This article agrees somewhat with my pet model of the relationship between intelligence and achievement. That is, (assuming you pass a certain threshold; you aren’t going to be a particle physicist with an 85 IQ) natural talent is only the dominating predictor of performance twice: when you don’t have that much practice at something and when you’re bumping up against the current limits of what can be done (e.g. when you’re late in your chess career or have seen all the gains from practice you can).
Obviously intelligence matters when you’re starting out in a field: if you can learn things more quickly and more completely than the next person, you’ll have a head start that can’t be beat with raw practice. It’s similarly self-evident that it’s necessary when you’re close to the “end” of your field: it’s /hard/ to push boundaries and do things no one has before. Mark Kac’s quote about “magical geniuses” comes to mind.
I think people spend a lot of time in the early stages of a field (I graduated with a math major and I’m still just starting out in math!) and I feel like this tends to bias people towards saying that intelligence is a dominating factor for performance over a lifetime. However, I think this neglects the fact that 99% of a given field lies somewhere between the absolute beginning and the absolute cutting edge.
This is something I’ve noticed: nearly all the high achievers I know are reasonably intelligent people who are crazy passionate. I knew people in my friend group at college who went on to get {Masters,PhDs} at {Stanford,MIT} and out of all 4 of them only one was exceptionally smart IMO (over 1/1000 rarity).
This also leads me to the conclusion that most people you see who seem crazy smart are probably a fairly normal level of smart with effort added to taste. The argument for this isn’t ideological - it’s statistical. There are simply so many more above-average people than there are exceptional people that most of the really high (but not world class) performers come from the former group.
This describes my experience perfectly. I feel like when people discuss aphantasia online, the word "seeing" gets overloaded to both refer to the act of picking up visual stimuli through the optic nerve, as well as a conceptualization action. When I "see" things in my mind's eye, I'm referring exclusively to the latter, and I think most people with normal visualization abilities do the same.
Due to the confusion of language as well as the testimonies of some rare people with incredibly vivid mental images that are on par with actual physical sight, I thought I might have aphantasia for a period of time, but after reading up on it, I feel like aphantasia is a much stronger condition than most people on the internet think it is. "Just seeing black" when you try to visualize something isn't enough - it seems like that's just a sign of being a person with a fairly typical brain who's using the word "see" in its literal sense.
For example, in the star test (https://www.reddit.com/r/Aphantasia/comments/aioyga/simple_a...), if I was a person who understood "see" in the first sense, I'd say that I was a 1. If I instead switch to using the second sense of the word, I'd easily be a 6.
It feels like any test that asks you to rate the vividness of the item you "see" in your mind's eye will fall prey to this problem. I saw a comment on HN where the commenter suggested asking someone to visualize an elephant in profile, and then ask them which way the trunk is facing to see if they're aphantasic or not. I'd also suggest that if you ever imagined a person running beside your car while you were taking a road trip as a child, you also probably don't have aphantasia.
I feel similarly; the author mentions spending ten minutes trying to solve one of these puzzles, and I can’t imagine doing that and enjoying it. Maybe it’s the case that spending more time on the ones that stumped me would yield fruit, but I have the impression that on this class of problem, if I don’t see the solution within two minutes then I probably won’t be able to figure it out in ten, which disincentivizes investing time in them. I’d be interested in knowing if the people who /can/ solve all the problems in the article do so by investing time in them and being methodical or if they just “see it” eventually, which is how I feel solving the easier ones.
There’s also the factor that some Bongard problems, independent of their difficulty factor, are just more satisfying than others. Spoiler for the fourth one, with pairs of circles: its solution is that the entries on the left have $property while the ones on the right...don’t. This makes the right side virtually useless except to check the rule that you derived from the left side.
Maybe it’s just that I don’t have research experience, and am thus unsteeled against problems that seem impenetrable, or maybe I just don’t have the mindset to be good at these, but I agree the really difficult ones can be frustrating.
I’m always a bit disappointed that people making the case for mouse-lite workflows stop at “it makes you faster.” In many cases, this is patently false at a global scale - I’ve been using Emacs for a month and I’m certain that I’ve already spent way more hours customizing and researching than I’ll ever make back from saving a couple deciseconds every time I use a keyboard shortcut instead of a mouse.
For me, using Vim keybindings and Emacs shortcuts is valuable because reaching for a mouse or navigating menus adds mental overhead. I view the moment-to-moment practice of programming as largely being an exercise in working memory. You’re trying to hold an abstraction in your head and implement it in an existing codebase that’s filled with other abstractions and interacting parts. Personally, removing a mouse from my workflow does wonders for ensuring that all my mental resources are dedicated to the task at hand. Going mouse-lite might save a trivial amount of time in the moment, but (for me) it makes programming more seamless and natural - which makes it not only more fun, but more productive.
A nitpick orthogonal to your main point, but I would argue anecdotally that there's no way elite schools have an average undergraduate IQ "multiple standard deviations" above the mean - unless by multiple, you mean "two". Any integer over that, and at 4,000,000 students graduating high school a year, and 3sigma working out to ~1/1000, there literally wouldn't be enough smart kids to go around, especially considering a majority of those students probably don't go to T10 schools anyways due to the fact that college isn't an idealized market.
Having gone to an elite school for undergrad, I'd argue most students were around 2sigma or slightly below, but almost universally also had 2sigma levels of work ethic, self-discipline, and goal-seeking.
The above argument might feel slightly wrong to people because it relies on the property that (g^a mod p) ^ b mod p == (g^ab mod p). The fact that this holds isn't too hard to figure out, but requires knowledge that pq mod r == ((p mod r) * (q mod r)) mod r, which again isn't too hard to figure out. However, at this point you're asking people to derive two basic number theory properties in a row, and notably "using modulus to write fizz buzz" (which is the level most non-math-major programmers are at wrt to modulus) is not the same thing as knowing how to do basic number theory, and proficiency in the former doesn't imply proficiency in the latter.
This is true, and another reason why I have problems with my "generous" take. However, I'd also suggest that the notion of a friction factor applies to new media as well: if Twitter makes it difficult to be casually racist on their platform, but there still exist sites which allow you to be casually racist, it spares the average individual from having their mental namespace polluted with those "virulent ideas" without eliminating free speech entirely. Whether this is a positive thing, or even an acceptable course of action is something I'm very dubious of, however.
This is all just my initial take on the topic though: I always have difficulty engaging with stuff like this and forming opinions constructively since it's just an exhausting concept to try to be productive with people on.
edit: I realize now that I misunderstood your point: I thought you were saying "new media can have a radicalizing effect" to which this comment was responding to by saying "light regulation works for new media as well". I now understand you said that "old media doesn't radicalize a significant number of people" which has the obvious endpoint "light regulation of old media isn't necessary". On balance, I definitely agree with that.
I always have trouble with stuff like this, because my inner teenage hacker is cheering that "information wants to be free!" while at the same time I'm cognizant of the fact that we have to treat information with a certain level of care.
Here's a take I don't necessarily believe, but is about as generous to the new left as I can make it: Ideas can be powerfully virulent, and we're especially susceptible to them when they support something we already suspect (confirmation bias). Under complete deregulation, people seek out information that confirms their biases, and our societal inertia continues unrestricted. The naive solution to me is something like we have now: introduce a friction factor. People are generally lazy, and if they don't have immediate access to something, they won't seek it out. If we make problematic media difficult to find but nevertheless available, we change the general cultural milieu without outright banning difficult texts.
This obviously falls apart when it comes to introducing new texts and ideas into the mainstream - if people are disincentivized to print anything that isn't playing by the rules, it's terrible for innovation and creates a whole new brand of inertia. It's also terrible in that it's an unstable equilibrium: if people care enough to keep their foot on the gas in terms of narrowing access to virulent media, it doesn't take much to convince them to go pedal-to-the-metal and start banning everything.
Obviously intelligence matters when you’re starting out in a field: if you can learn things more quickly and more completely than the next person, you’ll have a head start that can’t be beat with raw practice. It’s similarly self-evident that it’s necessary when you’re close to the “end” of your field: it’s /hard/ to push boundaries and do things no one has before. Mark Kac’s quote about “magical geniuses” comes to mind.
I think people spend a lot of time in the early stages of a field (I graduated with a math major and I’m still just starting out in math!) and I feel like this tends to bias people towards saying that intelligence is a dominating factor for performance over a lifetime. However, I think this neglects the fact that 99% of a given field lies somewhere between the absolute beginning and the absolute cutting edge.
This is something I’ve noticed: nearly all the high achievers I know are reasonably intelligent people who are crazy passionate. I knew people in my friend group at college who went on to get {Masters,PhDs} at {Stanford,MIT} and out of all 4 of them only one was exceptionally smart IMO (over 1/1000 rarity).
This also leads me to the conclusion that most people you see who seem crazy smart are probably a fairly normal level of smart with effort added to taste. The argument for this isn’t ideological - it’s statistical. There are simply so many more above-average people than there are exceptional people that most of the really high (but not world class) performers come from the former group.