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Text content: five minute university | Locklin on science | Page 3                                                       Skip to content Skip to search - Accesskey = s  Locklin on science    The Birthday paradox as first lecture   		Posted in five minute university, fraud, statistical tools by Scott Locklin on February 15, 2024	  The birthday paradox is one of those things that should be taught in grade school to banish superstition, bad statistics and mountebanks. Of course there are people who understand the birthday paradox and still consult astrologers, but knowledge of this fundamental idea of probability theory at least gives people a fighting chance. It’s dirt simple; if you ask people what the probability of there being a shared birthday in a group of n people is, they’ll probably estimate much too low. The probability of n people not having the same birthday is a lot like calculating the probabilities of hands of cards. You end up with an equation like the following:  n is number of people in the room, d is number of days in the year. Note that this generalizes to any random quality possibly shared by people. The probability of a group of people sharing a birthday is:  You can try calculating this with your calculator, but 365! is a big number, and we can use a little calculus to make an approximation:  From here, anybody should be able to plug 365 in for d, then make the probability 50%, and get a solution of around 23 people; a counter intuitive solution. Probability with replacement works like that; coincidences like this are much more likely than our naive intuition  implies. The naive intuition is  you need 180 people in a room to have a 50% chance of shared birthday. I guess most people are narcissists and forget other people can have matching birthdays too. Probability theory is filled with counter-intuitive stuff like this; even skilled card players are often terrible at calculating real world odds involving such coincidences. Aka, if it’s a joint probability you’re probably calculating it wrong. If it’s something in the real world, it is defacto joint probability, even if you don’t think of it that way. For the mathematically illiterate, . Thinking about what this (the factorial) is doing; the first guy has to compare himself to n-1 people, the second n-2, the third, n-3 and so on. Another way to think about it, there’s a 1/365 chance of you sharing a birthday with anybody. So, 364/365 of not sharing. You should be able to hand wave your way around that. You can take my word for the calculus approximation (google Stirling’s formula if you want to know more). If you stop to think about it a bit, the paradox is worse if you have an uneven distribution of probabilities for birth dates (aka more people are born in October or something), and of course is much worse if there are fewer possibilities (aka most things in life have fewer than 365 possibilities). Really they’re the same thing: uneven distributions are like removing possibilities. The human mind is designed to match patterns; to ascribe meaning to seeming regularity. “Coincidences” such as the birthday paradox are like crack cocaine to the brain’s pattern matcher. The ancients had their books of portents, actions of birds and animals, liver condition of sacrifices to the Gods.  The reality is, the bird livers had a very limited number of states; vastly more limited in distribution than 1 in 365. So of course you’ll see a lot of seemingly convincing coincidences. You’ll also forget about it when liver-divination doesn’t work just as you would with astrology or tarot cards. The ancients weren’t stupid, even if they never invented probability theory, and supernatural explanations seemed natural enough at the time, so all of this was convincing. Very intelligent people, even scientists, are just as subject to this sort of thing as anyone else. There are a couple of books out there about the correspondence of Wolfgang Pauli and Carl Jung about what they called “synchronicity.” This is a two dollar word for noticing coincidences and ascribing meaning to them. Mind you Pauli invented large parts of quantum mechanics and was one of the most intelligent and famously bloody minded men of his time (Jung was more of a nutty artist type), yet he still fell for what amounts to a version of the birthday paradox, combined with an overactive imagination.  Pauli was considered the conscience of physics; less charitably, he was called the “wrath of God;” he’d regularly chimp out at physics which was even mildly off. You can sort of understand where he was coming from: physics represented stability to him in a crazy time of Nazis and Communists. He even had to put up with his mother killing herself: something he did by taking up with a chorus girl and recreational alcoholism: Pauli was the most punk rock of early quantum mechanics. He made up some vague hand wavey bullshit about quantum entanglement which is possibly also a mystical bullshit concept in itself, because many of the early quantum mechanics found themselves in similar circumstances. I know I’m more prey to mystical bullshit when hungover or otherwise in a psychologically fragile state. Mind you this is a guy who would chimp at other physicists for leaving out an  from an equation. This bullshit got me lurid romantic encounters with countless goth girls and strippers while in grad school: thanks science bros There is something used by confidence trickters and stage magicians practicing mentalism related to this; in a group of people, getting an impressive cold read on one of them is pretty trivial. Fortune tellers, astrologers, occultists and quasi-religious entrepreneurs of all kinds use this technique. You use likely coincidences to build rapport until the mark is cooperating with you in playing psychic man, and basically giving the answers with body language and carefully constructed questions. People have no conception of how probabilities work, so they practically hypnotize themselves when one of the mentalists “I see a woman in your life, an older woman…” patter strikes home. There are plenty of numskulls who believe in such nonsense without overt mountebanks misleading them: turns out people who demonstrably suck at probabilistic reasoning are likely to believe all kinds of stupid nonsense. If you work in statistics or machine learning, this sort of thing is  overfitting. All statistical models and machine learning algorithms are subject to this. For a concrete example, imagine you made multiple hypothesis tests about a piece of data (machine learning is essentially this, but let’s stick with the example). The p-value is defined as the probability for your test being an accidental coincidence for doing one hypothesis test. You see where I’m going here, right? If you do many hypothesis tests, just like if you do many comparisons between all the people in the room, the p-values of any of them are not estimated properly. You are underestimating the false discovery rate, just as you are underestimating the birthday group probability: the combinatorics makes coincidences happen more often. The very existence of this problem escaped statisticians for almost a century. I think this happened because statistical calculations were so difficult with Marchant calculators and human computers when Fisher and people like him were inventing statistics as a distinct branch of mathematics, they’d usually only do one estimate, which is what the p-value was good for. Later on when computers became commonplace, statisticians were so busy doing boatloads of questionable statistics in service of the “managerial elite,” they forgot to notice p-values are underestimated when you’re doing boatloads of questionable statistics. Which is one of the reasons why we have things like the reproducibility crisis and a pharmacopoeia that doesn’t confer any benefit on anyone but shareholders. Now at least we are aware of the problem and have various lousy ad-hoc ways of dealing with this issue in the Bonferroni correction (basically you multiply p-values by the number of tests -not always possible to count and not great but better than nothing), and the Benjamini-Hochberg procedure (a fancier version of Bonferroni). There are other ideas for fixing this: q-values and e-values most prominent among them; most haven’t really escaped the laboratory yet, and none of which have made it into mainstream research in ways which push the needle even assuming they got it right. The important takeaway here is very smart people, including those whose job it is to deal with problems like this, don’t understand the group of ideas around the birthday paradox. People in the sciences have called for the publications of negative results. The idea here is if we knew all the different things people looked at with negative results, we could weight the positive results with something like Bonferroni corrections (also that people who pissed up a rope with a null experiment get credit for it). Of course my parenthetical “it’s not always possible to count” thing comes into play here: imagine everyone who ever ran a psychology experiment or observational study published null results: which ones do you count as relevant towards the one you’re calculating p-values for? What if 10,000 other people ran the experiment, got a null and forgot to mention it? Yep, you’re fucked as far as counting goes. Worse than all this, of course, is the nature of modern academia is such that fraud is actively encouraged: as I have said, I used to listen to people from the UCB Psychology department plotting p-mining fraud in writing their ridiculous papers on why you’re racist or why cutting your son’s balls off is good for him or whatever. Trading algorithms are the most obvious business case where this comes into play, and there are tools to deal with the problem. One of the most famous is White’s Reality Check, which uses a sort of bootstrap algorithm to test whether your seemingly successful in-sample trading algorithm could have been attributed to random  chance. There are various other versions of this; Hansen’s SPA, Monte-Carlo approaches. None are completely satisfying for precisely the same reason writing down all the negative science experiments isn’t quite possible. If you brute forced a technical trading algorithm, what about all the filters you didn’t try? What do you do if you used Tabu search or a machine learning algorithm? Combinatorics will mess you up you every time with this effect if you let it. White’s reality check wasn’t written down until 2005; various systematic trading strategies have been around at least 100 years before and explicitly are subject to this problem. It’s definitely a non-obvious problem if it took trader types that long to figure out some kind of solution, but it is also definitely a problem.    The seven degrees of Kevin Bacon effect is the same thing, though “network science” numskulls make a lot of noise about graph topology: it doesn’t really matter as long as the graph is somewhat connected (yes I can prove this). Birthday paradox attacks on cryptographic protocols are also common. Probably the concept is best known today because of birthday attacks on hashing functions. It seems like humans should have evolved better probability estimators which aren’t confused by the birthday paradox. People who estimate probabilities accurately obviously have advantages over those who don’t. Someone wrote a well regarded book (which ironically flunked reproducibility) on this: Thinking Fast and Slow. The problem is that Kahneman’s “type 2” probability estimator (the one associated with conscious thought) is generally just as bad as the “type-1” (instinctive estimator) it derives from. The brain is an overgrown motion control system, so there is no reason the type-2 probability estimator is going to be any good, even if it involved a lot of self reflection. Type-2 thinking, after all, is what got us Roman guys looking at livers to predict the future (or Kahneman’s irreproducible results). Type-2 is just overgrown type-1, and the type-1 type gizmo in your noggin is extremely good at keeping human beings alive using its motion control function, so it’s difficult to overcome its biases. You don’t need to know about the birthday paradox to avoid being eaten by lions or falling off a cliff. But you definitely need to know about it for more complicated pattern matching.       63 comments       Various marketing hysterias in machine learning   		Posted in five minute university, machine learning by Scott Locklin on December 17, 2023	  One of the un-spoken of problems of the contemporary sciences is marketing and public relations disinformation. Even when it isn’t obviously done by someone bribing a journalist or paying a PR firm it is a problem. Noodle theory got a lot of positive PR from media and book-writers for decades, and probably wouldn’t have gotten as far as it did without this sort of self-referential attention. It’s not like people were writing popular books on condensed matter physics; half of the high energy stuff that works was stolen from condensed matter physics. Nobody cares about nerds fooling around with shittonium on silicon-111; they solve real problems -no glory in that when you can look into the mind of gaaaawd with noodle theorists. More ominously, many universities, individuals and research institutions employ marketing agencies to get their research to the attention of the general public. This causes many distortions in the marketplace of ideas. Students will go into fields based on marketing nonsense or pop science baloney: chaos theory had a popular book before I studied it in school. This wasn’t terrible for me: classical dynamics is a great subject, but it could have been a problem. Larval Locklin wouldn’t have known any better and blindly trusted that James Gleick knew what he was talking about (he didn’t). In ye olden days you’d hear about a piece of research if it was important. Now, you will often hear about research because someone payed a marketer to tell you about it. Or else a dumb journalist was fucking the researcher’s sister. I can think of a couple of examples of distorting marketing bullshit from my present work in statistics and machine learning. This is a comparatively humble and obscure field with pragmatic practitioners who care about good results. LLMs and autonomous vehicles ought to come to mind as the most obvious such memes as these things are obviously shilled beyond all reason by companies who hope to one day profit from them, hopefully by selling out to a larger company who is in fear of missing out. I assume by now that most of you have the good sense to laugh these to scorn as marketing constructions, but there are many more smaller scale distortions which I’ve come across. Facebook Prophet is one that comes to mind. I remember this being trumpeted to the skies as a fully automated “deal with any timeseries” tool which works “at scale.” I looked at it when it came out in 2017 and decided if I wanted a trend-GAM with splines, it was a one liner in R and whatever quasi-automated BS they came up with was probably only suited to counting keyword impressions on FB. People continually hounded me with this marketing crap, asking NPC questions like “why do you study timeseries models; FB prophet made them obsolete.” This is an actual statement I received from several people who are not obvious mental defectives and who were productively employed in the field of data science. This dumb model continues to occupy disproportionate mindspace: even current year 2023 you still get surprised blogs noticing that canned ARIMA smokes FB Prophet on run of the mill problems. People continue to publish peer reviewed articles like this, which is borderline absurd. Why not compare FB prophet to a one-liner trend-GAM with splines in R? I guess it is a nice to have tool for lazy morons, and GAMs are OK on this class of problem, but had they simply improved R or Python’s tooling for trendy-GAM models, rather than carving out dumbass-mind-space of its own, I wouldn’t mind so much. There’s nothing special or innovative about it.  I wrote a trend-GAM/seasonal thing for somebody which probably worked better for counting ad-word impressions because it pegged concepts to weird holiday seasonalities, which mostly dominate websites which are selling something. I don’t think Prophet can do that.  Shilling this very pedestrian time series model as something revolutionary makes its authors look like mountebanks. The only way the world can heal is if we make fun of these swindlers for making their ridiculously generic models out to be something innovative or even particularly useful. Facebook prophet; also good for scalp health Another one which came a few years before was MINE. I remember it was from a bunch of MIT and Harvard dorks, and I remember someone pushing it hard as if it were the discovery of some new and wonderful thing, rather than a weaksauce turd which apes mutual information or distance correlation and takes a hell of a lot longer to calculate. It stands out in memory because I had to fuck with classpaths to make it work, but the all consuming hysteria around it was really something too. I also recall being extremely annoyed it’s no different from any other kind of Mutual Information or distance correlation tool which has existed from the time of magnetic core memory and vacuum tube CPUs. 12 years later, it is obvious now that it was a giant nothingburger. Nobody uses it. It never solved any interesting previously unsolvable problem. I’m not sure if the people responsible for it pushed it with a PR campaign funded by themselves, or if it was MIT. I suspect a little of both, since the website for it is still up. It was touted as being appropriate for “large datasets” but it sure chugged hard on small ones. Looking up the dudes who thought it up, one of them publishes lame papers on stats at MIT, the other has a Soros scholarship to become a doctor. They’re both MD/PhDs and don’t do much to improve my modest disdain for such people (I know of only one good one). SAX and the various doodads Keogh comes up with also harsh on my mellow. I was  excited by SAX when I first became aware of it. SAX is similar to an idea of my own creation.  I thought a professor of whatever like Keogh is might have had some motivating reason to do SAX the way he did instead of equal width buckets or kmean-trees or whatever. If there was such a reason to use SAX over any of the numerous other arbitrary methods, I am unaware of it. There are numerous other things which work like SAX. But look at the testimonials! The home page for SAX reads much like the testimonials for questionable nutritional supplements in form and function. In actual fact, SAX is a sort of histogram which allows you to represent the timeseries as a string. In other words it is simply discretization. For timeseries you’re generally only interested in some sort of longer term behaviors; most of the data points are redundant and polluted with uninteresting noise. Filters are one standard way of dealing with the noise; only keep the frequencies you’re most interested in. Putting the data points in buckets is another sort of filter which has interesting properties. Once you realize you’ve reduced your timeseries to a sequence of symbols (something you can’t do with filters; you need a discretization technique), you can then apply the numerous techniques associated with strings of symbols. This isn’t a big insight: I managed to have it on my own when working with Mutual Information as a variable selection technique. You can then use classic autocomplete doodads like Tries or bag of words to do predictions or look for motifs or whatever. Keogh makes a big deal that his discretization technique is bounded by Euclidean distance, but, like, who cares? If you fuzz the data into enough buckets…. of course it is bounded by Euclidean distance. In his original paper and marketing materials he also compares his invention to wavelets, DFT and piecewise linear approximations. This is nonsense. Wavelets and DFT move the problem into frequency space and are not discretizations. Piecewise linear solves another problem; it’s more like a weird filter to capture short term trend. Discretization is of course very different from these techniques, but the particular SAX discretization isn’t a unique or interesting way of putting the data into discrete buckets. It is just one of zillions of potential ways of doing this. The marketing website for SAX spurred all kinds of SAX papers using various kinds of symbol predictors, variations of SAX with slightly different properties. If he had simply said “use a histogram” like people have literally been doing since the 1960s (and probably before), nobody would ever have heard of it. Keogh’s histogram remedy Information geometry; I don’t think this one ever rose to the level of marketing hysteria, but it seemed like a lot of people were touting it for a while. I read a bunch of books on it (basically, all of them), looking for something that resembled an application. The most I was able to come up with was fiddling with Hessians in doing likelihood on weird functions. I guess this is OK, but in general it seems like you shouldn’t do likelihood on weird functions; you should use better functions or empirical likelihood. I have yet to figure out why people sperg out on it so much, and I don’t actually know enough differential geometry to say anything authoritative, but it smells like wankery. For contrast, I have done useful things using TDA, though most of them could have been done some other way. It’s possible IG is like TDA, potentially useful if you know it already, but you could just solve the problem another way. Genetic algorithms are a marketing hysteria from before my time. GA are a technique for searching a space; a gradient-free optimizer. The field is called metaheuristic optimization. It’s cute they use quasi-evolutionary techniques to segment and search the space, and they can occasionally produce better answers than the much older simulated annealing techniques. There are many alternatives; particle swarm optimizers, differential evolution, quasi-newton, tabu search, ant colony optimization. In my experience they’re all essentially the same; if you’re out on a limb where fiddly little differences between them matter, you’re probably doing something wrong. I generally just reach for differential evolution because the constraint handler is clean. There is nothing wrong with GA. Other than the fact that they seemed to dominate the literature back in the 80s and 90s. There were startups based on GAs back in the 80s, and they probably blew part of their budget on marketing, so people attributed magical qualities to this optimizer as opposed to, say, tabu search, which is of similar vintage. People really did solve problems with the tool, but it’s not clear they couldn’t have solved the same problems with any number of other tools. This is somewhat like SAX -an arbitrary solution, puffed up in importance by marketing budgets. Many of the kinds of problems solved by GA and friends fall into the NP-complete bucket, so I guess people could have become over-impressed with the sayings of computational complexity theory nerdoids (my opinion of them), but there are many such tools and people only got excited about GA. It wasn’t because it was first! GA is good for what ails you Things I’m leery of, but haven’t thought deeply about: SHAP (looks ad-hoc; many such techniques without the hysteria), matrix profiles (because Keogh basically), EMD (there’s lots of ways of doing blind source separation: non-negative matrix factorization is the real trick), DTW (probably has its place but seems over-referenced) anything Julia related (dorks) …. feel free to make additions.     49 comments       Chesterton’s fence applied to the engineering of physical objects   		Posted in Design, five minute university by Scott Locklin on June 13, 2023	  I like nice things. By nice things I don’t mean the most expensive things, though sometimes the nicest things are the most expensive.  I want all objects within my purview to have good design and durability. Why should I have to buy an object multiple times because it was poorly made? I know planned obsolescence and the cheapest possible product are the rule of the day, but on a long time scale, assuming humans don’t go extinct, disposable and poorly made objects will be viewed with disdain. Assuming “sustainability” isn’t just a stupid virtue word, not making junky objects that fill up the ash heap seems like an important part of it. Even if it is a stupid virtue word, it’s designed to appeal to rich white people like me so I’m going to talk about it. I first came across the idea of “buy it once” after buying a nice umbrella: one that manages to fit in my pants pockets. Umbrellas are objects generally made badly. They’re also things generally made too large; and when they’re a certain size, they’re small enough to not notice, so it’s easy to leave them behind by accident. Pocket size, you’d have to be an asshole to lose it. It really hasn’t given me any problems in a decade of hard use. Granted it was $50, and I have no idea if they’ll continue to make them, but this is the kind of thing I mean. This one I spotted on the lifetime guarantee: it’s pretty good insurance against it being a piece of crap, but I bet some management consultant MBA weasel with a spreadsheet could come up with an argument that selling cheap shit which will break and bankrupting the company will make someone more money.  I won’t go into too many details of why it works so well; they used good materials and engineering design, and left out useless bullshit like “auto opening” springs. Probably they just copied some old umbrella made 100 years ago. High quality objects like this umbrella exist, and I like owning such things. My ancient x220 thinkpad is such an item. While I’ve upgraded it with spare parts over the years enough it’s sort of the same thing in a “Ship of Theseus” way, the monitor and chassis are all original equipment, used daily since 2011. I sometimes contemplate upgrading to a new one, but there is little reason to do so. The modern chips have video decoder stuff baked in and it will have 16 threads instead of 4. Modern chips are  …. about 1.4 times faster per thread. A new thinkpad will also have a better screen, and won’t require a bit of scotch tape to hold the battery to the chassis. A new thinkpad will also have a much worse keyboard, and it won’t have the cool-ass thinklight. It will also have NSA spyware I can’t turn off. So fuck getting a new thinkpad. 1.4x on a thread is meaningless; the keyboard is way more important, and I have stockpiled enough parts for my x220 on multiple continents to keep the thing going for the rest of my career. 16 threads can be useful. When I need that, I can run the code on my desktop machine which has 64, all of which are considerably faster than laptop threads. Amusingly x220 I7 thinkpads with IPS screens are now increasing in price, because there are a lot of people like me who realize what’s important in a development machine. They’re still only a third or so of what a new Ryzen-7 one would cost, but my stinkpad might end up an appreciating asset in the long term: heck it’s already appreciated to 2/3 of what I actually paid for it back in 2011. Cold dead fingers Another such object  is an Armin Trosser coffee grinder I got from my Stepdad. It uses burrs adjusted for drip coffee, which, as an american, is my preferred wake up rocket fuel. It’s made out of steel and chunks of wood and has been used almost every day since it was bought in 1950s. Apparently it can be adjusted to grind finer; I haven’t bothered to do so. I don’t know what the mean time to failure on something like this would be; it appears to be immortal. The metal parts are thick. The wood parts are beefy hardwoods. I assume when it eventually wears out the wood will dissolve somehow, but it shows no signs of doing so. People copy the form of these things out of nostalgia, but nobody actually makes anything like this any more. In my ideal society, everything would be made like this, rather than making things out of shabby plastic and particleboard.  Which brings me around to Potempkin luxe. I have in the past used Zero-Halliburton aluminum cases to protect musical instruments and keep sensitive electronic equipment. The legend is, Halliburton used to airdrop stuff to its staff at oil wells, and so they designed very rugged aluminum cases capable of withstanding the abuse. I never had one of their briefcases until a few months ago. I do have a case based on the same shell as its contemporary 90s era briefcase which I keep sensitive electronics in. Got a suitcase I keep bagpipes in as well. Mind you it is a very try-hardy briefcase: I ordered it after a few too many glasses of wine and a James Bond marathon. My old ZH cases I bought used; they were absurdly sturdy. The new one is crap. I show you why, and tell you how I think they went wrong. Here is a comparison of new and old from the front:     Here is a comparison of new and old from the back:   Give them a good looking over and tell me where you think they went wrong/right on the new design. I’ll wait. So the first thing that should occur to you is to wonder where the polished steel clasps went. Those were long the defining characteristic of the brand. When you flipped them bad boys closed, the thing was sealed. ZH cases have this sort of tongue and groove thing that generally has a rubber gasket and in principle make it truly waterproof; including my brand new one. The ones with the clasps closed so tightly that it felt like it could be waterproof without putting a rubber gasket in it; never thought to try, but I’d have believed it if you told me. However because the new case lacks the clasps, this expensive tongue and groove thing around the shells is useless: between the flimsy “no sealing power” fastener and the lack of torque compensating hinges going across the bottom of the thing (two hinges < one big one). You’re lucky if your pencils don’t fall out of your briefcase if you shake it around. It gapes most embarrassingly when you have something substantive inside it, because, like, torque is a thing that applies even to ZH briefcases. This is truly astounding and I can’t believe they sell these things: had I seen it in person rather than having someone send it to my office, I’d have laughed uncontrollably at it. There are other differences. They make a big deal out of the innovative corner protectors. It is a common blemish on old ZH cases that the corners dent. I never really cared; long before that happens, the thing would be ooogly from scratches anyway. All that means is you had some experience: after all the goddamned things main responsibility is protecting the gold bars or nuclear codes or fine vintage x220 laptops or whatever is inside it. The contemporary one couldn’t even protect my laptop from a garden hose or mild drizzle. I’m certain if I dropped it from a moving airplane it would just explode into two clamshell pieces, because there is practically no physical matter holding it closed. Plastic versus aluminum feet; I assume to not scratch floors; still lame and definitely more fragile than the old aluminum bumps. The new handle is actually cooler than the old one. If I had to guess how this happened, the clasps were probably made by some outside contractor that died or went into another line of business. They were very well made; high tolerances and fine finish. Sourcing new ones would have been expensive and time consuming. I also guess that some of the more fastiduous customers wondered what the double clasps were for, and thought it pretentious to have to ostentatiously flip them open to a loud clack every time they open their briefcase. Mind you, you’re carrying a fucking $500 briefcase made out of metal that looks like it is out of a James Bond movie, but I guarantee some nitwit with plastic surgery said something about that. Finally there is the ever present urge to “update” things; to prevent them from being “tired.” The old case design really didn’t need any updating. It worked great, and all the design features  combined to a useful and well-made whole. The giant monolithic hinge of the past certainly looked kind of weird and stodgy 50s era, but it served a real purpose. The original ZH functional design had several such Chesterton fences in it. All you needed to do to notice something is wrong with the new design is walk around for a few minutes with something inside it more substantial than a few pieces of paper. I have no idea what to do about it: returning such things by mail is a super annoying process and for all I know won’t get me anywhere. Probably I will rivet some vintage or machined parts to the thing to see if I can approach the old standards.       54 comments       Silly Con Valley Camp Followers and other Weirdos   		Posted in five minute university, fraud, fun by Scott Locklin on April 14, 2023	  I remember sitting in the Berkeley City Club with my former business partner and kicking the can on weird ideas for making a dollar. One of the ideas I raised was writing the great american silly con valley novel. Lawler rightly pointed out that the TV show Silicon Valley had kind of nailed it. I hadn’t seen it at that point, but indeed from what I’ve seen they did nail it. The characters on it are all people I know, including myself (Gilfoyle), and the situations are very SV. The SV characters portrayed in the eponymous TV show are weird and worth showing to the rest of the world.  But there are many other categories of Silly Con Valley people, and they’re absolutely hilarious and ripe for some kind of dramatic portrayal. The Silly Con Valley Camp Follower is among the most egregious and hilarious of such archetypes. The only person I’ve ever noticed call them out is Steve Sailer, who politely calls them “Silicon Valley Adventuresses.” The most famous exemplar of which is Ellen Pao. Lest anyone has forgotten: Pao slept with her boss at a VC firm and got buttmad this didn’t immediately improve her career and sued the firm over it (and lost). She later licked her wounds by marrying fellow grievance monger and shakedown artist Buddy Fletcher; apparently also cruelly subjecting him to gay conversion therapy in the process. Pao is a very high profile example and peaking in life by being so incompetent and clownishly evil she fomented a genuine workers revolt among Reddit employees. Up to this point, tech employees had only made noise when their company is insufficiently woke: in this case they actually protested woke working conditions. This is a considerable achievement on Pao’s part. She easily surpassed the concept of “camp follower” or even “adventuress” -she’s practically an adjective of her own. I mean, look at the jawline on this woman: Chad genetics Most Silly Con Valley Camp Followers are neither this egotistical nor unpleasant, but the basic strategy of profiting from fucking Mr. Big is the same. The fact that “Mr. Big” types in the Valley aren’t as obvious as they might be in NYC is the source of much hilarity (Pao’s “romance” with the wrong dude for example) and makes up the majority of the substance of the dramatic arc of their adventures. Their stories should be told. It is the type of thing that people used to talk about. Jane Austen style novels for 21st century SV Camp Followers would be amazing (I’d settle for Tom Wolfe). It’s incredibly funny to watch it happening, and of course incredibly demoralizing if you have to clean up after one of the less competent ones who have girlboss delusions of competence. The SV Camp Follower is one of those pervasive things, like the favelas of drug addicts and schizos in American cities that polite people are supposed to pretend is something else, or ignore completely. Once in a while someone admits something: highest profile recent example was founder Perri Chase who admitted she boned an investor and felt bad about it. Someone on Quora asked about boffing investors (after all, most of them are fucking you already). Womens magazines occasionally mention it in a general sense, but mostly sleeping with the boss in return for career favors isn’t mentioned by polite people any more. Of course those of us in the know can simply pick them out of lineups of, say, Forbes 30 under 30s. I know one of them, can guess a few more   Divorce tick types who hope to profit from a marriage by plundering their ex husband’s assets are a somewhat different but related phenomenon. They achieve their “success” the old fashioned way: by taking half their nerdy ex husband’s stuff. They are fun to watch in action and they generally dress up nice. Succubi are usually obvious and easily avoided by non masochists. It’s pleasant to have an attractive trophy GF or whatever, but don’t marry women with extensive plastic surgeries (saline-bag tits, fish lips, botox) who has no real interest in you, your hobbies/ or career, who wants an “open relationship,” who has a bunch of divorced/whore friends and probably has a job like actress (whore) or model (whore). The divorce tick succubus is such a normal facet of American society,  it seems like there should be some kind of archetypical fictionalized portrayal by now.  Typically the Silly Con Valley succubi only need one good divorce, due to the particulars of California Divorce law. Gentlemen take note: California divorce law makes the male divorce tick a possible career path. A lot of Camp Follower antics, like Miz Chase mentioned above, are sort of situational. Fuck the connected guy to get access to his connections to find more important dudes to fuck to get …. whatever career favors or series-b guy introductions they’re seeking. In my observation they’re not too unpleasant unless you happen to have sex with one of them and not be immediately forthcoming with  the favors they require. Or (in my actual experience) if they come at you and you refuse to engage; then they’re annoying as shit.  Due to female ego fragility, they always think it’s because you are an emotional toddler who can’t take a hint. This is probably a reasonable assumption in le sperdo land, but it is not the only possibility. For example: foresight, aesthetic sensibilities, a preference for dongs or general disgust with sociopaths. This sort of miscommunication can result in comical (and, yes, annoying as shit) escalation on their part. I suspect a lot of these get their start in college getting nerds to do their homework for them. Such women certainly do this when they land in engineering roles, which, to be fair, is reasonably good practice for management assuming they don’t actually suck their boss’s dick in the process. The worst though, are the ones in your chain of command. Some middle manager, investor, advisor or whatever got his sperm spittoon hired into an important role in your firm. Or worse, you’re a middle manager, investor or advisor who some wannabe girlboss has ascertained can get her a job suited to her ego by allowing you access to her wet spot. In the former situation, you’re saddled with an incompetent: usually in the product management role. In the latter case, who knows what they’re capable of: I’ve never been interested in finding out, though I have been important enough to be pitched on such things.  I think workplace romances are normal if ill-advised. People thrown in close proximity tend to hook up more than people who don’t know each other at all or meet each other in some lame-ass “app.” Also, women are more attracted to the boss than the cleanup guy: hypergamy complicates things. Workplace romances are generally a bad idea unless you are planning a change in employer. Everyone knows a boss fucking his underling is an ethical breach. Generally it is considered an abuse of power by the boss. Nobody ever talks about the ethics of the sociopathic woman hurling herself like a flesh-missile and impaling herself on the boss, but everyone knows it’s a real thing.  Thirsty spergeloid gentlemen: the way you figure out if she’s fucking you for a promotion is she’s your underling, you’re having sex with her or she has hinted at the possibility, and she is asking you for a promotion, or has stopped doing useful work. I know, emotions and motivations are so hard to read in others; make a checklist. Speaking of autism; one might wonder why more honest women don’t call these broads on their shit. All women are adept at making other women feel sorry for them: probably dates from some hunter gatherer thing -you have to figure sociopaths who sleep with men for profit are particularly good at this. Either way, since more honest women never call out sociopathic women on this crap, and you have to wonder at their collective judgement in general. There’s a famous historical example of precisely what I am talking about. Not quite silicon valley stuff, but definitely tech business: Margaret Hamilton.  Miz Hamilton was a reasonably talented person; she worked on SAGE,  she worked on the moon navigation stuff as an individual contributor, and she did a couple of startups nobody ever heard of after leaving NASA. However, and they always leave this out of the official hagiographies, she did fuck the boss (she eventually married him), and that’s almost certainly why she was promoted to leadership, and definitely why she left her previous husband. Some anon wrote about it; I think he goes too far, but he might be right in all details, and it is certainly worth noting that this lady superhero girlboss of computard got her high position at least in part by fucking the boss. None of this stuff is a secret: she talks about it in the historical documents. The annoying thing about all this is she seems to be given full credit for the work of hundreds of men (she was the only woman), and nobody ever mentions the fairly important fact that she was fucking the boss, a la Helen Gurley Brown. Miz Hamilton I have no evidence she was a bad manager, and perhaps her promotion via seducing the boss was good for the effort as a whole, but very often, fucking the boss and getting the promotion is not good for the effort as a whole. It is at the very least as unethical and immoral as other forms of nepotism. I am of course a terrible person for noticing this, but it’s a good historical example of the kind of bullshit and happy talk that infests the upper middle classes who go into transports about people like Miz Hamilton, leaving out the grubby and ignoble parts. These grubby and ignoble parts matter: they make people miserable and occasionally cause entirely avoidable disasters. It’s probably impossible to spot these kinds of people if you’re being hired into a management chain, but easy to spot if it happens on your watch. It’s also easy to spot if you’re in the crosshairs and not a moron. I’m willing to bet that women who do this on purpose (they’ll always claim it was an accident -as if they just slipped and fell on their boss’s schween) have subreddits and forums to trade tips and intel. Other kinds of prostitutes do. Someone should investigate and tell me about it.     37 comments     « Newer Posts — Older Posts »    About me:  Stuff I like The Futurist Manifesto About Scott Locklin   Past blogsPast blogs Select Category astronomy big machines Book reviews brainz chaos Clojure cold fusion Corliss corona-chan Design econo-blasphemy econophysics energy finance finance journalism financial patents five minute university fraud fun Gambling systems Genetic data health history history information theory investments J Kerf Locklin notebook Lush machine learning manhood metalshop microstructure models nanotech non-standard computer architectures Open problems patent law patents patrician-entertainment philosophy physics physics anomalies privacy Progress Q reviews SBIR semantic web statistical tools stats jackass of the month systematic trading tools Uncategorized War nerding Wolfram Alpha   Email Subscription   Enter your email address to subscribe to this blog and receive notifications of new posts by email.   						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