough to find themselves on the right side of these distributions – smarter than average, better at school, more conscientious, whatever. To them go many spoils – probably more so now than at any time before, thanks to the information economy.

There’s a common story told about a hotshot student at school whose ego crashes to earth when they go to university and find themselves among a group all as special as they thought they were. The reality might be worse: many of the groups the smart or studious segregate into (physics professors, Harvard undergraduates, doctors) have threshold (or near threshold)-like effects: only those with straight A’s, only those with IQs > X, etc. need apply. This introduces a positive skew to the population: most (and the median) are below the average, brought up by a long tail of the (even more) exceptional. Instead of comforting ourselves at looking at the entire population to which we compare favorably, most of us will look around our peer group and find ourselves in the middle, and having to look a long way up to the best.[ref]As further bad news, there may be progression of ‘tiers’ which are progressively more selective, somewhat akin to stacked band-pass filters: even if you were the best maths student at your school, then the best at university, you may still find yourself plonked around median in a positive-skewed population of maths professors – and if you were an exceptional maths professor, you might find yourself plonked around median in the population of fields medalists. And so on (especially – see infra – if the underlying distribution is something scale-free).[/ref]

normal

Yet part of growing up is recognizing there will inevitably be people better than you are – the more able may be able to buy their egos time, but no more. But that needn’t be so bad: in several fields (such as medicine) it can be genuinely hard to judge ‘betterness’, and so harder to find exemplars to illuminate your relative mediocrity. Often there are a variety of dimensions to being ‘better’ at something: although I don’t need to try too hard to find doctors who are better at some aspect of medicine than I (more knowledgeable, kinder, more skilled in communication etc.) it is mercifully rare to find doctors who are better than me in all respects. And often the tails are thin: if you’re around 1 standard deviation above the mean, people many times further from the average than you are will still be extraordinarily rare, even if you had a good stick to compare them to yourself.

Look at our thick-tailed works, ye average, and despair![ref]I wonder how much this post is a monument to the grasping vaingloriousness of my character…[/ref]

Continue reading “Log-normal lamentations”

Funding cannibalism motivates concern for overheads

Summary: Overhead expenses’ (CEO salary, percentage spent on fundraising) are often deemed a poor measure of charity effectiveness by Effective Altruists, and so they disprefer means of charity evaluation which rely on these. However, ‘funding cannibalism’ suggests that these metrics (and the norms that engender them) have value: if fundraising is broadly a zero-sum game between charities, then there’s a commons problem where all charities could spend less money on fundraising and all do more good, but each is locally incentivized to spend more. Donor norms against increasing spending on zero-sum ‘overheads’ might be a good way of combating this. This valuable collective action of donors may explain the apparent underutilization of fundraising by charities, and perhaps should make us cautious in undermining it.

Continue reading “Funding cannibalism motivates concern for overheads”

Saving the World, and Healing the Sick

When I applied to medical school, I had to write a personal statement: selling how exceptional my achievements were, what wonderful personal qualities I had, and my noble motivations for wanting to be a doctor. The last of these is the most embarrassing in retrospect:

I want to study medicine because of a desire I have to help others, and so the chance of spending a career doing something worthwhile I cannot resist. Of course, Doctors [sic] don’t have a monopoly on altruism, but I believe the attributes I have lend themselves best to medicine, as opposed to all the work I could do instead.

These “I like science and I want to help people” sentiments are common in budding doctors: when I recite this bit of my personal statement in a talk (generally as a self-flagellating opening gambit) I get a mix of laughs and groans of recognition – most wrote something similar. The impression I get from those who have to read this juvenalia is the “I like science and I want to help people” wannabe doctor is regarded akin to a child zooming around on their bike with stabilizers – an endearing work in progress. As they became seasoned in the blood sweat and tears of clinical practice, the vainglorious naivete will transform into a more grizzled, realistic, humane compassion. Less dying nobly, more living humbly; less JD, and more Perry Cox.

I still have a long way to go. Continue reading “Saving the World, and Healing the Sick”

How far can hard work take us?

There’s a perennial question about how much achievement something depends on talent, and how much on hard work. Perhaps genius (or even garden variety exceptional performance) is written into someone’s genes, or perhaps what separated Einstein from his peers had more to do with his work ethic than his IQ.

Evidence points in both directions. On the one hand, most high performers, whatever their field, emphasize how important hard work – rather than ‘just talent’ – is to their achievements (e.g. Terrence TaoWill Smith, Ira Glass, Thomas Edison). Some, like Malcolm Gladwell, talk about a ‘10000 hour rule‘ as the required hard work before one can truly excel. Perhaps the main proponent of the ‘Arbeit uber alles’ approach is Erikson’s work on deliberate practice. On the other hand, there are lots of instances where innate physical or mental characteristics play an important role: the average height of NBA players is 6’7″, Intelligence (albeit imperfectly measured by IQ) seems to predict lots of things (including various intellectual achievements) – and it appears to remain predictive even into the very high range.

So perhaps it is a mix. But the precise mechanism of the mix could be important; how do innate talents and amount of training relate to one another when it comes to achievement? Could some maths help?

A Growth-mindset model

Here’s one suggestion, implied by Uri Baum:

Performance = Talent + Practice intensity x Time practising[ref]Perhaps even better would be to use a time integral here, as likely practice intensity will vary over time. But multiplication is simpler, and simplicity is better than precision for toy models.[/ref]

On this sort of model, talent counts, but as time passes, practice matters more. Unlike talent – a static given – one can grow a stock of practice over time, and time invested in practice and hard work has a rich return on performance (c.f. Hamming’s remarks). An attractive corollary is that if one can improve one’s practice intensity, be that through more focused training, deliberate practice, better learning styles, etc. this acts as a multiplier – working smarter, as well as working harder may be a stronger determinant of success than talent.

If so, extraordinary talent may be a curse – it could let us coast. Bram suggests there might be a mechanism where if we select for exceptional achievement, we select for people with varying mixes of raw talent and hard work. The group which skew more towards the latter may overtake those skewing to the former former over time: those who skew towards more practice time and intensity will be able to grow faster, whilst those who mainly got to where they were ‘just’ on their talent may find they are hitting a wall unless they can improve how they develop. Continue reading “How far can hard work take us?”