What does “algorithmic ranking” bring to mind for you? Personally, I get visions of political ragebait and supplement hucksters and unnecessary cleavage. I see cratering attention spans and groups of friends on the subway all blankly swiping at glowing rectangles. I see overconfident charlatans and the hollow eyes eyes of someone reviewing 83 photo she just made her boyfriends take of her in front of a sunset. Most of all, I see dreams of creative expression perverted into a desperate scramble to do whatever it takes to please the Algorithm. Of course, lots of people like algorithmic ranking, too. I theorize that the skeptics are right and algorithmic ranking is in fact bad. But it’s not algorithmic ranking per se that’s bad—it’s just that the algorithms you’re used to don’t care about your goals. That might be an inevitable consequence of “enshittification”, but the solution isn’t to avoid all algorithms, but just to avoid algorithms you can’t control. This will become increasingly important in the future as algorithmic ranking becomes algorithmic everything. Why algorithmic ranking is bad for some people sometimes You’ve heard it all before. I think algorithmic ranking leads many people to spend time and emotional energy on things they’d rather not spend them on. I also think it leads lots of people to believe preposterous bullshit promoted by charismatic charlatans. I’m disturbed when I see how kids interact with addictive algorithms, but then I notice that adults are much the same. You know the story. A common defense of algorithmic ranking is that “your feed is your problem”. If you’re getting political ragebait and unnecessary cleavage, then that’s on you for engaging with that stuff. If you actually cared about the things you pretend you care about, everything would be fine. The problem is looking you in the mirror. I find this defense bewildering and almost hostile. I mean, where is it spelled out how you’re supposed to behave to get the content you want? Maybe there are little like buttons, but what do they do? How do they interact with all the other signals, like what you watch? It’s unclear. Now, I’m sure that many of the people who complain about ragebait and cleavage are in fact drawn to them in some way. Maybe they don’t swipe away fast enough when that stuff is inserted into their endless content trough. If they only had eyes for philosophy lectures and meditation videos, maybe that’s all they’d see. OK, but so what? Where’s the empathy? Everyone has some divergence between the urges they feel and the urges they wish they felt. We don’t judge alcoholics who throw away their booze. We don’t make fun of gambling addicts who avoid travel to Vegas or Monaco. So why is it wrong to not want lurid but unhealthy content dangled in front of you? One of the fundamental arts of being a human is using your “better self” to try to control your “lesser self”. You can put a giant calendar on your wall to track when you exercise. You can keep junk food out of your home. You can write your algorithmic ranking manifestos using an app that permanently deletes everything if you stop typing for 5 seconds. These tricks are good. We need more of them! Algorithmic ranking—as we know it—is the opposite. So what would I propose instead? How about… sliders? Why can’t I click a slider to say “more educational content” or “less political rage” or “no David Sinclair-esque supplement huckster bullshit”? Or how about an algorithm that just does what it says on the tin? Remember, YouTicBooX might let you “like” stuff, but the algorithm’s goal isn’t to show you stuff you’d like. The goal is to make money. Your likes are just another feature to be integrated with the rest of your behavioral profile for increasing engagement and targeting ads, thank you very much. The algorithm is running on you, not for you. But what about the market? Another common defense of current algorithms goes like this: If they’re so bad, then why did they win? If people wanted sliders, they would have picked services with sliders. But they didn’t. Go make SliderTube if you want. No one cares. There isn’t some pent-up demand for algorithms that give more control to our better selves. Sometimes people also gesture at the tyranny of the marginal user. The idea is that, sure, power users like control. But where companies really compete is in the fight for the “marginal user”, the person who is almost ready to quit. This person only vaguely understands what a phone is, has never heard of “algorithms”, likes flashing lights, and has the attention span of a pissed-off chimpanzee. They will not tolerate any complexity, so all sliders must go. Sorry, power users. There’s clearly something to these arguments. But still: If your portal to the world is designed for the marginal user, surely you’ve gone wrong somewhere, no? What happened to Netflix? In the long-long ago, Netflix had star ratings. You’d rate stuff between 1 and 5 stars and get a sorted list of predictions: Chunking Express 4.49 Days of Being Wild 4.51 Solaris 4.57 In the Mood for Love 4.62 Master and Commander: The Far Side of the World 4.98 Nowadays, you get a disorienting set of categories like DARK COMEDIES ABOUT ITALIAN FEUDALISM and LIFE IS SHORT—WATCH IT AGAIN and THINGS YOU’RE IN THE MIDDLE OF, HELPFULLY PLACED IN A INCONSISTENT LOCATION. Instead of star ratings, there are “match percentages”, but you have to interact to see them and they always seem to be 98%. What happened? Well, the story is in the public record. (See, for example this post and this post by Gibson Biddle.) In short, Netflix realized a bunch of things: That they needed to concentrate everything on increasing subscriber revenue. And that the main goal of recommendations should be subscriber retention, or making sure people don’t cancel. That the things people rate highly aren’t always the same as what they actually watch. It’s cool that you gave The Seventh Seal five stars. But after a long day at work and finally getting the kids to bed, are you really going to choose Andrei Rublev over The Great British Bachelorette and the Furious 7? That to retain people, you need to get them started watching new stuff. Lots of people want to watch Friends, so Netflix will pay $100 million/year for Friends. But if you just join, binge every episode of Friends, and then cancel, that’s bad. However, if the Friends button were to—say—randomly shift around in the interface, maybe while hunting for it you’ll get hooked on some other (hopefully cheaper) shows and stick around longer. That beyond your explicit ratings, there are lots of implicit signals like what watch, what you click on, what devices you use, and how long you stop scrolling when shown different kinds of thumbnails. These implicit signals are more useful than explicit rankings when predicting what to show you to keep you subscribed. That many people don’t want to rate stuff. And (I speculate) that this provides a convenient excuse to drop the whole star rating system and replace it with the “whatever the hell order we want” system that prevails today, where the match % means nothing and promises nothing. Netflix could have kept the star ratings as some kind of optional feature for the nerds, hidden away in some dusty submenu. But they didn’t. They 100% killed the star ratings for everyone. Why? I guess maintaining features takes work. But mostly I think they figured that most star rating diehard wouldn’t actually quit the platform. They’d grumble but accept the new system and thereby be Retained. And probably they were right. Now, I don’t mean to vilify Netflix. I mean, sure, it’s an amoral automaton doing whatever maximizes profits. But this is hardly the worst example of algorithmic ranking, and hey, this is capitalism! If Netflix tried to be “principled” and stuck with star ratings, maybe some other company would have displaced them? Don’t hate the player, hate the game? (Maybe don’t hate the game either?) What algorithmic ranking should be Let me summarize my argument so far: Algorithmic ranking as we know it is designed to maximize money for the companies doing the ranking, duh. That’s great if what you want is to be addicted or—more precisely—if your behavior happens to create incentives for rankings that are well-aligned with your goals in life. Otherwise, it’s not. Companies settled on these algorithms for a reason. It’s not because they’re evil, it’s because this is what’s profitable. If you accept all that, then what follows? One view is that this is further proof we must smash capitalism and end the malign power of the invisible hand. That’s intellectually coherent, but not my style. Another view is that, well, this is the outcome of the market. It’s pointless to fight the equilibrium, so we should just live with the algorithms. This is also not my style. A third view is that we must reject algorithmic ranking. Refuse to use any social media with algorithmic ranking. Subscribe to blogs using RSS. Install browser extensions that block YouTube’s recommendations. Chronological timelines only. Human curation only, forever. This third view is very much my style. One of the reasons I love blogging is that I can reach people without worrying about the damn algorithms. (Hi.) But I’ve come to believe it’s a dead end. After all, people like algorithmic ranking. Maybe with better interfaces or a bigger social movement, more people would shift towards human curation. But I suspect not that many, and the arc of history bends towards algorithms. And good algorithmic ranking—which you control—would be awesome. I mean, I appreciate that people subscribe to this blog. But I find it a little disturbing that if someone less well-known than me wrote the same thing, then many fewer people would read it. (I find it extremely disturbing that if someone more famous wrote it, then many more people would read it.) Yet that’s an inevitable consequence of relying on subscriptions instead of algorithms. This isn’t (only) an issue of vanity. I think it leads to an “invisible graveyard” of contributions that never happen. Say you’re a sane person who doesn’t want to spend hours every week writing for strangers on the internet. But maybe you’re—I don’t know—maybe you’re on the board of your local volunteer fire department. And maybe you have one sizzling banger to write about how local volunteer fire department boards should be organized. That information is important! Reality is fractally complex! But probably you won’t write it, because almost none of the people who’d benefit from it will ever see it. I think the solution is to embrace algorithmic ranking, but insist on “control”—to insist that the algorithm serves your goals and not someone else’s. How could that happen? In principle, we could all just refuse to use services without control. But I’m skeptical this would work, because of rug-pulls. The same forces that made TikTok into TikTok will still exist and history is filled with companies providing control early on, getting a dominant position, and then taking the control away. Theoretically everyone could leave at that point, but that rarely seems to happen in practice. Instead, I think the control needs to be somehow “baked in” from the beginning. There needs to be some kind of technological/legal/social structures in place that makes rug pulls impossible. What exactly should those structures be? And what exactly is “control”, after all? I don’t know! Those seem like difficult technical problems. But they don’t seem that hard, do they? I suspect the main reason they haven’t been solved is that we haven’t tried very hard. We should do that. And—I dare say—we should do it quickly. My guess is that algorithmic ranking will soon become a sort of all-encompassing algorithmic interface. More about that soon, but if all the information that enters your brain is being filtered by an algorithm, it seems important that you know the algorithm is on your side. Thanks: Steve Newman, Séb Krier

What is this? I am offering to act as a “mentor”, to you, in case that seems like something you’d find useful. How will it work? We will meet three times for 30 minutes. During those sessions, I’ll try to help you do whatever it is you’re trying to do. Then I’ll sit back and congratulate myself on everything you do for the rest of your life. Why are you doing this? It’s an experiment. I have a theory that there isn’t enough mentoring in the world, and that creating more mentoring might be an efficient step towards filling the universe with bliss-maximizing Dyson spheres. So I’ve decided to try this and see what happens. What topics are allowed? In principle, any topic. But I’ll probably be able to help you more if I have some kind of expertise or interest in whatever you’re trying to do. It could be anything related to statistics, science, AI, self-improvement, blogging, academia, writing, rationalism, (effective) altruism, air quality, the welfare of animals, or anything I’ve ever written about. Or it could be something else entirely. To encourage you to think broadly, I will try to pick at least one person with a topic not on the previous list. Who is eligible? Anyone. In particular, anyone at any age or career stage. But also the other kinds of anyone. What will it cost? Nothing. Is there an application? I have no idea how many people will be interested, but when scarce resources are given away, demand often exceeds supply. So there is an application, which is here: I basically just ask (1) what you want to do, and (2) how you hope I can help you. How many people will you pick? Three. If lots of people apply, I might try to recruit some other mentors. Or I might be lazy and disorganized and not do that. How will you pick? I will pick primarily based on how much I think I can help you and secondarily based on how much what you’re trying to do will advance the general welfare of the universe. I stress that the primary axis is primary! If you make a strong argument that I can help you become very rich or succeed in dating (unlikely) then I’ll pick you over some do-gooder that I can help slightly less. What makes you great that you can mentor other people? Nothing. Honestly, I could give you several reasons that I’m less than ideal as a mentor! But I suspect that mentoring is valuable enough (and undersupplied enough) that even less-than-ideal people like me can still be helpful. How will we meet? We will meet by video call using Signal. Will you share any details about me without my permission? I might write about the results of this experiment in general, reflecting on how it went, giving tips for other people who might try something similar, etc. The whole point of doing this is to experiment and understand if it works, after all. If you want me to share some details about you, I might. But I am very sensitive to privacy and I will not share anything (even broad details) without running it past you first and I’m extremely likely to agree to remove any information you ask me to remove, even if you’re being ridiculous. Is this a good opportunity to interview you or try to get you to go on a podcast, etc.? No. I will attack you.

(1) Jimmy Carter rabbit incident On April 20, 1979, President Carter was on vacation fishing in a pond in his hometown of Plains, Georgia. After returning to DC, he mentioned to some White House staffers that a large rabbit had swum towards him “hissing menacingly” and he’d had to scare it away. Four months later, press secretary Jody Powell—possibly after a lot of drinking—mentioned this story to Associated Press reporter Brooks Jackson, which resulted in this front-page article in the Washington Post: The country went crazy and spent more than a week mocking Carter for this ridiculous story—a story that Carter only mentioned in private, to his staffers, and which was apparently leaked to the press by Carter’s own press secretary. But Carter refused to comment. After Reagan beat Carter in the 1980 election, his administration found a photo taken by a White House photographer and—the rabbit was real: See also: Max Nussenbaum’s excellent review of Kai Bird’s biography of Carter, The Outlier. Note: the fate of the rabbit is unknown. (2) The voltmeter story Does it matter how information gets to you? For example, say a paper comes out that tries yelling at kids in school and finds that yelling is not effective at making them learn faster. You might worry: If the experiment had found that yelling was effective, would it have been published? Would anyone dare to talk about it? How much should you downweight evidence like this, where the outcome changes the odds you’d see it? If you’re a true believer fundamentalist Bayesian, the answer is: None. You ignore all those concerns and give the evidence full weight. At a high level, that’s because Bayesianism is all about probabilities in this world, so what could have happened in some other world doesn’t matter. The voltmeter story is an evocative tale where this conclusion seems intuitive and hard to avoid. But is it really always valid? I constantly see people who are enthusiastic about Bayesian reasoning argue in ways that are inconsistent with this rule. I’m not sure if that’s because they aren’t aware of the rule, or it’s because it’s a bullet they aren’t willing to bite (or both). (3) PROJECT XANADU® Founded 1960 * The Original Hypertext Project “Xanadu®” and the Eternal-Flaming-X logo are registered trademarks of Project Xanadu. The computer world is not just technicality and razzle-dazzle.  It is a continual war over software politics and paradigms.  With ideas which are still radical, WE FIGHT ON. I think this is some kind of way of… visualizing text? But communicated in an unusual way? There’s an example visualization, and—of course—a video narrated by Werner Herzog. I don’t understand what’s happening here, but I’m cheering for them. (4) Hierarchical Taxonomy of Psychopathology I often wonder if current mental disorders will still exist in 100 years. Will we talk about someone having “ADHD” or “autism”? Or will those be subsumed by some other classification? Doug points out this article which mentions the Hierarchical Taxonomy of Psychopathology. The idea seems to be that, instead of saying someone “is a psychopath” or “is not a psychopath”, you’d measure to what degree they have dozens of interrelated features of psychopathy: I have no real opinion about this but I suspect it gets at some deep issues about the meaning of science and human nature, so I’m hoping someone (Experimental History? SMTM?) will explain. (5) Slightly More Than You Wanted To Know: Pregnancy Length Effects Everyone agrees that pre-32 weeks is really bad, pre-37 weeks is pretty bad, and post-42 weeks is dangerous. In this post, though, I’ll focus on the sweet spot: the 37-41 week range. If you have a baby in this range, you’re basically in good shape, and should be grateful. But are you in slightly better shape in some parts of the window than others? Let’s find out. (6) The Yamasuki singers Speaking of parenthood, I’ve long been a fan of the 1971 album Le Monde Fabuleux Des Yamasuki, produced by Jean Kluger and Daniel Vangarde. This is a concept album, with “phonetic pseudo-Japanese” lyrics apparently written using a Japanese dictionary, and recorded with a children’s choir and a black-belt Judo master. It’s an frantic mixture of innocence and mayhem that doesn’t really fit into any existing musical genre, but I always felt that it shared some of the spirit of modern electronic music. I only recently realized that Daniel Vangarde is the father of one of the members of Daft Punk. (The robot with the grey head in Epilogue.) (7) Stopp, Seisku Aeg! Speaking of old music, Stopp, Seisku Aeg! is a song recorded by Velly Joonas in Estonia in 1983, apparently an arrangement of Frida’s I See Red. I was extremely suspicious that this song was some kind of retcon. It just seemed too good, too adapted to 2025-era tastes to have been made in the USSR 40 years ago. But as far as I can tell, it’s real and Velly Joonas is a public musician, painter and poet to this day. (8) What o3 Becomes by 2028 What can you predict about the future of AI if you take numbers seriously, in particular amounts of (a) money, (b) FLOPS, (c) data, and (d) energy? Seems like… a lot? This post should probably be mandatory reading for anyone interested in where AI is going. Short, but with exquisite information density. Despite the title, it’s almost all more general than just o3. (9) Obelisk (biology) You’re familiar with cells. (You’re made of them.) You’re also surely familiar with viruses, which are small bits of genetic code (DNA or RNA) surrounded by a protein coat. Viruses infect cells by having proteins on their coat bind to specific molecules on the cell membrane. Viroids are pieces of RNA that are similar to viruses but with no protein coating. All known viroids only infect plant cells. They are can survive without a protein coat because they have an extremely stable (circular) structure and often just rely on damage (e.g. from insects) to get into cells. Well, good news! We now have a brand new lifeform. Obelisks are viroid-like things that probably live in your mouth. Here, we describe the “Obelisks,” a previously unrecognised class of viroid-like elements […] We find that Obelisks form their own distinct phylogenetic group with no detectable sequence or structural similarity to known biological agents. Further, Obelisks are […] detected […] ~50% of analysed oral metatranscriptomes (17/32). Also: Given that the RNA sequences recovered do not have homologies in any other known life form, the researchers suggest that the obelisks are distinct from viruses, viroids and viroid-like entities, and thus form an entirely new class of organisms. (10) Alcohol and Cancer Risk You may have heard the Surgeon General recently warned that alcohol causes cancer. You, being a reader of this blog, are already aware of this [1, 2]. But the report is still worth looking at as an example of science communication. Here’s an excellent summary of the relevant mechanisms: (Mechanism D was news to me.) This summary of how much risk of cancer rises with alcohol consumption also deserves praise for being unusually non-misleading: While the upward-sloping arrows a bit much, this gets a lot of things right: ✔️ compares to base rate ✔️ shows absolute risks, not some screwy “percentage change in hazard ratio” nonsense ✔️ shows 0% and 100% ✔️ not horrendously ugly (If you’re wondering why the absolute risk of cancer is so much higher for women than for men, I think it’s mostly that men are at much higher risk of dying from other stuff like cardiovascular disease. You can’t get cancer if you die from something else first.) Most public health communication drives me crazy by being too “opinionated”. Are the increases from 16.5% to 21.8% for women or 10.0% to 13.1% a lot? Should everyone stop drinking? The right answer is to shut up and let the reader decide for themselves. It’s refreshing to see someone actually do that. Of course I don’t love the unambiguous causal language (“increases”) when it’s all observational data. But we have no choice but to rely on observational data since we can’t have nice things. Everyone complains when the government is incompetent. But it’s equally important to celebrate when the government gets things right. So to all the government employees who made this happen—well done. (11) Tyler John, back in 2022: I always tell my friends: it’s nothing, really. Don’t worry about repaying me. It was never about you anyway, you just happen to be among the most efficient means to filling the cosmos with bliss-maximising Dyson spheres. Really, I should be thanking you.

The Attorney General of Massachusetts recently announced that drivers for ride-sharing companies must be paid at least $32.50 per hour. Now, if you’re a hardcore libertarian, then you probably hate the minimum wage. You already disagree with this policy, so you need no convincing and we can part now on good terms. But what if you’re part of the vast majority of people who like the minimum wage? What if you think the minimum wage is awesome and you want to expand it? That’s fine. I won’t try to change your mind! But even so, there are strong reasons to be skeptical about this policy. Because: If you read closely, you’ll see that Massachusetts’ rule is that drivers must be paid $32.50 for hours that they spend driving passengers around. For the time they spend waiting for passengers to request rides, they will still be paid $0. And when you screw around with prices, you change the amount of time they spend waiting around. This kind of policy could help drivers. But if you analyze things carefully, it can’t help them very much. In the end, this policy is mostly equivalent to forcing riders to pay extra to subsidize drivers sitting around doing nothing. I’ll first give the intuition with words and drawings, and then I’ll prove it with a tiny bit of math. Story time Say there’s a city—call it Billiard Ball Falls—where people behave in suspiciously convenient ways. All rides take exactly one hour, including the time for the driver to get to the rider. And demand for rides is constant over time. Now, how many rides would you take if they only cost $1? Personally, I’d buy fresh produce and visit friends across town more often. Eventually, I might move further away from work. But if rides cost $1000, I’d only take them in emergencies. Assuming most people are like me, the total demand for rides from all people will decrease as the price goes up. Maybe something like this: Meanwhile, if drivers were paid $1 per ride, who would drive? Maybe a tiny number of very bored and lonely people? I certainly wouldn’t. But if I could earn $1000 per ride, I’d feel morally obligated to drive and donate much of the money to charity. So the total supply of rides from all people, is some kind of upward-sloping curve: In a free market, prices will—under some not-too-crazy assumptions—eventually settle at whatever price makes these curves intersect. Riders pay around $2.33 per ride and drivers earn around $2.33 per hour. A story as old as ECON 101. But we’re here to talk about something more interesting. What if the government mandates a new, higher, price? We have a problem. Since rides now cost more than the old market price, people will buy fewer rides. But since pay is higher, more people will want to be drivers. That’s not going to work. Riders can’t buy 300 rides per hour while drivers are selling 500 rides per hour. That would violate conservation of ride. Ordinarily, what would happen in this situation is prices would go down. This would cause drivers to drive a bit less and riders to ride a bit more and this would continue until the price went back to the market price. But that can’t happen when the price is fixed. So what happens instead? Well, demand can’t change. People will want to buy some number of rides at the government price and that’s that. In this situation, supply matches demand through a decrease in the utilization of drivers. Think of it like this: Prices are high, so lots of people want to offer rides. But there’s a shortage of customers, so drivers will have to wait around a while before they get a customer. Now there’s a subtle point here. (One that took me quite a while to figure out.) It’s easiest to understand with an example. Say the government mandates a price of $30 per ride and say drivers spend U=⅔ of their time actually working. Then the effective wage is $20 per hour, so people supply SUPPLY($20) hours of work. But only ⅔ of those hours actually become rides, so the number of rides supplied is ⅔ × SUPPLY($20). Get that? When drivers spend more time waiting around, this decreases supply in two ways. When drivers wait around, they don’t create any rides (duh). When drivers wait around, this makes their effective wage lower, so they drive less. If the government mandates a price of P and drivers spend a fraction U of their time waiting around, and you account for both of the above effects, the actual number of rides supplied will be U×SUPPLY(U×P). (Through the logic in the above example.) OK, so remember where we left our example. The supply curve SUPPLY(P) is the same as U×SUPPLY(U×P) when U is 1. What happens in this situation is that U decreases until U×SUPPLY(U×P) intersects with the demand curve at the government price. This happens to be when U is around 0.9, meaning drivers spend 90% of their time driving customers around and 10% of their time waiting around: Now what? Now we’re done. We just have to remember that the effective wage of drivers is government price times the utilization rate. In this case that’s around 10% lower: So, in this example, after the government increases prices: Riders pay more. Riders take fewer rides. Drivers spend more time waiting around. Driver wages don’t increase. Now, the effective wage usually will change, at least at little. It depends on the situation. In one extreme, people could be totally insensitive to prices. No matter how much rides costs, riders keep buying the same number of rides. And no matter how much drivers are paid, no one works more hours. In this case, forcing a higher price won’t decrease utilization—it will just transfer more money from riders to drivers. In the other extreme, people could be very sensitive to prices. When prices go up, riders cut back on rides and drivers try to work more. In this case, forcing a higher price will decrease utilization a lot and the effective wage might even go down. But how exactly does this work? In realistic situations, how much will a price increase actually help drivers? I’m glad you asked! Science time Humans encompass multitudes. There are infinite possible supply and demand curves. This complicates things for bloggers trying to disparage Massachusetts ride-sharing price minimums. So why don’t you just try it? Here’s a calculator. Enter whatever supply and demand curves you want, and how much the government will increase prices. It will then calculate the utilization rate and wage drivers earn at the new equilibrium. (You can use simple Javascript in your formulas, e.g. you can write W**2 for W² or Math.log(W) for log(W).) DEMAND(P) = SUPPLY(W) = Price increase (percent) = --> // Function to calculate the value of P where DEMAND(P) = SUPPLY(P) using the bisection method let timeoutId; function calculate(){ // Clear any previously set timeout clearTimeout(timeoutId); // Set a new timeout to trigger after 30ms timeoutId = setTimeout(function() { try { calculate0(); } catch(error){ if (error instanceof SyntaxError) { document.getElementById("result").textContent = "Syntax error! (Are you using valid Javascript syntax?)"; } document.getElementById("result").textContent = "Calculation error! (Is DEMAND decreasing? Is SUPPLY increasing? Are both are positive?)"; } }, 300); // 300 ms delay } function plot(DEMAND,SUPPLY,P1,P2,Pstar,priceRatio,U){ const canvas = document.getElementById('canvas'); const ctx = canvas.getContext('2d'); ctx.clearRect(0, 0, canvas.width, canvas.height); const xOffset = canvas.width / 2.5; // X-axis center (middle of canvas) const yOffset = canvas.height / 2; // Y-axis center (middle of canvas) ymax = SUPPLY(P2)*1.2; function moveTo(P,D){ const canvasX = 2*xOffset * (P)/(P2); const canvasY = yOffset * (2 - 2*D/ymax); ctx.moveTo(canvasX, canvasY); // Move to the starting point } function lineTo(P,D){ const canvasX = 2*xOffset * (P)/(P2); const canvasY = yOffset * (2 - 2*D/ymax); ctx.lineTo(canvasX, canvasY); // Move to the starting point } function textAt(P,D,text,angle=0){ const canvasX = 2*xOffset * (P)/(P2); const canvasY = yOffset * (2 - 2*D/ymax); ctx.save(); ctx.translate(canvasX, canvasY); ctx.rotate(-angle); console.log(angle); ctx.fillText(text, 0, 0); ctx.restore(); } ctx.beginPath(); ctx.moveTo(0, 0); // Move to the starting point ctx.lineTo(0, 2*yOffset); ctx.lineTo(2.5*xOffset, 2*yOffset); ctx.strokeStyle = 'black'; // Set the line color ctx.lineWidth = 2; // Set the line width ctx.stroke(); // Apply the stroke (draw the graph) ctx.beginPath(); for (let P = P1; P supplyAtMid) { P1 = mid; // Move the lower bound } else { P2 = mid; // Move the upper bound } iter++; } // Return the midpoint after max iterations return mid; } // Define the bisection method function bisectionMethodU(DEMAND, SUPPLY, P) { let lo = 0; let hi = 10; let iter = 0; let mid; // Apply the bisection method while (iter 1e-20) P1 = P1 / 1.1 P1 = P1 / 100 let P2 = P1 * 2.0 while(DEMAND(P2) > SUPPLY(P2) && P2 SUPPLY(P1) && DEMAND(P2) market price$" + P.toFixed(3) + "/ride "; rez += " market wage$" + P.toFixed(3) + "/hour "; rez += " market flow" + (DEMAND(P)).toFixed(3) + " rides/hour "; rez += " government price$" + (P*priceRatio).toFixed(3) + "/ride "; rez += " government flow" + (DEMAND(P*priceRatio)).toFixed(3) + " rides/hour "; rez += " utilization" + (U).toFixed(3) + " "; rez += " effective wage$" + (U*P*priceRatio).toFixed(3) + "/hour "; //rez += " effective wage × utilization$" + (U*U*P*priceRatio).toFixed(3) + "/hour "; rez += " "; document.getElementById("results").innerHTML = rez; plot(DEMAND,SUPPLY,P1,P2,P,priceRatio,U); } else { //document.getElementById("result").textContent = "Error: The initial bounds do not bracket a solution. (Is DEMAND is decreasing, SUPPLY is increasing, and both are positive)"; } } // Call calculate() when the page loads to show the initial result window.onload = function() { calculate(); } If you screw around for a while, you will hopefully notice that it’s quite hard to increase wages much above the market wage. It is possible, but requires you to assume that people basically don’t care about prices. For example, if DEMAND(P)=101-P and SUPPLY(W)=99+W, then the market price is $1/ride. If the government increases that to $2/ride, then utilization only drops slightly to 0.981, so the effective wage goes up from $1/hr to $1.961/hr. But is it realistic to assume that people don’t care about prices? Do you really have to assume that? Can we prove anything with “realistic” assumptions? Math time In this section, I’ll prove that that when the government increases prices, the absolute best that drivers can hope for is that 50% of the extra money shows up in wages. For example, if the market price is $20/ride (and the market wage $30/hr) and the government increases the price to $30/ride, then the highest possible new wage is $25/hr. And probably less. (If you hate math and you trust me, feel free to skip this section.) To obviate with the vastness of the human condition with its infinite supply and demand curves, I’m going to analyze a situation where the price starts at the market price and then is changed to be just slightly higher. This is helpful, because then we only need to worry about the supply and demand near the equilibrium, which reduces everything to just four numbers. This is helpful, because it means we only need to care about the shape of the supply and demand curves near the equilibrium, which reduces things to just four numbers. THEOREM. (Me, 2025) Suppose that W(P) is the effective wage at price P. Then at the market price P, Assume that: DEMAND(P) is the number of rides people want to buy per hour at a price of P per ride. SUPPLY(W) is the number of people who want to work per hour, at hourly wage W. U(P) is the utilization rate at price P, defined as the rate where DEMAND(P)=U(P)×SUPPLY(U(P)×P). Let W(P)=U(P)×P is the effective wage at price P. P is the market price, so DEMAND(P)=SUPPLY(P). Recall from above that the effective supply with price P and utilization U is U×SUPPLY(U×P). Now, define the utilization U(P) to the the fraction of time that drivers will spend actually driving people around if the government mandates the price to be P. This will be whatever function makes demand equal to the effective supply. That is, U(P) is (by definition) whatever function is needed to satisfy the equation DEMAND(P) = U(P) × SUPPLY(U(P) × P). If DEMAND(P) and SUPPLY(W) could be anything, then there’s really no way to simplify this equation. But we can always take the derivative. This gives a complicated formula. But if we assume that the current price P is the market price then we get DEMAND’(P) = d/dP U(P) × SUPPLY(U(P) × P) = U’(P) × SUPPLY(U(P) × P) + U(P) × d/dP SUPPLY(U(P) × P) = U’(P) × SUPPLY(U(P) × P) + U(P) × SUPPLY’(U(P) × P) × d/dP(P × U(P)) = U’(P) × SUPPLY(U(P) × P) + U(P) × SUPPLY’(U(P) × P) × (U(P) + P U’(P)). Now if we assume P is currently the market price, then we have that DEMAND(P)=SUPPLY(P) and U(P)=1. Thus, the above equation becomes DEMAND’(P) = U’(P) × SUPPLY(P) + SUPPLY’(P) × (1 + P U’(P)) = U’(P) × (SUPPLY(P) + P SUPPLY’(P)) + SUPPLY’(P), and so U’(P) = (DEMAND’(P) - SUPPLY’(P)) / (SUPPLY(P) + P SUPPLY’(P)). Now, the effective wage is W(P) = P×U(P). This means that the change is (when P is the current equilibrium) W’(P) = U(P) + P×U’(P) = 1 + P×(DEMAND’(P) - SUPPLY’(P)) / (SUPPLY(P) + P SUPPLY’(P)) = (SUPPLY(P) + P×SUPPLY’(P) + P×DEMAND’(P)      - P×SUPPLY’(P)) / (SUPPLY(P) + P SUPPLY’(P)) = (SUPPLY(P) + P×DEMAND’(P)) / (SUPPLY(P) + P SUPPLY’(P)) = (SUPPLY(P)/P + DEMAND’(P)) / (SUPPLY(P)/P + SUPPLY’(P)) = (S/P + DEMAND’(P)) / (S/P + SUPPLY’(P)) Let’s try to understand what this means. First, recall our equilibrium graph: The three quantities in the equation can be seen as the slopes of three lines in this graph. Specifically: DEMAND(P)/P is the slope of the line that goes from the origin to the equilibrium point. This is the number of rides that happen per dollar at the equilibrium point. DEMAND’(P) is the slope of the demand curve at the equilibrium point. This is how sensitive demand is to changes in price. It’s a negative number, since demand goes down when prices go up. SUPPLY’(P) the slope of the supply curve at the equilibrium point. This is how sensitive supply is to changes in wages. This is a a positive number, since supply goes up when prices go up. Note that the government increasing prices could cause wages to go down. This will happen if demand is sensitive enough to prices near equilibrium: COROLLARY. The change in wages W’(P) is negative if and only if the magnitude of DEMAND’(P) (a negative number) is larger than the magnitude of SUPPLY(P)/P. SUPPLY’(P)>0 so the sign of W’(P) is the same as the sign of F/P + DEMAND’(P)=DEMAND(P)/P + DEMAND’(P). I’m not sure how likely it is that wages would actually go down in practice. When I try making up plausible-seeming supply and demand curves, wages do go down sometimes, but it’s fairly rare, and even when it happens the decrease is usually small. Here’s a result that I think is more important in practice. Informally, it says that if the supply curve is “upward sloping”, then the increase in wages is at most 50% of the increase in prices. To me, this is the strongest argument against increasing prices. COROLLARY. If SUPPLY’(P) > SUPPLY(P)/P, then W’(P)<½. DEMAND’(P)<0, so W’(P) ≤ (F/P) / (F/P + SUPPLY’(P)). But if SUPPLY’(P) > SUPPLY(P)/P, then (F/P + SUPPLY’(P))> 2(F/P). When will the supply curve be upward sloping? Let me be show you what I’m talking about: If this is true, then I think we can fairly say that “most of the extra money the government is forcing people to pay doesn’t manifest as extra wages”. I claim this is almost certainly true. Think of it like this: If wages were half as much, would people drive half as much? Or less than half as much? I think it’s less than half as much. This means that the orange curve in the above picture is going to be below the red line, and at least 50% of the extra money is “wasted”. But really, it’s much worse than that. For one thing, this result basically assumes the worst case, where increasing prices doesn’t decrease demand at all. In the real world, demand will go down and the increase in wages will be even less. For another, this doesn’t even account for waste! Suppose a price increase made wages go up 25%, but drivers now only spend 50% of their time actually driving people around. Are you happy? I’m not happy, because (1) this hurts riders and (2) it seems crazy to interfere with markets in ways that encourage people spend more time doing thing that aren’t productive. (I’m sure that all the results in this section are known, but it was easier—and more fun—to just re-derive it myself.) Discussion time In practice, Massachusetts’ policy probably isn’t quite as bad as my simple model suggests: For one thing, in the real world, lower driver utilization will mean reduced wait times for riders, so the money isn’t totally wasted. And the minimum of $32.50/hr only seems to apply when averaged over a few weeks. And maybe some of the extra money will come out of the profits of the ride-sharing company? (Though one can argue that reducing profits is also bad.) But still, if you want to run a command economy where the government sets prices, there are better ways of doing it! And this is not theoretical: New York mandates a minimum wage of $17.22/hr that includes time waiting around. The ridesharing companies responded to this as anyone could predict: They refuse to let drivers get on the clock at all. Jacobin bitterly calls this a “loophole”, but… what are we hoping for here? The money has to come from somewhere. Without a magical supply of extra riders, you can’t force prices above market rate without some kind of consequence! Now, New York’s policy is kind of weird. It mandates a minimum wage, and then leaves it to companies to limit supply. The old-fashioned way of propping up driver pay is to limit taxi medallions, and then let the market price increase naturally. New York’s policy is very indirect, but amounts to basically the same thing. (Incidentally, this isn’t just a story about ride-sharing. It’s also a decent model for why it’s bad that American realtors were able to establish a monopoly where they can extract 6% of the value of anyone who wants to sell a home. That doesn’t just take money away from home-selling and give it to real estate agents. It also subsidizes real-estate agents to spend lots of time competing with each other for clients in a way that does nothing to advance the welfare of general society.) So really, I think Massachusetts’ policy is worse than bad—it’s a mistake. Riders pay more and get fewer rides. And for what? Basically to pay drivers to sit around, spending energy, wasting time, and increasing traffic. Healthy, ambitious societies do not do that.

How much should a couple talk if they are having dinner in a restaurant, after being together for one month/year/decade? If it’s safer to face backwards in vehicles, then what is it that’s shared by infants in cars and soldiers on military planes but no one else? Among rock bands with > 250 million albums sold, 5/6 are from the UK vs. 1/6 from the US. (Or 6/8 vs. 2/8 if you count Elton John and Michael Jackson). Why? If you swim in public pools, is that because you reject the research suggesting that most contain 30-80 liters of urine, or because you don’t mind? Is declining fertility destined to be reversed through growth of high-fertility subcultures, or could there be competing low-fertility cultures that peel people away so effectively that population declines forever? Does postapocalyptic fiction represent a yearning for the life and death of pre-history? If so, where is there so little fiction based on ordinary pre-history life? What is the best Brassica? I collect here the most common for readers negligent in their Brassica studies: species examples nigra black mustard oleracea kale, cabbage, collard greens, broccoli, cauliflower, Chinese broccoli, Brussels sprouts, turnip cabbage rapa bok choy, choy sum, napa cabbage, turnip, canola (sometimes) carinata Ethiopian rape, Ethiopian mustard napus rutabaga, rapeseed, turnip (sometimes), canola (often) juncea mustard greens, Chinese/Indian/Korean mustard, canola (sometimes) Does it matter to you, emotionally, that only nigra, oleracea, and rapa are diploid species, and the others are lame tetraploids that just add together the ancestral genomes (carinata=nigra+oleracea, napus=rapa+oleracea, juncea=nigra+rapa) as first proposed in 1935 in Woo Jang-choon’s Triangle of U theory? Which color of food should there be more of? Choose two yes/no opinion questions. Around 50% of the population should say yes to each. What do you choose to get the smallest possible intersection? Do you think you could cultivate a taste in types of music you don’t currently like if you tried? If yes, why don’t you? What percentage of young people’s increased propensity to explore new music is driven by social taste competition? Say you were born in China/America/India (assuming you weren’t) but you are still “you”. What’s the biggest difference? What are the odds that humans are just too dumb to understand the universe and our place in it? What are the odds that that consciousness isn’t unified and that there isn’t just a single “you” in your head experiencing the world? If you could cure all heart disease or all cancer, which would you pick? Take the conditions in the current Diagnostic and Statistical Manual, e.g. Antisocial personality disorder Attention-deficit/hyperactivity disorder Autism spectrum disorder Avoidant personality disorder Bipolar II disorder Borderline personality disorder Dissociative amnesia Major depressive disorder Paranoid personality disorder Schizophrenia Tourette’s disorder etc. What fraction of these concepts will still exist in 100 years? Does time actually go faster as you get older, or do we just remember it differently? What foods are best eaten with chopsticks but don’t come from food traditions that use chopsticks? What about with Western cutlery? What about with your hands? I’ve written to the “corresponding author” of dozens of published research papers, always with polite and straightforward questions. Something like 80% do not respond, at all. Even when they promised the journal to make data available upon request, most do not respond. How much of a jerk would I be to publish a list of those papers? To what degree is the anomalous self-confidence of American economists explained simply by the existence of Milton Friedman? Say you can have your eyes to be upgraded to either (a) have a fourth group of cone cells peaking around 370 nm in the UV band, like birds or (b) to be sensitive to polarization, like cephalopods. Your visual cortex is also upgraded to process the information. Which do you choose? How different would the next 20 years be if things created entirely by humans AI got an unfakable gold star? How much do normies really miss out on by using a Bourdieu-007 final last (1) ACTUALLY FINAL 2b edited.txt style file naming scheme instead of learning a source control system? If you could make yourself enjoy something less, what would it be? Would that make you enjoy life more, overall? How much does it matter how open people are to persuasion? If people were much more/less open to being convinced by arguments and changing their minds, how much better/worse would the world be? Assume that people are only convinced by “good” arguments. Say you flip a standard US penny 20 times, getting 15 heads. What’s your best estimate for the true bias of the coin, if you think there’s a 50% chance Bayesian statistics are correct? Per minute, is there really any philosophy text that offers more insight than Existential Troopers? Who would win in a wrestling match, Jesus or Shirdi Sai Baba? In an alternative universe where when yeast broke down sugar molecules into fentanyl rather than alcohol, would we all get together and celebrate the new year by consuming fentanyl? If you’d like to answer these questions instead of using them to start arguments as intended, you can do that here. (previously) (previously)