Posts
Comments
I would like to see an (optional) personality test section - email me at jsinick@gmail.com if you're interested in the possibility, as I have some detailed thoughts.
Yes, this is something that I've wondered about quite a bit specifically in connection with the variation in conscientiousness and agreeableness by religion. I plan on partially addressing this issue by discussing some objective behavioral proxies to the personality traits in later posts.
What I had in mind was that the apparent low average conscientiousness in the Bay Area might have been one of the cultural factors that drew rationalists who are involved in the in-person community to the location. But of course the interpretation that you raise is also a possibility.
Glad you liked it :-).
So I'd be interested to hear a little more info on methodology - what programming language(s) you used, how you generated the graphs, etc.
I used R for this analysis. Some resources that you might find relevant:
- Practical Data Science with R has very nice introduction to exploratory data analysis.
- Advanced R goes into more detail on the language.
- The graphs were made using ggplot2.
- I used the lme4 package for Bayesian hierarchical modeling. See, e.g. Getting Started with Mixed Effect Models in R.
- Kaggle Kernels has some good sample scripts.
And depending on how far back most of this data was collected, plausibly most of the Berkeley respondents were high school or college students (UC Berkeley alone has over 35,000 students), since for awhile that was the main demographic of Facebook users, and probably for awhile longer that was the main demographic of Facebook users willing to take personality tests.
Douglas_Knight is correct – the average age of users is quite low, at ~26 years old both for the high conscientiousness cities and the low conscientiousness cities.
Physics is established, so one can defer to existing authorities and get right answers about physics. Starting a well-run laundromat is also established, so ditto. Physics and laundromat-running both have well-established feedback loops that have validated their basic processes in ways third parties can see are valid.
Depending on which parts of physics one has in mind, this seems possibly almost exactly backwards (!!). Quoting from Vladimir_M's post Some Heuristics for Evaluating the Soundness of the Academic Mainstream in Unfamiliar Fields:
If a research area has reached a dead end and further progress is impossible except perhaps if some extraordinary path-breaking genius shows the way, or in an area that has never even had a viable and sound approach to begin with, it’s unrealistic to expect that members of the academic establishment will openly admit this situation and decide it’s time for a career change. What will likely happen instead is that they’ll continue producing output that will have all the superficial trappings of science and sound scholarship, but will in fact be increasingly pointless and detached from reality.
Arguably, some areas of theoretical physics have reached this state, if we are to trust the critics like Lee Smolin. I am not a physicist, and I cannot judge directly if Smolin and the other similar critics are right, but some powerful evidence for this came several years ago in the form of the Bogdanoff affair, which demonstrated that highly credentialed physicists in some areas can find it difficult, perhaps even impossible, to distinguish sound work from a well-contrived nonsensical imitation.
The reference to Smolin is presumably to The Trouble With Physics: The Rise of String Theory, the Fall of a Science, and What Comes Next . Penrose's recent book Fashion, Faith, and Fantasy in the New Physics of the Universe also seems relevant.
A few nitpicks on choice of "Brier-boosting" as a description of CFAR's approach:
Predictive power is maximized when Brier score is minimized
Brier score is the sum of differences between probabilities assigned to events and indicator variables that are are 1 or 0 according to whether the event did or did not occur. Good calibration therefore corresponds to minimizing Brier score rather than maximizing it, and "Brier-boosting" suggests maximization.
What's referred to as "quadratic score" is essentially the same as the negative of Brier score, and so maximizing quadratic score corresponds to maximizing predictive power.
Brier score fails to capture our intuitions about assignment of small probabilities
A more substantive point is that even though the Brier score is minimized by being well-calibrated, the way in which it varies with the probability assigned to an event does not correspond to our intuitions about how good a probabilistic prediction is. For example, suppose four observers A, B, C and D assigned probabilities 0.5, 0.4, 0.01 and 0.000001 (respectively) to an event E occurring and the event turns out to occur. Intuitively, B's prediction is only slightly worse than A's prediction, whereas D's prediction is much worse than C's prediction. But the difference between the increase in B's Brier score and A's Brier score is 0.36 - 0.25 = 0.11, which is much larger than corresponding difference for D and C, which is approximately 0.02.
Brier score is not constant across mathematically equivalent formulations of the same prediction
Suppose that a basketball player is to make three free throws, observer A predicts that the player makes each one with probability p and suppose that observer B accepts observer A's estimate and notes that this implies that the probability that the player makes all three free throws is p^3, and so makes that prediction.
Then if the player makes all three free throws, observer A's Brier score increases by
3*(1 - p)^2
while observer B's Brier score increases by
(1 - p^3)^2
But these two expressions are not equal in general, e.g. for p = 0.9 the first is 0.03 and the second is 0.073441. So changes to Brier score depend on the formulation of a prediction as opposed to the prediction itself.
======
The logarithmic scoring rule handles small probabilities well, and is invariant under changing the representation of a prediction, and so is preferred. I first learned of this from Eliezer's essay A Technical Explanation of a Technical Explanation.
Minimizing logarithmic score is equivalent to maximizing the likelihood function for logistic regression / binary classification. Unfortunately, the phrase "likelihood boosting" has one more syllable than "Brier boosting" and doesn't have same alliterative ring to it, so I don't have an actionable alternative suggestion :P.
Brian Tomasik's article Why I Prefer Public Conversations is relevant to
I suspect that most of the value generation from having a single shared conversational locus is not captured by the individual generating the value (I suspect there is much distributed value from having "a conversation" with better structural integrity / more coherence, but that the value created thereby is pretty distributed). Insofar as there are "externalized benefits" to be had by blogging/commenting/reading from a common platform, it may make sense to regard oneself as exercising civic virtue by doing so, and to deliberately do so as one of the uses of one's "make the world better" effort. (At least if we can build up toward in fact having a single locus.)
Wait, your category (ii) is surely exactly what we care about here.
Yes, I see how my last message was ambiguous.
What I had in mind in bringing up category (ii) is that we've had some students who had a priori worse near term employment prospects relative to the usual range of bootcamp attendees, who are better positions than they had been and who got what they were looking to get from the program, while not yet having $100k+ paying jobs. And most students who would have gotten $100k+ paying jobs even if they hadn't attended appear to have benefited from attending the program.
The nature of the value that we have to add is very much specific to the student.
Hello! I'm a cofounder of Signal Data Science.
Because our students have come into the program from very heterogeneous backgrounds (ranging from high school dropout to math PhD with years of experience as a software engineer), summary statistics along the lines that you're looking for are less informative than might seem to be the case prima facie. In particular, we don't yet have meaningfully large sample of students who don't fall into one of the categories of (i) people who would have gotten high paying jobs anyway and (ii) people who one wouldn't expect to have gotten high paying jobs by now, based on their backgrounds.
If you're interested in the possibility of attending the program, we encourage you to fill out our short application form. If it seems like it might be a good fit for you, we'd be happy to provide detailed answers to any questions that you might have about job placement.
Yes, that was supposed to be June 24th! We have a third one from July 5th – August 24th. There are still spaces in the program if you're interested in attending.
Thanks for the written feedback (which adds to what I had gleaned in person).
There were actually multiple times during the first couple weeks when I (or my partner and I) would spend 4+ hours trying to fix one particular line of code, and Jonah would give big-picture answers about e.g. how linear regression worked in theory, when what I'd asked for were specific suggestions on how to fix that line of code. This led me to giving up on asking Jonah for help after long enough.
I think that what happened here is me having misunderstood what you were asking for, rather than any disinclination on my part to help you with individual lines of code. I will take this feedback into account.
Intermediate and advanced SQL, practice of certain social skills (e.g. handshakes, being interested in your interviewer, and other interview-relevant social skills), and possibly nonlinear models.
This is helpful detail regarding what you were looking for. Which topics would you have preferred to have been been dropped in favor of these?
Hi Toggle,
Thanks for your question!
Most of our students have just started looking for jobs over the past ~2 weeks, and the job search process in the tech sector typically takes ~2 months, from sending out resumes to accepting offers (see, e.g. "Managing your time" in Alexei's post Maximizing Your Donations via a Job).
The feedback loop here is correspondingly longer than we'd like. We expect to have an answer to your question by the time we advertise our third cohort.
Thanks for your interest! Some responses below.
Do you require applicants to have a graduate degree?
No degree is required. We're selecting on ability rather than on credentials.
Zipfian Academy, App Academy, and other bootcamps are 12 weeks long, and (the first instance of) this one is only 6 weeks long. Why is this, and what are you cutting out relative to other data science bootcamps to make it this short? (This is my most pressing question).
Based on the preliminary interest that people have expressed anticipate that the students in our first cohort will be significantly stronger than is typical of data science bootcamps, and will correspondingly be able to cover the material at an accelerated pace. We expect at least some of our cohorts to run a full 12 weeks.
Regarding the comparison with coding bootcamps, there are reasons to believe that the amount that somebody needs to know to be in the top x% of industry data scientists is less than the amount that's needed to be in the top x% of programmers. (I can elaborate.)
We're cutting out some of the more advanced machine learning algorithms, which industry data scientists use infrequently enough so that they can be a distraction from getting started.
As a tie-in to my last question, is there a hiring event which employers will be invited to around the end of the program?
Very few bootcamp students who I know got their jobs through this route, so we may or may not do this depend on how efficient it is relative to other routes. Like other bootcamps that offer the "pay later" model, we have a large stake in ensuring that our students find jobs.
Do you know which language(s) you'll be using?
We'll be working primarily in R, and teaching SQL as well.
Yes, we'll definitely be covering this.
Thanks for the suggestion. That would be wonderful. We'll definitely think about this – it's a matter of whether we can create a sufficiently simple presentation of the material so that the marginal returns per unit time are high for the student population that we'll be working with.
It might be that I have gotten to cynic but if you measure 6 variables it's more likely that one of them get a statistical significant result then if you first turn those 6 variables into 2 variables via PCA.
Yes, this is the point :-)
I'm sure you're aware that the word "cult" is a strong claim that requires a lot of evidence, but I'd also issue a friendly warning that to me at least it immediately set off my "crank" alarm bells.
Thanks, yeah, people have been telling me that I need to be more careful in how I frame things. :-)
Do you have evidence of legitimate mathematical results or research being hidden/withdrawn from journals or publicly derided, or is it more of an old boy's club that's hard for outsiders to participate in and that plays petty politics to the damage of the science?
The latter, but note that that's not necessarily less damaging than active suppression would be.
Or maybe most social behavior is too cult-like. If so; perhaps don't single out mathematics.
Yes, this is what I believe. The math community is just unusually salient to me, but I should phrase things more carefully.
I question the direction of causation. Historically many great mathematicians have been mentally and socially atypical and ended up not making much sense with their later writings. Either mathematics has always had an institutional problem or mathematicians have always had an incidence of mental difficulties (or a combination of both; but I would expect one to dominate).
Most of the people who I have in mind did have preexisting difficulties. I meant something like "relative to a counterfactual where academia was serving its intended function." People of very high intellectual curiosity sometimes approach academia believing that it will be an oasis and find this not to be at all the case, and that the structures in place are in fact hostile to them.
This is not what the government should be supporting with taxpayer dollars.
Especially in Thurston's On Proof and Progress in Mathematics I can appreciate the problem of trying to grok specialized areas of mathematics.
What are your own interests?
That probably where there's something I don't understand. I don't understand why the analysis took ~1500 hours. Spending that much time with a dataset also instinctively triggers "fishing expedition" in my head. I don't know to what extend that's warranted.
The issue of multiple hypothesis testing is precisely why it took 1500 hours :-). I was dealing with the general question "how can you find the most interesting generalizable patterns in a human interpretable data set?" It'll take me a long time to externalize what I learned.
For now I'll just remark that dimensionality reduction reduces concerns around multiple hypothesis testing. If you have a cluster of variables A and a cluster of features B and you suspect that there's some relationship between the variables A and the variables B, you can do PCA on the two clusters separately, then look at correlations between the first few principal components rather than looking at all pairwise correlations between variables in A and variables in B.
A more interesting project would be to explore LW's ideological landscape. It would be very interested in how various rationalist beliefs interact with each other. Does seeing yourself as an "aspiring rationalist" correlates to beliefs on UFAI risk?
There is the 2014 LW survey data, which is interesting, even if less substantive than what you have in mind. I have an unfinished project that I'm doing with it (got bogged down in cleaning it to make it nicely readable).
I don't have direct exposure to CS academia, which, as you comment, is known to be healthier :-). I was speaking in broad brushstrokes , I'll qualify my claims and impressions more carefully later.
I'll be writing more about this later.
The most scary thing to me is that the most mathematically talented students are often turned off by what they see in math classes, even at the undergraduate and graduate levels. Math serves as a backbone for the sciences, so this may badly undercutting scientific innovation at a societal level.
I honestly think that it would be an improvement on the status quo to stop teaching math classes entirely. Thurston characterized his early math education as follows:
I hated much of what was taught as mathematics in my early schooling, and I often received poor grades. I now view many of these early lessons as anti-math: they actively tried to discourage independent thought. One was supposed to follow an established pattern with mechanical precision, put answers inside boxes, and "show your work," that is, reject mental insights and alternative approaches.
I think that this characterizes math classes even at the graduate level, only at a higher level of abstraction. The classes essentially never offer students exposure to free-form mathematical exploration, which is what it takes to make major scientific discoveries with significant quantitative components.
Yes, this seems like a fair assessment o the situation. Thanks for disentangling the issues. I'll be more precise in the future.
I'm speaking based on many interactions with many members of the community. I don't think this is true of everybody, but I have seen a difference at the group level.
Do people pathologize Grothendieck as having gone crazy?
His contribution of math is too great for people to have explicitly adopted a stance that was too unfavorable to him, and many mathematicians did in fact miss him a lot. But as Perelman said:
Of course, there are many mathematicians who are more or less honest. But almost all of them are conformists. They are more or less honest, but they tolerate those who are not honest." He has also said that "It is not people who break ethical standards who are regarded as aliens. It is people like me who are isolated.
If pressed, many mathematicians downplay the role of those who behaved unethically toward him and the failure of the community to give him a job in favor of a narrative "poor guy, it's so sad that he developed mental health problems."
The top 3 answers to the MathOverflow question Which mathematicians have influenced you the most? are Alexander Grothendieck, Mikhail Gromov, and Bill Thurston. Each of these have expressed serious concerns about the community.
Grothendieck was actually effectively excommunicated by the mathematical community and then was pathologized as having gone crazy. See pages 37-40 of David Ruelle's book A Mathematician's Brain.
Gromov expresses strong sympathy for Grigory Perelman having left the mathematical community starting on page 110 of Perfect Rigor. (You can search for "Gromov" in the pdf to see all of his remarks on the subject.)
Thurston made very apt criticisms of the mathematical community in his essay On Proof and Progress In Mathematics. See especially the beginning of Section 3: "How is mathematical understanding communicated?" Terry Tao endorses Thurston's essay in his obituary of Thurston. But the community has essentially ignored Thurston's remarks: one almost never hears people talk about the points that Thurston raises.
I'm not claiming otherwise: I'm merely saying that Paul and Jacob don't dismiss LWers out of hand as obviously crazy, and have in fact found the community to be worthwhile enough to have participated substantially.
One of the things I find most charming about LW, compared to places like RationalWiki, is how much emphasis there is on self-improvement and your mistakes, not mistakes made by other people because they're dumb.
I agree that LW is much better than RationalWiki, but I still think that the norms for discussion are much too far in the direction of focus on how other commenters are wrong as opposed to how one might oneself be wrong.
I know that there's a selection effect (with respect to the more frustrating interactions standing out). But people not infrequently mistakenly believe that I'm wrong about things that I know much more about than they do, with very high confidence, and in such instances I find the connotations that I'm unsound to be exasperating.
I don't think that this is just a problem for me rather than a problem for the community in general: I know a number of very high quality thinkers in real life who are uninterested in participating on LW explicitly because they don't want to engage with commenters who are highly confident that their own positions are incorrect. There's another selection effect here: such people aren't salient because they're invisible to the online community.
I'm sympathetic to everything you say.
In my experience there's an issue of Less Wrongers being unusually emotionally damaged (e.g. relative to academics) and this gives rise to a lot of problems in the community. But I don't think that the emotional damage primarily comes from the weird stuff that you see on Less Wrong. What one sees is them having born the brunt of the phenomenon that I described here disproportionately relative to other smart people, often because they're unusually creative and have been marginalized by conformist norms
Quite frankly, I find the norms in academia very creepy: I've seen a lot of people develop serious mental health problems in connection with their experiences in academia. It's hard to see it from the inside: I was disturbed by what I saw, but I didn't realize that math academia is actually functioning as a cult, based on retrospective impressions, and in fact by implicit consensus of the best mathematicians of the world (I can give references if you'd like) .
Thanks so much for sharing. I'm astonished by how much more fruitful my relationships have became since I've started asking.
I think that a lot of what you're seeing is a cultural clash: different communities have different blindspots and norms for communication, and a lot of times the combination of (i) blindspots of the communities that one is familiar with and (ii) respects in which a new community actually is unsound can give one the impression "these people are beyond the pale!" when the actual situation is that they're no less rational than members of one's own communities.
I had a very similar experience to your own coming from academia, and wrote a post titled The Importance of Self-Doubt in which I raised the concern that Less Wrong was functioning as a cult. But since then I've realized that a lot of the apparently weird beliefs on LWers are in fact also believed by very credible people: for example, Bill Gates recently expressed serious concern about AI risk.
If you're new to the community, you're probably unfamiliar with my own credentials which should reassure you somewhat:
I did a PhD in pure math under the direction of Nathan Dunfield, who coauthored papers with Bill Thurston, who formulated the geometrization conjecture which Perelman proved and in doing so won one of the Clay Millennium Problems.
I've been deeply involved with math education for highly gifted children for many years. I worked with the person who won the American Math Society prize for best undergraduate research when he was 12.
I worked at GiveWell, which partners with with Good Ventures, Dustin Moskovitz's foundation.
I've done fullstack web development, making an asynchronous clone of StackOverflow (link).
I've done machine learning, rediscovering logistic regression, collaborative filtering, hierarchical modeling, the use of principal component analysis to deal with multicollinearity, and cross validation. (I found the expositions so poor that it was faster for me to work things out on my own than to learn from them, though I eventually learned the official versions).You can read some details of things that I found here. I did a project implementing Bayesian adjustment of Yelp restaurant star ratings using their public dataset here
So I imagine that I'm credible by your standards. There are other people involved in the community who you might find even more credible. For example: (a) Paul Christiano who was an international math olympiad medalist, wrote a 50 page paper on quantum computational complexity with Scott Aaronson as an undergraduate at MIT, and is a theoretical CS grad student at Berkeley. (b) Jacob Steinhardt, a Hertz graduate fellow who does machine learning research under Percy Liang at Stanford.
So you're not actually in some sort of twilight zone. I share some of your concerns with the community, but the groupthink here is no stronger than the groupthink present in academia. I'd be happy to share my impressions of the relative soundness of the various LW community practices and beliefs.
Yes, you seem to have a very clear understanding of where I'm coming from. Thanks.
See my edit. Part of where I'm coming from is realizing how socially undeveloped people's in our reference class are tend to be, such that apparent malice often comes from misunderstandings.
See Rationality is about pattern recognition, not reasoning.
Your tone is condescending, far outside of politeness norms. In the past I would have uncharitably written this off to you being depraved, but I've realized that I should be making a stronger effort to understand other people's perspectives. So can you help me understand where you're coming from on an emotional level?
Why did you have this impression?
Groupthink I guess: other people who I knew didn't think that it's so important (despite being people who are very well educated by conventional standards, top ~1% of elite colleges).
Tell me how exactly you're planning to use PCA day-to-day?
Disclaimer: I know that I'm not giving enough evidence to convince you: I've thought about this for thousands of hours (including working through many quantitative examples) and it's taking me a long time to figure out how to organize what I've learned.
I already have been using dimensionality reduction (qualitatively) in my day to day life, and I've found that it's greatly improved my interpersonal relationships because it's made it much easier to guess where people are coming from (before people's social behavior had seemed like a complicated blur because I saw so many variables without having started to correctly identify the latent ones).
i think the sooner you lose the need for everything to resonate deeply or have a concise insightful summary, the better.
You seem to be making overly strong assumptions with insufficient evidence: how would you know whether this was the case, never having met me? ;-)
It seem to me like to make major contributions to human knowledge you need to do a lot more than say: "Hey PCA is really great". You actually have to understand reasons of why people aren't using it and fixing those reasons.
Have you read my speed dating project posts? I haven't yet written up the most important one on demographics (I can do that soon, just many conflicting priorities), but the one on individual variation in revealed preferences for attractiveness vs intelligence and sincerity starts to get at what I'm talking about.
My project gives a proof of concept for what I'm talking about in the context of social psychology. I've never seen such an application. So no, it's not just the realization that it could be applied, it's also giving a proof of concept: that's why it took ~1500 hours rather than ~10 hours.
As far as I can tell, the situation is simply that deep knowledge of the technique hasn't yet percolated into the social psychology community, and people who do have the relevant background knowledge haven't actually tried doing social psychology research. All you need is to notice something that's been missed. There are many such things (see Peter Thiel's discussion of how there are still secrets in his book "From Zero To One.")
If I recall correctly, Freeman Dyson has indicated that his demonstration of the equivalence of the two different formulations of quantum electrodynamics isn't as amazing as people believe, but was largely a function of him being one of the first people to learn both formulations! :-)
So I'd strongly encourage you to pursue your ideas more. I've been looking some at the General Social Survey data, where I haven't yet found something highly nontrivial (maybe I'm looking at the data the wrong way, or maybe it's just not a good dataset for this). I'd be happy to share my code with you / a cleaned form of the data, if you're interested in exploring factors for political labels.
Ok, I guess what I mean is that it's suspicious that it maps onto a preexisting notion held by the general population, in the same way that it would be suspicious for psychology research to apparently show the existence of demon possession (which humans have in fact believed in). I wouldn't find it suspicious if it mapped onto a notion of someone with demonstrated exceptional ability to read and connect with people (e.g. Bill Clinton).
The way scientific progress occurs is by developing progressively more refined understandings of what's going on: for example, passing from the Ptolemaic model of the stars and planets to the Copernican model to the Newtonian model to Einstein's theory of general relativity. One can't hope to understand reality if one isn't flexible enough to recognize that things might be very different from how they initially appear.
I know that many researchers know something about PCA. I do think that it's not applied nearly enough (c.f. Sarah's remarks about Asperger's Syndrome, which was removed from the DSM a few years after she made her post). The main issue to my mind is that when people apply it in psychology they seem to come into it with preconceived notions concerning what they might find, rather than collecting large and diverse datasets, letting it speak for itself, and then trying to interpret what the principal components mean in human terms.
Consider the construct of conscientiousness. It's very suspicious that it maps onto a prexisting notion, and it's just not that predictive. I got lots of C's and D's in school, but worked 90 hours a week for 12 weeks on my speed dating project. Am I conscientious? ;-) As far as I can tell, they came up with questions based on preconceived notions, then did factor analysis, and came up with a construct that some meaning, while being very far from carving reality at its joints.
Yes. The basic situation is that I figured out how the methods that Charles Spearman used to discover IQ can be used to shed a lot of light on many different psychology and sociology questions. This is what I was implicitly getting at in my sequence of posts on my Speed Dating Project, though I did a poor job contextualizing the results. IQ is by far the most robust construct to come out of psychology research, so this could in principle revolutionize social science (with a huge amount of work by many talented people).
Some people would say that psychology researchers used the methodology to discover the Big 5 Personality traits among other things, but the constructs that they developed are relatively weak because they haven't utilized the full power of Spearman's framework. See also Sarah Constantin's post A Yardstick for Smell: Thinking in PCA (she preempted me in recognizing the potential of the methods 4.5 years before I did, but I didn't fully understand what she was getting at at the time).
It's difficult to make such claims without coming across as grandiose and/or arrogant, so I should emphasize that I think that many LWers would be capable of doing such research with the right background and style of research, if they took Paul Graham and Steve Jobs' advice. The great mathematician Alexander Grothendieck said:
In our acquisition of knowledge of the Universe ( whether mathematical or otherwise) that which renovates the quest is nothing more nor less than complete innocence. It is in this state of complete innocence that we receive everything from the moment of our birth. Although so often the object of our contempt and of our private fears, it is always in us. It alone can unite humility with boldness so as to allow us to penetrate to the heart of things, or allow things to enter us and taken possession of us.
This unique power is in no way a privilege given to "exceptional talents" - persons of incredible brain power (for example), who are better able to manipulate, with dexterity and ease, an enormous mass of data, ideas and specialized skills. Such gifts are undeniably valuable, and certainly worthy of envy from those who (like myself) were not so endowed at birth," far beyond the ordinary".
Yet it is not these gifts, nor the most determined ambition combined with irresistible will-power, that enables one to surmount the "invisible yet formidable boundaries " that encircle our universe. Only innocence can surmount them, which mere knowledge doesn't even take into account, in those moments when we find ourselves able to listen to things, totally and intensely absorbed in child play.
[...]
In fact, most of these comrades who I gauged to be more brilliant than I have gone on to become distinguished mathematicians. Still, from the perspective of 30 or 35 years, I can state that their imprint upon the mathematics of our time has not been very profound. They've all done things, often beautiful things, in a context that was already set out before them, which they had no inclination to disturb. Without being aware of it, they've remained prisoners of those invisible and despotic circles which delimit the universe of a certain milieu in a given era. To have broken these bounds they would have had to rediscover in themselves that capability which was their birth-right, as it was mine: the capacity to be alone.
Maybe I'm misinterpreting, but do you mean "...that that's simply because psychology researchers haven't investigated it carefully."?
Yes, thanks, fixed.
I did some reading of the literature on intrinsic motivation and came to a conclusion I hadn't seen anywhere else, which is that people are intrinsically motivated to complete tasks that raise their status.
Yes, I think that the situation is that people are biologically hardwired to pursue their comparative advantage because doing so was was historically what was most conducive to becoming higher status, so that people's motivation goes way up when they're pursuing their natural comparative advantage (relative to their subjectively perceived communities).
Thanks for the detailed comment. I omitted details in order to keep my post short, and get the main point across.
I believe that the IQ tests that Terman and Hollingworth were using were effectively scaled differently from modern IQ tests. They may have corresponded to "mental age" as opposed to "standard deviations. In particular, they discuss IQ scores of 180, and there definitely aren't enough people who are 5+ SD above the mean to get reliable scores in that range.
Putting that aside, there are genetic factors other than IQ alone that play a role in intellectual and emotional development See my discussion of aesthetic discernment here: it hasn't been established as a valid psychometric construct, but I have very high confidence that that's simply because psychology researchers haven't investigated it carefully. If one is 2.5+ SD above the mean in each of IQ and aesthetic discernment, one is going to be extremely isolated. I think that that's what one is seeing with someone like Scott Alexander.
Relatedly, Benbow and collaborators also found that children who scored high on verbal and not math have greater social maladjustment than those who score high on math and not verbal (don't have the references immediately on hand, can dig them up later if you want.)
Thanks, fixed.
Thanks, this is great advice.
Probably better to send me private messages via the LW interface then rather than communicating by email them - do you know how?
Thanks for the suggestion.
The actual situation is that over the past 3 months I've had a cluster of insights that's extended far beyond math education as typically conceived, and I think that I've finally uncovered a road forward for people in our reference class to (as a group) increase our productivity by ~100x+. (As a point of reference, Bill Gates makes ~$10 billion a year: that should make the factor of 100x less far fetched.)
There are so many things to say that it's difficult to know where to start. I have ~500 unpublished pages on the subject, but a lot of it is in the form of correspondence and so not easily shared in its current form.
May I asks what your own situation is, so that I can better address it? Feel free to email me at jsinick@gmail.com.
I know that the content itself is clear. The main thing that I need to work on is making my writing more engaging to a broader audience. If the writing isn't appealing enough to motivate people to read carefully, I'm not going to get through to them :D. I think that Scott Alexander / Yvain would do a better job than I can. I don't expect to be able to get up to his level, but I hope to move in that direction.
Thanks.
I know that I'm actually far above average after controlling for the complexity of the material that I'm trying to convey, but nature doesn't grade on a curve: it's not enough to be at the 99th percentile of academic mathematicians to actually successfully convey ideas to a broad audience of people without technical backgrounds :D.
I'm glad that you're understanding what I'm writing, but as a practical matter it seems as though I've been failing with > 50% of those who I've been trying to reach.
I was speaking figuratively / poetically. If I can disseminate what i know to 100 people I'll be happy, though I hope for more, and it might prove to be unrealistic.
Oh, sure, I know that, I have a very long ways to go. What I meant to convey was that I already have a lot to work on with written communication alone :D. But I am in fact spending more time talking with people in person as well, just only have so much time in the near term...
Thanks.
There are meta-principles that are relevant to learning how to communicate with any group of people, that I'm just starting to learn. Reaching the LW community would be a great starting point, but only makes a small dent in the general problem of knowledge of how to think about the world mathematically in general being very rare, in juxtaposition with the fact that far more people are capable of learning than are currently learning.
Thanks. The issues come across in writing just as much as orally – you've already seen them.
By "impact" I meant "efficacy of donating."