10x programmers etc.

[ajschumacher]

see also: #92 debunked "double hump"

---

in https://www.nature.com/news/how-to-raise-a-genius-lessons-from-a-45-year-study-of-super-smart-children-1.20537:

what has become clear is how much the precociously gifted outweigh the rest of society in their influence.

“Whether we like it or not, these people really do control our society,” says Jonathan Wai, a psychologist at the Duke University Talent Identification Program in Durham, North Carolina, which collaborates with the Hopkins centre.

Some researchers and writers, notably psychologist Anders Ericsson at Florida State University in Tallahassee and author Malcolm Gladwell, have popularized the idea of an ability threshold. This holds that for individuals beyond a certain IQ barrier (120 is often cited), concentrated practice time is much more important than additional intellectual abilities in acquiring expertise.

[ajschumacher]

In The Tyranny of Metrics, page 100, on giving attention to closing achievement gaps:

And resources are diverted away from maximizing learning on the part of the more gifted and talented—who may in fact hold the key to national economic performance.

(that cites the above Nature article, which mentions declining attention on G&T in Europe

[ajschumacher]

In The Tyranny of Metrics, pages 72-73:

One assumption that lies behind the effort to boost levels of college enrollment and completion is that increases in average educational attainment somehow translate into higher levels of national economic growth. But some distinguished economists on both sides of the Atlantic—Alison Wolf in England, and Daron Acemoglu and David Autor in the United States—have concluded that that is no longer the case, if it ever was. In an age in which technology is replacing many tasks previously performed by those with low to moderate levels of human capital, national economic growth based on innovation and technological progress depends not so much on the average level of educational attainment as on the attainment of those at the top of the distribution fo knowledge, ability and skill.

That cites:

• Does Education Matter (2003 book by Wolf) https://www.amazon.com/Does-Education-Matter-Economic-Business/dp/0140286608
• What Does Human Capital Do? (Acemoglu & Autor) https://www.nber.org/papers/w17820

Does the developing technology matter? I guess it's saying: Pushing more people up to low/moderate levels doesn't matter because we don't need people at that level anyway?

The book continues:

In recent decades, the percentage of the population with a college degree has gone up, while the rate of economic growth has declined. And though the gap between the earnings of those with and without a college diploma remains substantial, the falling rate of earnings for college graduates seems to indicate that the economy already has an oversupply of graduates.

That cites:

• Wolf chapters 2 and 6
• The Great Reversal in the Demand for Skill and Cognitive Tasks https://www.nber.org/papers/w18901 This paper seems a bit dated, talking about unemployment that was high then, but we now know that unemployment went down down down in subsequent years (until COVID-19). But they're not necessarily wrong; it does seem like a lot of people are educated beyond the real requirements of their jobs.

The book's paragraph ends by lamenting a shortage of workers in the skilled trades.

[ajschumacher]

On low-side:

“The average software developer, for example, doesn’t own a single book on the subject of his or her work, and hasn’t ever read one.” (Peopleware, page 11)

Yegge on programmers who can't type: http://steve-yegge.blogspot.com/2008/09/programmings-dirtiest-little-secret.html This still seems crazy, but I'm reminded that at BAH I worked with someone who couldn't touch type (in 2013, I think?).

[ajschumacher]

Peoplesoft pages 44-48 "Individual Differences" etc. includes their study results, and quotes:

While this [10 to 1] productivity differential among programmers is understandable, there is also a 10 to 1 difference in productivity among software organizations. (Harlan Mills, Software Productivity, 1981/1988)

The Peoplesoft folks find that variability of individuals is mostly between organizations, with individuals at the same org tending to be more alike.

[ajschumacher]

“The final outcome of any effort is more a function of who does the work than of how the work is done.” (Peoplesoft, page 91)

[ajschumacher]

F. Scott Fitzgerald, on "vitality", in The Crack-Up (https://classic.esquire.com/article/1936/2/1/the-crack-up)

I felt a certain reaction to what she said, but I am a slow-thinking man, and it occurred to me simultaneously that of all natural forces, vitality is the incommunicable one. In days when juice came into one as an article without duty, one tried to distribute it—but always without success; to further mix metaphors, vitality never “takes.” You have it or you haven’t it, like health or brown eyes or honor or a baritone voice. I might have asked some of it from her, neatly wrapped and ready for home cooking and digestion, but I could never have got it—not if I’d waited around for a thousand hours with the tin cup of self pity.

[ajschumacher]

Richard Hamming on ``Why do so few scientists make significant contributions and so many are forgotten in the long run?'' https://www.cs.virginia.edu/~robins/YouAndYourResearch.html (ref from https://planspace.org/20151118-debugging_teams/ originally)

What Bode was saying was this: ``Knowledge and productivity are like compound interest.''

The steady application of effort with a little bit more work, intelligently applied is what does it. That's the trouble; drive, misapplied, doesn't get you anywhere.

If you do not work on an important problem, it's unlikely you'll do important work.

Goes through several factors (luck, brains, courage, working conditions, drive, ambiguity, emotional commitment) and doesn't come down on just one central focus but emphasizes the importance of courage, drive, allowing ambiguity, emotional commitment, and choosing to work on something that could be important.

[ajschumacher]

Howard Stern recently interviewed Jerry Sienfeld on the Howard Stern show. This bit caught my attention. Stern was talking about how hard he worked everyday to make a living in radio and then said:

Howard Stern: "I thought (to myself), you know, it is possible to will yourself, maybe not to be the greatest in the world but to certainly get what you want."

Jerry Sienfeld: "I'm going to adjust your perspective a little bit. That was no will. What you were using, what Michael Jordan uses and what I use, is not will. It's love. When you love something, it's a bottomless pool of energy. That's where the energy comes from. But you have to love it sincerely. Not because you're going to make money from it, be famous, or get whatever you want to get. When you do it because you love it, then you can find yourself moving up and getting really good at something you wanted to be really good at. Will is like not eating dessert or something that's just forcing yourself. You can't force yourself to be what you have made yourself into. You can love it. Love is endless. Will is finite."

https://twitter.com/BrendanFitzTV/status/1263998531188035584

via (including transcription above) Farnam Street's "Brain Food No. 371: The upside of stress, how to be great, and 3 types of listening"

I think this is really interesting and speaks to differences in motivation and thinking between people. The difference between "I want to be great at piano" and "I want to play piano all day every day" - it's about the difference between process and product.

[ajschumacher]

Hamming also talks about coding as being like writing, and then I saw this quote in here:

https://evrone.com/dhh-interview

Evrone: You have seen lots of Ruby code for sure. In your personal opinion, what makes code good or shitty? Anything that is obvious for you at first glance?

David: If the code is poorly written, usually it smells before you even examine the logic. Indentation is off, styles are mixed, care is simply not shown. Beyond that, learning how to write great code, is a life long pursuit. As I said in my RailsConf 2014 keynote, we're not software engineers, we’re software writers. “Writing” is a much more suitable metaphor for what we do most of the time than “engineering” is. Writing is about clarity and presenting information in a clear-to-follow manner so that anybody can understand it.

There's no list of principles and practices that somebody can be taught and then they will automatically produce clear writing every time. If you want to be a good writer, it’s not enough just to memorize the dictionary. Just knowing the words available to you, knowing the patterns of development is not going to make you a good developer. You have to develop an eye. You have to decide that the most important thing for your system is clarity. When you do decide that, you can start developing an eye.

The only way to become a good programmer, where, by definition, I define good programmers as somebody who writes software with clarity, is to read a lot of software and write a lot of software.

[ajschumacher]

de Bono in Lateral Thinking: Creativity Step by Step (page 47):

To regard insight and innovation as a matter of chance does not explain why some people are consistently able to generate more ideas than others.

He isn't saying this is due to the people themselves, though. His whole thing is that these skills can be taught; there are techniques that anyone can use.

[ajschumacher]

adding old notes from #124...

---

from Paul Graham, http://www.paulgraham.com/gh.html

A great programmer might be ten or a hundred times as productive as an ordinary one

from David Deutsch, https://aeon.co/essays/how-close-are-we-to-creating-artificial-intelligence:

It has always been the case that a single exceptionally creative person can be thousands of times as productive — economically, intellectually or whatever — as most people

elitist, yes, okay... but?

connection to IQ? (cf Flynn)

connection to privilege/position? (ability to have others do work for you, etc.)

---

"Programmer Moneyball: Challenging the Myth of Individual Programmer Productivity" https://insights.sei.cmu.edu/sei_blog/2020/01/programmer-moneyball-challenging-the-myth-of-individual-programmer-productivity.html

"The real world, of course, is far more complex than the limited, controlled study that we conducted." but an interesting contribution to this topic, I think.

[ajschumacher]

I place my bets more often on high motivation than on any other quality except judgment. There is no perfection of techniques that will substitute for the lift of spirit and heightened performance that comes from strong motivation, The world is moved by highly motivated people, by enthusiasts, by men and women who want something very much or believe very much.

https://fs.blog/great-talks/personal-renewal-john-gardner/ original: http://www.pbs.org/johngardner/sections/writings_speech_1.html

[ajschumacher]

Hamming in The Art of Doing Science and Engineering:

"You read constantly about "engineering the production of software," both for the efficiency of production and for the reliability of the product. But you do not expect novelists to "engineer the production of novels." The question arises: "Is programming closer to novel writing than it is to classical engineering?" I suggest yes! Given the problem of getting a man into outer space, both the Russians and the Americans did it pretty much the same way, all things considered, and allowing for some espionage. They were both limited by the same firm laws of physics. But give two novelists the problem of writing on "the greatness and misery of man," and you will probably get two very different novels (without saying just how to measure this). Give the same complex problem to two modern programmers and you will, I claim, get two rather different programs. Hence my belief that current programming practice is closer to novel writing than it is to engineering. The novelists are bound only by their imaginations, which is somewhat as the programmers are when they are writing software. Both activities have a large creative component, and while you would like to make programming resemble engineering, it will take a lot of time to get there—and maybe you really, in the long run, do not want to do it! Maybe it just sounds good. You will have to think about it many times in the coming years; you might as well start now and discount propaganda you hear, as well as all the wishful thinking which goes on in the area! The software of the utility programs of computers has been done often enough, and is so limited in scope, so it might reasonably be expected to become "engineered," but the general software preparation is not likely to be under "engineering control" for many, many years.

"There are many proposals on how to improve the productivity of the individual programmer, as well as groups of programmers. I have already mentioned top-down and bottom-up; there are others, such as head programmer, lead programmer, proving the program is correct in a mathematical sense, and the waterfall model of programming, to name but a few. While each has some merit I have faith in only one, which is almost never mentioned—think before you write the program, it might be called. Before you start, think carefully about the whole thing, including what will be your acceptance test that it is right, as well as how later field maintenance will be done. Getting it right the first time is much better than fixing it up later!

"One trouble with much of programming is simply that often there is not a well-defined job to be done; rather, the programming process itself will gradually discover what the problem is! The desire that you will be given a well-defined problem before you start programming often does not match reality, and hence a lot of the current proposals to "solve the programming problem" will fall to the ground if adopted rigorously." (pages 57-58)

"Many studies have shown programmers differ in productivity, from worst to best, by much more than a factor of ten. From this I long ago concluded the best policy is to pay your good programmers very well but regularly fire the poorer ones—if you can get away with it! One way is, of course, to hire them on contract rather than as regularly employed people, but that is increasingly against the law, which seems to want to guarantee even the worst have some employment. In practice you may actually be better off to pay the worst to stay home and not get in the way of the more capable (and I am serious)!" (page 59)

"I made the comparison of writing software with the act of literary writing; both seem to depend fundamentally on clear thinking. Can good programming be taught? If we look at the corresponding teaching of "creative writing" courses we find most students of such courses do not become great writers, and most great writers in the past did not take creative writing courses! Hence it is dubious that great programmers can be trained easily.

"Does experience help? Do bureaucrats after years of writing reports and instructions get better? I have no real data, but I suspect with time they get worse! The habitual use of "governmentese" over the years probably seeps into their writing style and makes them worse. I suspect the same for programmers! Neither years of experience nor the number of languages used is any reason for thinking the programmer is getting better from these experiences. An examination of books on programming suggests most of the authors are not good programmers!

"The results I picture are not nice, but all you have to oppose it is wishful thinking—I have evidence of years and years of programming on my side!" (pages 60-61)

"People often make the mistake of saying, "Thinking is what Newton and Einstein did." But by that definition most of us cannot think—and usually we do not like that conclusion!" (page 79)

"... Of course robots will displace many humans doing routine jobs. In a very real sense, machines can best do routine jobs, thus freeing humans for more humane jobs. Unfortunately, many humans at present are not equipped to compete with machines—they are unable to do much more than routine jobs. There is a widespread belief (hope?) that humans can compete, once they are given proper training. However, I have long publicly doubted you could take many coal miners and make them into useful programmers. I have my reservations on the fraction of the human population that can be made into programmers in the classical sense; if you call getting money from the bank dispensing "machine programming," or the dialing of a telephone number (both of which apply the human input to an elaborate program which is then executed, much like an interpreter acts on your program input), then of course most people can be made into programmers. But if you mean the more classical activity of careful analysis of a situation and then the detailed specification as to what is to be done, then I say there are doubts as to what fraction of the population can compete with computers, even with nice interactive prompting menus.

"Computers have both displaced so many people from jobs, and also made so many new jobs, it is hopeless to try to answer which is the larger number. But it is clear that on average it is the lower-level jobs which are disappearing and the higher-level jobs which are appearing. Again, one would like to believe most people can be trained in the future to do the higher-level jobs—but that is a hope without any real evidence." (pag 94)

"It must be your friends, in some sense, who make you famous by quoting and citing you, and it pays, so I claim, to be helpful to others as they try to do their work. They may in time give you credit for the work, which is better than trying to claim it yourself. Cooperation is essential in these days of complex projects; the day of the individual worker is dying fast. Teamwork is more and more essential, and hence learning to work on a team, indeed possibly seeking out places where you can help others, is a good idea. In any case the fun of working with good people on important problems is more pleasure than the resulting fame." (page 210)

Let me turn to another effect of a measurement system, and illustrate it by the definition and use of IQs. What is done is a plausible list of questions—plausible from past experience—is made and then tried out on a small number of people. Those questions which show an internal correlation with others are kept and those which do not correlate well are dropped. Next, the revised test is calibrated by using it on a much larger sample. How? Simply by taking the accumulated scores (the number of people's score which are below the given amount) and plotting these revised numbers on probability paper—meaning the cumulative probabilities of a normal distribution are the horizontal lines. Next, the points where the cumulative actual scores fall at a given percentage points are related, via a calibration table, to the corresponding points on the cumulative normal probability curve. As a result it is observed intelligence has a normal distribution in the population! Of course it has, it was made to be that way! Furthermore, they have defined intelligence to be what is measured by the calibrated exam, and if that is the definition of intelligence, then of course intelligence is normally distributed. But if you think maybe intelligence is not exactly what the calibrated exam measures, then you are entitled to doubt intelligence is normally distributed in the population. Again, you get what was measured, and the normal distribution announced is an artifact of the method of measurement and hardly relates to reality. (page 375)

[ajschumacher]

Re: Hamming's coal miners remark: https://www.nytimes.com/2019/05/12/us/mined-minds-west-virginia-coding.html

(discovered after https://twitter.com/Minds_Mined followed me)

[ajschumacher]

Nick Patterson, Broad Institute https://planspace.org/20160427-simple_isnt_easy/

The smarter you are the less likely you are to make a stupid mistake.

as part of mechanism?

[ajschumacher]

In The Man Who Solved the Market:

"Simons was struck by the unique way talented researchers were recruited and managed in his unit [of IDA]. Staff members, most of whom had doctorates, were hired for their brainpower, creativity, and ambition, rather than for any specific expertise or background. The assumption was that researchers would find problems to work on and be clever enough to solve them. Lenny Baum, among the most accomplished code-breakers, developed a saying that became the group's credo: "Bad ideas is good, good ideas terrific, no ideas is terrible."" (pages 24-25)

---

"Courting accomplished candidates, Simons developed a unique perspective on talent. He told one Stony Brook professor, Hershel Farkas, that he valued "killers," those with a single-minded focus who wouldn't quit on a math problem until arriving at a solution. Simons told another colleague that some academics were "super smart" yet weren't original thinkers worthy of a position at the university.

""There are guys and there are real guys," he said." (pages 34-35)

---

“We can teach you about money,” Patterson explains. “We can’t teach you about smart.” (page 284)

[ajschumacher]

hmm https://www.investors.com/news/management/leaders-and-success/self-improvement-want-be-10-times-better-what-you-do-heres-how/ (promo for a book on the topic)

[ajschumacher]

“Passion is the genesis of genius.” is attributed to Galileo...

[ajschumacher]

"Fermi and the Manhattan Project embodied an age of discovery that rewarded quality over quantity in expertise. In nuclear physics, the 1030s and 1940s were an age of fundamental breakthroughs, and when it came to making those breakthroughs, one Enrico Fermi was worth thousands of less brilliant physicists. American leadership in this era was built in large part on attracting geniuses like Fermi: men and women who could singlehandedly tip the scales of scientific power.

"But not every technological revolution follows this pattern. Often, once a fundamental breakthrough has been achieved, the center of gravity quickly shifts from a handful of elite researchers to an army of tinkerers–engineers with just enough expertise to apply the technology to different problems. This is particularly true when the payoff of a breakthrough is diffused throughout society rather than concentrated in a few labs or weapons systems.

"Mass electrification exemplified this process. Following Thomas Edison's harnessing of electricity, the field rapidly shifted from invention to implementation. Thousands of engineers began tinkering with electricity, using it to power new devices and reorganize industrial processes. Those tinkerers didn't have to break new ground like Edison. They just had to know enough about how electricity worked to turn its power into useful and profitable machines."

Kaif-fu Lee, in AI Super-Powers, page 86

[ajschumacher]

"You have made a convert of an opponent in one sense, for I have always maintained that excepting fools, men did not differ much in intellect, only in zeal and hard work; and I still think this is an eminently important difference." (Ellenberg page 300, quoting Charles Darwin's letter to his cousin Francis Galton on the effect of reading Galton's "Hereditary Genius")

[ajschumacher]

"the useless class" is due to https://en.wikipedia.org/wiki/Yuval_Noah_Harari (author of Sapiens)

[ajschumacher]

Reich’s Law, in Failure to Disrupt:

“People who do stuff do more stuff, and people who do stuff do better than people who don’t do stuff.”

[ajschumacher]

"In revamping our education systems, we can learn much from South Korea's embrace of gifted and talented education. These programs seek to identify and realize the potential of the country's top technical minds, an approach suited to creating the material prosperity that can then be broadly shared across society." (page 229, Kai-fu Lee, AI Superpowers)

quick search turns up, e.g., http://www.koreaherald.com/view.php?ud=20160108000828

[ajschumacher]

Netflix CEO on paying sky-high salaries: ‘The best are easily 10 times better than average’ https://www.cnbc.com/2020/09/08/netflix-ceo-reed-hastings-on-high-salaries-the-best-are-easily-10x-better-than-average.html

"But, as an engineer, I was familiar with a concept that has been understood in software since 1968, referred to as the “rock-star principle.”"

"She has an adjustable perspective, so when she gets stuck in a specific way of thinking, she has ways to push, pull, or prod herself to look beyond."

points to "Exploratory experimental studies comparing online and offline programming performance" https://dl.acm.org/doi/10.1145/362851.362858 / pdf: https://web.eecs.umich.edu/~weimerw/481/readings/productivity-performance.pdf

[ajschumacher]

http://blogs.edweek.org/edweek/edtechresearcher/2014/03/big_data_mooc_research_breakthrough_learning_activities_lead_to_achievement.html

Reich's Law: "People who do stuff do more stuff, and people who do stuff do better than people who don't do stuff."" (page 39)

[ajschumacher]

"Reading instructors sometimes discuss a transition, which happens in about the third grade, from learning to read–learning how to decode the sounds and meaning of text–to reading to learn–using reading to advance content knowledge." (pages 63-64, Reich)

as an example of an educational "threshold" (not advancing a person's linear "score" but giving them a discrete skill) compare also Montessori normalization

Reich uses this language in Failure to Disrupt:

"People develop self-regulated learning strategies through direct instruction and practice, often through a long apprenticeship in formal educational systems." (page 36)

"The students who tend to thrive in these kinds of environments are those who have already demonstrated academic proficiency, since most people develop self-regulated learning through an apprenticeship in the formal education system." (page 235)

Reich also says:

"... step change is what continuous, incremental change looks like from a distance." (page 245)

---

On page 95 (of Reich), a reference to Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching:

"The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance." (from the abstract)

This is like employees who need "micro-management" if they aren't able to execute independently...

---

update 2020-10-08:

"... a shift in identity where the learning activity is a part of who they are rather than something that they do ..." (page 91, Justin Reich in Failure to Disrupt)

---

"Want your students to learn independently? It’s not as simple as that—in fact, students don’t get better at learning independently by just learning independently."

From a Learning How to Learn email, describing Daisy Christodoulou's book "Teachers vs Tech? The Case for an Ed Tech Revolution."

---

See also #215, where I write:

old posts: https://planspace.org/2011/09/10/future-of-education/ https://planspace.org/2012/03/05/ramblings-on-learning-management/

I used to have a lot more hope for computer-adaptive instruction, seems like.

My thinking now is something more like: The way to get individualized learning is to teach students the skill(s) of learning what they want to learn independently. It has to come from the students themselves.

---

The "Knowledge Portfolio" metaphor is pretty good. ("Tip 9: Invest Regularly in Your Knowledge Portfolio" page 15) We want people to be life-long knowledge investors.

(in The Pragmatic Programmer)

---

On the early US educational focus on "Americanizing" and making good citizens (rather than training for a job): https://newrepublic.com/article/152979/betsy-devos-fabricating-history-sell-bad-education-policy

---

Being able to type is another kind of transitional skill, and one I think should really get more attention...

---

being at some level of socioeconomic "comfort" (as opposed to scarcity as in Mullainathan and Shafir's book) is an important kind of transitional divide as well... see also wrap-around services, etc. (social/economic supports as a step function change)

[ajschumacher]

https://www.economist.com/graphic-detail/2020/10/03/its-better-to-be-a-poor-pupil-in-a-rich-country-than-the-reverse

suggests personal wealth ~ higher scores, but also country wealth ~ higher scores

[ajschumacher]

"agency" as a thing that can vary based on training

https://www.nature.com/articles/s41467-020-18152-x

and agency (choosing) as helping to learn

https://www.scientificamerican.com/article/we-learn-faster-when-we-arent-told-what-choices-to-make/

[ajschumacher]

"Many humans have the instinct to find and worship idols." (page 28)

"The Genius Myth is the tendency that we as humans need to ascribe the success of a team to a single person/leader." (page 28)

"The vast majority of the work at Google (and at most companies!) doesn't require genius-level intellect, but 100% of the work requires a minimal level of social skills." (page 29)

Software Engineering at Google, Brian Fitzpatrick

[ajschumacher]

Intelligence as more about fooling other people than being more productive per se:

Diana Fleischman http://nautil.us/blog/the-dark-side-of-smart

Human intelligence is incredibly useful but it doesn’t safeguard you against having false beliefs, because that’s not what intelligence is for. Intelligence is associated with coming up with more convincing bullshit and with being a better liar, but not associated with a better ability to recognize one’s own bias. Unfortunately, intelligence has very little influence on your ability to rationally evaluate your own beliefs, or undermine what’s called “myside bias.”

[ajschumacher]

"Ratings, although an important way to measure performance during a specific period, are not predictive of future performance and should not be used to gauge readiness for a future role or qualify an internal candidate for a different team." (page 77)

at Google; by Demma Rodriguez, in Software Engineering at Google

wasn't there some other thing about scores not being predictive of success at google? SATs or GPA or something? ... I don't see it in a quick googling...

[ajschumacher]

Guershon Harel has a "premise" (assumption) of some subtlety:

in https://math.ucsd.edu/~harel/pdf/DNRII.pdf (see also, #185 and #205)

Epistemophilia: Humans—all humans—possess the capacity to develop a desire to be puzzled and to learn to carry out mental acts to solve the puzzles they create. Individual differences in this capacity, though present, do not reflect innate capacities that cannot be modified through adequate experience.

[ajschumacher]

men vs. women in chess and the max-of-various-sample-sizes explanation: https://twitter.com/weijima01/status/1316690212047720448?s=21

[ajschumacher]

"A little bit of slope makes up for a lot of y-intercept" John Ousterhout https://gist.github.com/gtallen1187/e83ed02eac6cc8d7e185

but also: the increasing lines shouldn't really be straight, but possibly exponential

[ajschumacher]

on that linear/exponential question:

https://www.readingrockets.org/article/critical-thinking-why-it-so-hard-teach

Prior knowledge and beliefs not only influence which hypotheses one chooses to test, they influence how one interprets data from an experiment. In one experiment,18 undergraduates were evaluated for their knowledge of electrical circuits. Then they participated in three weekly, 1.5-hour sessions during which they designed and conducted experiments using a computer simulation of circuitry, with the goal of learning how circuitry works. The results showed a strong relationship between subjects' initial knowledge and how much subjects learned in future sessions, in part due to how the subjects interpreted the data from the experiments they had conducted. Subjects who started with more and better integrated knowledge planned more informative experiments and made better use of experimental outcomes.

ref 18 is: Schauble, L., Glaser, R., Raghavan, K., and Reiner, M. (1991). “Causal models and experimentation strategies in scientific reasoning,” The Journal of Learning Sciences, 1, 201-238.

[ajschumacher]

and: the Matthew effect: https://en.wikipedia.org/wiki/Matthew_effect

and here's even an exponential-looking "plot": https://www.phonicbooks.co.uk/2017/06/04/matthew-effect-comes-reading-instruction/

[ajschumacher]

The Five Dimensions of Curiosity https://hbr.org/2018/09/curiosity Todd B. KashdanDavid J. DisabatoFallon R. GoodmanCarl Naughton

[Curiosity] enhances intelligence: In one study, highly curious children aged three to 11 improved their intelligence test scores by 12 points more than their least-curious counterparts did. It increases perseverance, or grit: Merely describing a day when you felt curious has been shown to boost mental and physical energy by 20% more than recounting a time of profound happiness. And curiosity propels us toward deeper engagement, superior performance, and more-meaningful goals: Psychology students who felt more curious than others during their first class enjoyed lectures more, got higher final grades, and subsequently enrolled in more courses in the discipline.

[ajschumacher]

Thus it becomes obvious that one must be wary in attributing scientific discovery wholly to anyone person. Almost every discovery has a long and precarious history. Someone finds a bit here, another a bit there. A third step succeeds later and thus onward till a genius pieces the bits together and makes the decisive contribution. Science, like the Mississippi, begins in a tiny rivulet in the distant forest. Gradually other streams swell its volume. And the roaring river that bursts the dikes is formed from countless sources.

The Usefulness of Useless Knowledge, Abraham Flexner

[ajschumacher]

https://www.linkedin.com/pulse/yale-professor-craig-wright-cultivating-genius-youre-thinker-hempel/

some interesting quotes...

"In an odd way, it can be reduced down to a simple mathematical cool equation: Genius equals significance times number of people influenced times duration."

"The very notion of genius is predicated on an inequality—that some people have the capacity for...having a greater impact on society than other people."

[ajschumacher]

The difficulty of transfer (mentioned page 109 of Reich's Failure to Disrupt) makes me wonder to what extent transfer is related to general intelligence - or whether they might even be largely the same thing.

The referenced Critical Thinking: Why Is It So Hard to Teach? (web, more complete PDF) is quite good.

[ajschumacher]

"... over time, as you grow older, your overall stamina builds up. Early in your career, working eight hours a day in an office can feel like a shock; you come home tired and dazed. But just like training for a marathon, your brain and body build up larger reserves of stamina over time." (page 120, Software Engineering at Google, written by Ben Collins-Sussman, edited by Riona MacNamara)

[ajschumacher]

"People complain of the lack of power to concentrate, not witting that they may acquire the power, if they choose." (page 37, How to live on 24 hours a day)

[ajschumacher]

Giftedness and Genius: Crucial Differences https://www.gwern.net/docs/iq/1996-jensen.pdf

My primary thesis is that the emergence of genius is best described using a multiplicative model.

I will argue that exceptional achievement is a multiplicative function of a number of different traits, each of which is normally distributed, but which in combination are so synergistic as to skew the resulting distribution of achievement.

Scientific genius: A psychology of science (Simonton, 1988) https://psycnet.apa.org/record/1988-98120-000

that ref refs: Ortega hypothesis https://en.wikipedia.org/wiki/Ortega_hypothesis (average or mediocre scientists contribute substantially to the advancement of science; opposed to "Newton hypothesis" that it's all about great scientists - nice parallel with great man theory of history vs. people's history, etc.)

Genius: The natural history of creativity (Eysenck, 1995) https://psycnet.apa.org/record/1995-98356-000

"Moreover, the upper limit of genius cannot be described as characterized by precocity, high intelligence, knowledge and problem-solving skills being learned with speed and ease, outstanding academic achievement, honors and awards, or even intellectual productivity."

"In discussing Ramanujan's work, the Polish mathematician Mark Kac was forced to make a distinction between the "ordinary genius" and the "magician.""

• ability
• productivity
• creativity

The "chance configuration" theory of creativity isn't really tenable because people are bad at being random (and because of combinatorics).

Eysenck Personality Questionnaire (for psychoticism) https://en.wikipedia.org/wiki/Eysenck_Personality_Questionnaire

P - Psychoticism/Socialisation: Psychoticism is associated not only with the liability to have a psychotic episode (or break with reality), but also with aggression. Psychotic behavior is rooted in the characteristics of toughmindedness, non-conformity, inconsideration, recklessness, hostility, anger and impulsiveness. The physiological basis suggested by Eysenck for psychoticism is testosterone, with higher levels of psychoticism associated with higher levels of testosterone.

"Price's Law" https://en.wikipedia.org/wiki/Derek_J._de_Solla_Price#Scientific_contributions half of contributions made by sqrt(n_contributors) people; similar to https://en.wikipedia.org/wiki/Lotka%27s_law and Matthew Principle (also Pareto principle?)

"twisted pear" plot of productivity versus IQ https://www.megasociety.net/noesis/149/iq&pear.html refs https://prometheussociety.org/ huh! Mensa is 1/50, Prometheus is 1/30k weird https://en.wikipedia.org/wiki/Prometheus_Society

• motivation

• mental energy

"serum urate level (SUL) ... They [some studies] show that SUL is only slightly correlated with IQ, but is more highly correlated with achievement and productivity."

"Why should there be such a relationship? The most plausible explanation seems to be that the molecular structure of uric acid is nearly the same as that of caffeine, and therefore it acts as a brain stimulant."

refs "Physical Correlates Of Human Intelligence" (Jensen & Sinha, 1993) https://www.gwern.net/docs/iq/1993-jensen.pdf which says "Belief in an association between gout and eminencedates back to antiquity." etc.

The author's three ingredients:

• "Ability = g = efficiency of information processing"
• "Productivity = endogenous cortical stimulation"
• "Creativity = trait psychoticism"

"A high level of expertise involves the automatization of a host of special skills and cognitive routines. Automatization comes about only as a result of an immense amount of practice. Most people can scarcely imagine (and are probably incapable of) the extraordinary amount of practice that is required for genius-quality performance, even for such a prodigious genius as Mozart."

"... the direction of personal ambition and the persistence of effort."

The author quotes some correspondent:

"I have felt for a long time that IQ, however defined, is only loosely related to mental achievement. Over the years I have bumped into a fair number of MENSA people. As a group, they seem to be dilettantes seeking titillation but seem unable to think critically or deeply. They have a lot of motivation for intellectual play but little for doing anything worthwhile. One gets the feeling that brains were wasted on them. So, what it is that makes an intelligently productive person?"

"Genius involves actual achievement and creativity."

"Individual differences in countable units of achievement, unlike measures of ability, are not normally distributed, but have a very positively skewed distribution, resembling the so-called J-curve."

https://en.wikipedia.org/wiki/J_curve but I think he just means a hockey stick?

"... the J-curve can be normalized by a logarithmic transformation."

consistent with a multiplicative process, perhaps... but isn't that consistent with multiplying many small factors, in the same way that normal is a sum of many small factors? hmm...

"... the threshold nature of g and math talent is so crucial to excelling in math and the quantitative sciences ..."

The author suggests (with Lubinski and Benbow) that a "theoretical orientation" might be an important additional factor ("as measured by the Allport, Vernon, and Lindzey Study of Values" https://en.wikipedia.org/wiki/Values_scale#Allport-Vernon-Lindzey).

"Thus, a nation's most important resource is the level of educated intelligence in its population; it determines the quality of life. It is imperative for society to cultivate all the high ability that can possibly be found, wherever it can be found."

[ajschumacher]

https://planspace.org/20201108-game_changer_solomon_blumberg/ ("How to be 10x in the talent economy")

[ajschumacher]

https://rittersp.com/wp-content/uploads/2014/03/Chambliss-Mundanity-of-Excellence.pdf (linked from https://terrytao.wordpress.com/career-advice/does-one-have-to-be-a-genius-to-do-maths/)

"... not only are the little things important; in some ways, the little things are the only things."

"... the simple doing of certain small tasks can generate huge results. Excellence is mundane."

interesting note about "college professors" on page 82, about how most don't publish at all, and "simply participating in scholarship is a huge step."

"In the pursuit of excellence, maintaining mundanity is the key psychological challenge."

"1) Excellence is a qualitative phenomenon."

"2) Talent is a useless concept."

"3) Excellence is mundane."

"Motivation is mundane, too." (local, short-term rewards)

[ajschumacher]

"How to be a genius" https://talentdevelop.com/articles/HTBAG.html by David Dobbs (linked from https://terrytao.wordpress.com/career-advice/does-one-have-to-be-a-genius-to-do-maths/) is largely about working hard

references "Cambridge Handbook of Expertise and Expert Performance"

genius is 99 per cent perspiration - or, to be truer to the data, perhaps 1 per cent inspiration, 29 per cent good instruction and encouragement, and 70 per cent perspiration

[ajschumacher]

The idea of innate genius sort of lines up with the fiction trope of the accidental hero: something happened to them (external cause, like Harry Potter) which hasn't happened to you, the reader, so there's no reason for you to be exceptional.

The difference between fantasy and biography is whether the hero becomes exceptional by luck or effort.

There is still the question of how much motivation and the tendency/ability to work hard is pre-determined. Certainly you don't have much control over whether you're born into a supportive environment, etc.

[ajschumacher]

Terry Tao's "Does one have to be a genius to do maths?"

includes this quote:

Better beware of notions like genius and inspiration; they are a sort of magic wand and should be used sparingly by anybody who wants to see things clearly. (José Ortega y Gasset, “Notes on the novel”)

also links to this Norvig thing on winning programming contests being bad for Google job performance: https://catonmat.net/programming-competitions-work-performance

another thought: If you have very high IQ, are you more likely to realize that a happy life is one that doesn't involve extreme levels of achievement? Maybe it's helpful to not be quite so smart, in order to still want to work really hard? (compare dolphins in Hitchhiker's guide, who are happy to not make cities etc.)

[ajschumacher]

"... the reality that there is anywhere from a 20:1 and 40:1 difference in productivity among developers, depending on whose study you believe" (page 23, with footnote as follows) "In 1968, a difference of 10:1 in productivity among programmers was noted in Exploratory experimental studies comparing online and offline programming performance. The gulf seems to have widened since then." (in Pragmatic Thinking and Learning)

"Sadly, studies seem to indicate that most people, for most skills, for most of their lives, never get any higher than the second stage [of five], advanced beginner, "performing the tasks they need and learning new tasks as the need arises but never acquiring a more broad-based, conceptual understanding of the task environment."" (page 25)

[ajschumacher]

"They say that equality is not possible, because some people will always be stronger or smarter than others. But it is exactly because of this, said Lichtenberg, precisely because some people are stronger and smarter than others, that the principle of equality is necessary. The advantages of the rich over the poor demonstrate not only inequality of force and intellect, but inequality of civil rights."

Leo Tolstoy, A Calendar of Wisdom, page 60 (entry for February 17)

(that must be https://en.wikipedia.org/wiki/Georg_Christoph_Lichtenberg who is mentioned)