“Computer,” one can imagine asking many years from now, in some kind of futuristic, robotic retirement home, “remind me: What was the deal with Drake and the ‘goth baddie’?”
In this future your A.I. companion will whir and hum, calculate and infer, and spit out something like this: That’s a great question — and you’ve really hit on a load-bearing 21st-century event. In September 2026, the Canadian singer and rapper Drake released a music video in which he was seen receiving an emo-goth makeover from the OnlyFans model and streamer Pinkchyu, whom he had purportedly met and become smitten with while shooting an internet dating show released earlier that month. Historians believe the popular viral videos, which started a number of discourse cycles on social media, were most likely stunts arranged to promote Drake’s video project, “Fear of Missing Out.”
This is not a bad answer to the question. You will be reminded of Drake, of Pinkchyu and of the viral cycle of promotion that accompanied “FOMO.” But if you set aside a little bit more money in retirement for the slightly better A.I. companion, you might learn of a third player in the Drake-Goth Baddie romance: an Australian online casino, registered in Curaçao, called Stake.
Stake, which entered the gambling business in 2017, has long been a leader in aggressive and somewhat underhanded digital-first marketing; it’s notorious for paying spammy social media accounts to swipe already-viral images and memes and repackage them with the Stake logo. Since 2022, however, it has been best known as the money behind Kick, the edgy video-streaming platform rival to Twitch, and the home of unpleasant but unavoidable figures like Braden Peters, better known as Clavicular; Adin Ross, a right-wing Zoomer shock jock; and ChudTheBuilder, who is perhaps best known for yelling racial slurs at strangers. Following years of regular appearances with popular streamers like Ross, during which the pair would gamble on Stake — winning, Bloomberg reported in February, at mathematically improbable rates — Drake debuted his own new Kick stream in August, which is where the dating show with Pinkchyu took place. The occasion: Stake’s ninth anniversary.
For most of my life as a consumer of the stupid promotional nonsense that surrounds major album and film releases, these rollouts have taken place on MTV or magazines, in blogs or, eventually, on Instagram. But here, Drake, probably the most shameless student of popularity in the 21st century, has spurned them all for an apparently much higher-leverage channel: an online casino and the social media apparatus built around it.
But why should we be surprised? Traditional gambling — casinos, lotteries and sports betting — is a $643 billion global industry, according to the market research firm Statista; last year, about a third of that revenue came from the United States, where online gambling in particular has soared in the years since the pandemic. Depending on how you count, this makes gambling almost twice as large as the global music, video game and film industries combined.
It’s hard not to see the traces of gambling money everywhere you turn these days: in sports broadcasts now blanketed with odds and sportsbook branding, in a podcast ecosystem underwritten by DraftKings and FanDuel ad money and, yes, in the influencer freaks rocketing to fame thanks to canny marketing spending by offshore casinos. The success of casino capital has given it an outsize weight in producing and disseminating culture, especially as older and more reliable sources of revenue for media and entertainment — advertising in particular — dry up or are captured by tech platforms.
But focusing on gambling alone only tells part of the story of this strange new development in culture. We are living through a kind of postpandemic gamified speculative-trading apocalypse of which traditional gambling is only one horseman. There’s also crypto, now an enormous industry still searching for a nonspeculative use; stock trading apps like Robinhood, which popularized high-risk, leveraged options trading among retail investors; and, most recently, prediction markets, which saw $60 billion in trading volume last year. Soon, it won’t make much sense to distinguish among these categories, as the apps converge on a multi-offering model featuring some combination of sportsbook, prediction market, options trading and crypto, if not all of the above.
What underwrites this emerging industry — besides an excellent business model and billions of dollars of revenue from suckers and billions of dollars of investment from the smart-money set — is a shared vision of a world built around gambling and the calculated risks that accompany it. The influencers, livestreamers, podcasters and aggregators (not to mention rappers and comedians and athletes) who have reoriented their output around the imperatives of betting capital not only work in service of what you might call the speculative sector but operate according to its logic as well. What is social media, after all, but a venue where you can wager your reputation and stake high-risk claims — and, perhaps, trigger a lavish (if infrequent) payout? All while enjoying the addictive satisfactions of endless nondeterministic push-button stimulus.
Gambling, in other words, is not simply paying for the culture. It is the culture.
No one knows this better than sports fans. Every major sports league and sports broadcast has a sportsbook partner or sponsor, and nearly every broadcast now prominently features betting lines and parlay suggestions. Leagues that once undertook damnatio memoriae on athletes who gambled now promote stars with exclusive branded sportsbook deals; dozens of major-league stadiums feature internal betting windows. Every major sports league is now a subsector of the gambling industry, rather than the other way around.
Perhaps this is not worth mourning: Professional sports are, in some sense, a kind of entertainment. But even if you don’t take sports seriously, consider if the same forces were to take hold of news media in general. Kalshi, an app that allows enterprising consumers of news to bet on elections, awards, invasions and the like, has partnered with CNN, CNBC and Fox News to provide them with prediction-market data; its rival Polymarket has its own agreements with Dow Jones and X. Right now, these deals offer in data what the sportsbooks partnerships offer in money: a new source for an essential material that has lately been scarce. In an era in which polling is “broken,” prediction-market odds can potentially help take the temperature of the electorate.
But if the prediction-market business keeps growing as quickly, the partnerships might expand beyond the pure provision of data, and Kalshi and Polymarket could become the same kind of reliable sources of funding to cable news that DraftKings and MGM are to sports media. It’s not hard from here to imagine a future in which CNN anchors promote their electoral “Locks of the Week” and Fox News analysts offer up branded parlay bets. (At least ratings would be up, as fans stay up late even during blowouts to see if the Republicans cover the spread.)
This may seem far-fetched, but when speculative capital enters an ecosystem, it has a way of completely reorienting all the players. The gambling-oriented sports-entertainment complex has created a new type of fan, less a devoted adherent to a particular team or player than an omnivorous and avaricious consumer of scorelines. What kind of citizen does a prediction markets-oriented news media give us? The hopeful answer here, such as it is — the answer provided by the marketing materials for the various wagering apps — is that we all become daring superforecasters.
In his recent book, “On the Edge,” the hybrid journalist-pollster-professional gambler Nate Silver proposes an anthropological distinction between groups he calls the Village and the River. The Village is “people who work in government, in much of the media and in parts of academia” — in Silver’s telling, epistemically cautious, methodically conservative and socially conformist. The River is an “ecosystem” of people, among them tech-aligned entrepreneurs, investors, thinkers, literal gamblers and, I suppose, Drake, who “speak one language with terms such as expected value, Nash equilibrium and Bayesian priors.” The Village is staid, outdated, cautious; the River is cool and fun.
It might be helpful to think of the River less as a temperament or subculture than as the militant vanguard of what the philosopher Ian Hacking called “the probabilistic revolution,” the slow displacement of determinism and strict causality with a new mode of thinking rooted in uncertainty and statistical inference. This style of reasoning understands the world in terms of distributions rather than particularities; its laws are observed relations rather than causal accounts. “Chance,” it suggests, isn’t a function of human ignorance but a property that could be measured, governed and put to profitable use.
In fact, statistics has its roots in gambling. The discipline was born when French mathematicians tried to settle a debate about the odds of a given dice roll. But it flourished in the 19th century, as modern states began producing large data sets about their populations: censuses, marriage statistics, mortality rates. The application of statistical methods to these data sets revealed that certain “laws” could hold true on the population level without anyone really needing to know or care why.
If the defining statistical apparatus of the 19th century belonged to European states, that of our century is the property of a few dozen companies in Northern California, where the statistical style rules. Venture capital, the investment philosophy that built Silicon Valley, is a method less for picking companies than for constructing exposure to a distribution: If most investments go to zero, and your returns are concentrated in enormous outliers, the smart move is to construct broad exposure, rather than to try to determine winners in advance.
At the same time the software systems that govern our lives are also built on probabilities, not particularities: The recommendation algorithm serving up a video has no clue what the video contains and does not know you, your preferences, your desires; it simply estimates a conditional probability. The user interface you interact with is as much a product of repeated statistical experiments — A/B testing — as it is of considered judgments or design principles. And the advertising auctions funding everything online estimate the odds that you will click or install, and price your attention accordingly, several billion times a day.
Large language models, the foundation of the systems we now broadly refer to as “A.I.” and the apotheosis of tech-industry innovation, might be the purest expression of the statistical style. They have no beliefs and know no facts; they’re conditional probability distributions over fragments of text. And the thing is, they work: L.L.M.s produce astonishingly lucid, fluid and plausible text. Indeed, what makes the statistical style so powerful and attractive is that it works across the board. Venture investing, advertising auctions, A/B testing, recommendation algorithms and other practices derived from the probabilistic framework have made the tech industry and its stars fabulously wealthy.
Its success, in turn, justifies its spread. Increasingly the tech industry seems determined to go further, fully surrendering everyday judgment and even personality to the statistical approach: “I’m updating my priors on Thai food,” you might hear an engineer say; or, from a V.C., “Going for a walk is +EV.” (Translation: “I was wrong about Thai food” and “Going for a walk is nice.”) At Silicon Valley parties, or so I’ve read, everyone talks about their “p(doom)”: a cutesy expression of probability to describe your relative confidence that an artificial intelligence will kill the human race. The implication here is that, just as people in the past understood their minds to function like clockwork, hydraulics, steam engines and eventually computers, the people at the forefront of innovation see their minds as an even more cutting-edge technology: stochastic models and inference engines.
It’s unsurprising that the wealthy whiz-kids of Silicon Valley, habituated as they are to data collection, inference and speculative investment, would turn to prediction markets. But why does anyone else? One popular explanation is what the podcaster Demetri Kofinas calls “financial nihilism”: a sense that all other pathways to wealth and stability have been cut off, and therefore that the only option is to turn to crypto, day trading, gambling and perhaps streaming yourself doing one or all of the above. At the dawn of an era when A.I. may entirely restructure the job market, this is the message most consistently broadcast to young men online by Silicon Valley and its gambling subsectors: Avoid the permanent underclass.
But what if the apparent affection for high-risk endeavor is less a product of nihilistic recklessness and more a considered adoption of the statistical style (or a vulgar version thereof) in personal finance, social interaction, health and romance? The kids, in this story, embrace gambling not so much for the thrill but because they’ve been conditioned by the world around them to seek exposure across a range of investments, just like a venture capitalist.
Last year, I called a Kick streamer named Mike Smalls Jr. to ask him about the time he livestreamed a hurricane. In October 2024, as Hurricane Milton was bearing down on Tampa, Fla., Smalls heard that the streamer Adin Ross was offering $70,000 to anyone who streamed the hurricane. “So I went out there with an air mattress,” he told me, “at a nearby pond.” For the first hour or so, Smalls, sitting on his air mattress, tried to control his umbrella while bantering with viewers. Eventually, the water rose over the banks of the pond, and Smalls, who can’t swim, found himself clinging to a tree. At some point, Ross himself joined the chat, and had to break it to Smalls that the $70,000 offer wasn’t legitimate. Smalls, still streaming, indefatigable, managed to wheedle $10,000 out of him.
I’d been struck by the story of a guy gambling his life against a jackpot, and I was expecting to talk to an inveterate risk-taker, a new man who saw his life in terms of odds and probabilities. But Smalls didn’t see the stream as a gamble, and he doesn’t gamble much himself. (Though he used to on Kick, with bankrolls provided by Stake.) “Gambling can be very addictive,” he told me, “so I don’t want to brand myself too much as a gambling guy.” He struck me not so much as a risk-on oddsmaker but as a fairly methodical and thoughtful self-starter — one for whom his volatile streaming career was an investment on par with his college education.
But even those of us who have never livestreamed are similarly exposed. The health and bodybuilding content young men consume is couched in the language of risk and odds — reducing your “all-cause mortality” — derived from the huge amounts of data you can gather from your Oura rings and Whoop bands. Once you’ve maxxed your looks, you can enter the dating-app casino, increasing your odds of a payout with better photos and captions; if you get lucky and find a partner to have a kid with, a start-up called Orchid can give you “polygenic risk scores” for your future children.
Your job, at this point, may well have a reward structure not all that different from a slot machine: Maybe you’re a start-up employee taking a significant portion of pay in equity, or maybe you’re a “creator” (which is to say a journalist, musician, actor, illustrator) hoping to end up on the right side of the winner-take-all economy, or maybe you’re driving an Uber and gambling that surge pricing will hit the evening you have the car.
Even politics has become quite obviously perverted by this logic. Former Representative Sean Patrick Maloney recently complained that “being a social media influencer” is now typical behavior for legislators. His frustration may be heartfelt, but pumping out potentially viral videos (rather than producing complex bipartisan legislation) is a statistically rational exercise in Congress, where attention is currency. Even the online-phobic head-down legislators are unavoidably roped in thanks to Kalshi and Polymarket, which have made tradable assets of nearly every component of their job, the most absurd being “mentions markets,” which pay out not for some political outcome but when a politician or spokesperson uses a word or phrase. What predictions and statistical calculation threaten to corrupt in this case isn’t just causality and particularity but the meaning of citizenship in a democracy: A vote is a singular commitment; on Kalshi, you can hedge.
For some people — denizens of the River — this world might be ideal, or close to it: a place to maximize your wealth and prestige by expertly playing odds across all spheres of your existence. I can see its appeal, too: I remember reading Emily Oster’s best seller “Expecting Better” when my wife was pregnant and appreciating a book that allowed her to make her own decisions about, say, diet, based on her own tolerance for risk, instead of operating according to the one-size-fits-all rules of the medical establishment.
But I also remember standing in front of the deli counter trying to figure out how comfortable with Listeria risk we really were versus how much she really wanted some prosciutto, and ultimately finding the freedom of individuated risk as enervating in its own way as the restrictions of blanket recommendations. I don’t think I’m alone. For those of us who aren’t accustomed to the particular habits of mind and styles of reason of Silicon Valley, the world of casinos and prediction markets and financialized opinions is exhausting: calculating your individual risk profile at all hours of the day, hedging every bet, avoiding all commitments in order to keep your options open.
This doesn’t have to be the inevitable endpoint of the probabilistic revolution, or of institutions designed to account for chance. Among the earliest innovations to take advantage of the science of statistics and probability was insurance, which is a way to collectively pool risk. The offloading of probabilistic calculation away from institutional bodies and onto individuals — the shift from “insuring” or “investing” to “betting,” put crudely — is a more recent innovation.
But it’s the individual gambler that Silicon Valley can make the most use of. Casinos need marks. Crypto needs bag holders. Prediction markets need dumb money. And L.L.M.s need information.
In an October 2025 article for the venture capital firm Andreessen Horowitz’s blog, the company’s editor at large, Alex Danco, surveys a future in which “intelligent machines are conceiving, driving and implementing a lot of our material progress.” With A.I. doing all the important stuff, what’s left for the rest of us? The answer Danco lands on is speculation: “Predictions,” in the machine-led future, “give us something to do.” Someone, after all, has to produce new information to be absorbed and weighted by A.I.; to Danco, this is “our purpose.” Maybe this sounds grim or demeaning, or at least unusual, to you. It doesn’t to Danco. In fact, he ends on a hopeful note: “I couldn’t imagine something more optimistic if I tried.”
Easy for him to say; he already made all the right bets.
Max Read is the author of the Read Max newsletter.
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