Possibly as a result of the math education discussion I talked about yesterday, there’s been a weird surge of tweets from Fields-Medal-caliber mathematicians insisting that absolutely anyone can learn absolutely anything in math, followed by other people commenting on the mild irony of that. Well, OK, maybe not that many tweets, but like the joke goes, it’s only two nickels but it’s weird that it happened twice.
Somewhere in there, this tweet with a quote from Yoichiro Nambu came across my feed, and I did my usual like-and-retweet thing to flag it to comment on later, then basically forgot. Some person helpfully liked the RT this morning, bringing it back to my attention. I’ll do the screenshot thing because the owner of Twitter is a petulant child:
I find this amusing in the context of the math thing because it’s a very compact example of a phenomenon that I see a lot: people averring that “talent” is the determining factor for success in fields they’re not good at, but that their own area is fully accessible to everyone. If anything, Nambu’s version is milder than a lot of the modern variants, because he acknowledges some role for talent in physics, but that it takes different forms. Nowadays, even that mild concession to the idea that “talent” exists might be angrily denounced as an expression of some problematic -ism (largely depending on who the speaker is).
This tendency comes from a good place— assertions about talent and who can have it have been the basis for some very ugly gatekeeping in the past, and still linger in a lot of places. Like pretty much everything else that falls into the swamp of hyperpolarized social media, though, it gets taken to some weird extremes. The entire idea of talent, like its cousin “merit,” gets denounced as a wholly artificial construct, something that was invented by creepy racists for evil ends.
Of course, when push comes to shove, most people pretty clearly believe in both talent and merit. Most of the academics who are loudly insistent that it’s essentially impossible to measure individual merit are not accepting thesis students on a first-come, first-served basis, but have some criteria for selecting only “the best” of those who express interest. (Many of them also tend to be absolutely convinced that whatever they publish is higher quality and more important than whatever their colleagues do. They’re fun at parties.) And a lot of people who publicly proclaim that it’s problematic to suggest that some individuals are better at certain things than others are quick to fall back on variants of “Not a Math Person” to excuse their own innumeracy, or argue that it’s not really important for students in their field to be expected to learn algebra. (And on the flip side, there’s no shortage of scientists who will declare that arts requirements are a waste of time for their students.)
(It occurs to me as I’m typing that there’s a kind of interesting mirror-image relationship between talent and merit in what I’m talking about above. Merit is an illusion everywhere except in our personal area of expertise, talent is a thing that exists only for fields outside our personal area of expertise. I’m not sure how well that holds up, though, so I’ll leave this as a parenthetical…)
I’m a career academic, so I’m by no means immune to this not-entirely-consistent quirk of discourse. I very definitely have strong opinions about the relative quality of things produced by other people, and many of the negative assessments take the form of thinking “Wow, you’re not good at this.” I may even have more of those opinions than some of my colleagues, since I have Thoughts about the quality of both technical output and written communication. At the same time, though, I would be very uncomfortable declaring that these differences are entirely down to innate inborn abilities. I’m fine with saying that so-and-so is a terrible writer, but would balk at saying that so-and-so is incapable of being a good writer.
My personal attempt to square this circle, which I made in Eureka (and which you can find excerpted here) is to try separate out ability and inclination. I would agree that, outside of a tiny number of people with genuine disabilities, essentially everyone can do basically anything in the realm of human activities: math, science, music, literary theory. The biggest determinant of the differences of achievement in these areas is usually a matter of personal taste and inclination: whether you enjoy doing the things you need to do to excel in a particular area.
That is, I’m considerably better at math than the average person not because I have that much more innate talent for the subject, but because I happen to find the things you need to do to be good at math congenial, and as a result spend more time doing them. That practice lets me manipulate algebraic equations with a degree of ease that some people find off-putting, but it’s just a matter of having done it a lot. Inclination to enjoy a thing builds ability to do it well.
At the same time, I’m nowhere near good enough at math to be a theoretical physicist, let alone a professional mathematician, because I don’t enjoy it that much. I find relatively basic activities congenial, but there’s a point beyond which the work just doesn’t seem worth the reward. To me, but not to someone who enjoys that sort of thing more than I do. I’m not incapable of doing what they do— I can generally work my way through whatever operations appear in a theory paper in a field where I know the basic concepts and notation, but it’s a laborious process, and not a thing I normally choose to do.
This puts me more or less in line with this very economist-y take on the whole math discussion:
(The same guy has a short thread that’s probably the best thing to come out of the whole silly argument.) It’s not “hitting a wall” of innate ability, it’s a slow process of returns diminishing until you say “This isn’t worth the effort any more. I’m out.”
There’s still some innate element to this— the inclinations that amplify abilities aren’t consciously chosen— but I prefer this formulation because it shifts the source of differences in achievement into de gustibus territory. And, you know, non est disputandum.
This is not a hugely successful line, though— that book didn’t sell for shit— probably because it doesn’t really admit grand declarative statements. I find some of the pushback it gets kind of baffling, though: a surprising number of highly educated professionals who are adamant that talent and merit are neoliberal myths are also weirdly invested in the idea that Math Is Different and they shouldn’t be expected to engage with it, ever. I can’t entirely get my head around the psychology of that position.
Which kind of comes back around to the Nambu quote I started with, and the notion that talent is a thing that determines success only in fields that other people are successful in. And that’s as good a stopping point as anything else I’m going to come up with this morning.
If you like this kind of thing, you should 100% buy my book, but if the reward doesn’t seem worth the effort, you could settle for clicking this button:
And if you want to dispute anyone’s gustibus, the comments will be open:
Couple more basic problems to throw into the mix.
1) All it takes in some cases is someone with authority, usually a teacher, telling you that you are bad at something to lock that in, especially early in life, when *everything* is potentially hard to learn. You may not even remember consciously that someone said it but something in you remembers.
2) All it takes in some cases is someone explaining/teaching an important or critical point or skill badly, or introduced an area of study that is misaligned with the rest of what you're studying. I remember in 5th grade math we took a violent, wrenching turn into learning base-16 math that the teacher was wholly unequipped to explain--he would just shrug and say "it's for computers, they say"--that was then not followed up on in 6th grade math and I remember feeling utterly bewildered by it.
3) All knowledge has path dependency. We love to imply that with talent OR effort, you can do anything, but both discourses are covering the fact that at some point it's just too late to make up lost ground in all sorts of things (not just STEM). I think that's what we mean by a "wall" sometimes: a recognition that even if we wanted to do something because we now understand how it works and why it's valuable, it's too late a fair amount of the time.
I studied theoretical physics, even started PhD work, but I quickly found that at the Scientific American level it was fascinating and hence easy but at the PhD level it was boring and hence hard. While computer science was more fun than any hobby and hence easy, and it remained so as I burrowed for 45 years. Therefore, “anybody can learn computer science”.