fisted by the invisible hand
economics is fun actually
There’s a common criticism of neoclassical economics that goes something like this:
Economists pretend that human beings are rational self-interested agents, but no one is actually like that! It’s not scientific to represent people as simple equations, we’re emotional, chaotic, irrational creatures—those stuffy math nerds will never be able to understand or predict real human experiences.
This critique is seductive because it’s half true. Mathematical models of human behavior are indeed oversimplified, and economists are often stuffy math nerds, but this does not mean economics is always boring, invalid, or useless—far from it. Classical economics makes more sense when you view it as a technology rather than as a science. It is not a description of reality, but rather a collection of abstractions we can use to build powerful systems to aggregate information and allocate resources.
Suppose you desperately want to know the answer to the following question: Who will win AVN’s Female Performer of the Year Award in 2023? There are a few ways you could approach this problem:
Use background intuition and knowledge. What scenes have each of the nominees released this year? Has anyone come out with a really big scene?
Do statistical analysis. Are there metrics which are historically correlated with winning the award, such as DVD sales?
Run a poll on social media. Popularity is likely correlated with winning awards; who do a million porn fans want to win?
Survey industry insiders and experts. Professionals and industry journalists are more familiar with the inner workings of AVN; what do they think?
I encourage you to try forecasting AVN 2023 results using any of these methods. You’ll find that predicting the future is really hard. I’ve been writing down AVN predictions in advance for the past few years, and in spite of how closely I (*cough*) follow the industry, they’ve almost all been wrong. Background knowledge is unreliable, historical correlations don’t always hold up, and online polls usually contain more noise than signal. Asking industry insiders avoids some of these issues, but experts have personal biases of their own and it’s hard to know which insiders are the most accurate.
Is there some other approach which aggregates all of the available information from both experts and fans, avoids personal biases, and incorporates statistical analysis where appropriate? If you’re willing to use the dark magicks of classical economics, the answer is yes: prediction markets.
On a prediction market, traders buy and sell shares of contracts which represent predictions about the future—if the prediction comes true, the contract can be redeemed for cash. Using our AVN example, we can imagine a prediction market containing shares of contracts like “Savannah Bond will win the 2023 AVN Female Performer of the Year Award,” “Blake Blossom will win the 2023 AVN Female Performer of the Year Award,” and so on for each of the other nominees. If Savannah wins, one Savannah share is redeemable for $1. If she loses, it’s worth $0. If you want to make money, how much are you willing to pay for Savannah shares? $0.40 per share? $0.80 per share? This reflects your beliefs about the outcome—market prices are probabilities.
The function of a prediction market is to aggregate collective knowledge. If the “Savannah Bond will win the 2023 AVN Female Performer of the Year Award” contract is trading at $0.75 per share, this means the market estimates that this will happen with 75% probability. If new information comes to light which makes this seem less likely (for example, someone else releases a hugely popular scene), people will sell their Savannah shares and the price will drop.
If you’re having trouble building intuition around this, YouTuber Robert Miles and GMU economist Robin Hanson have good introductory videos.
Prediction markets are often more accurate than polls and expert forecasters, because they rewarding participants who consistently make correct predictions and incentivizing anyone with information to participate. These markets can represent any question as long as it can be clearly defined and verified. Binary outcomes are represented by two contracts which cover both possible outcomes, for example “Angela White will shoot >50 scenes in 2023” and “Angela White will not shoot >50 scenes in 2023” would both exist on the market.
We can also trade conditional predictions—suppose we have “if Mike Adriano releases a clown-themed scene in 2023, it will be nominated for an AVN Award” and “if Mike Adriano releases a clown-themed scene in 2023, it will not be nominated for an AVN Award” on the market. If Mike does release a clown scene in 2023, then one of these contracts will be worth $1 at the end of the year, but if he doesn’t then everyone can redeem their shares for whatever they paid, as if the contracts never existed. Conditional predictions are useful because they allow us to see what the market thinks about a decision that hasn’t been made yet—for example, I bet Mike would be very interested in knowing which of those contracts has a higher price!
cool, cool. now make it sexy
Prediction markets are not just a cute toy for guessing AVN winners—with the right set of conditional predictions in a market, you can transform an entire industry.
Consider everyone’s favorite niche fetish, gooning. Gooning communities have existed online since the 1990s, and internet weirdos (myself included) have been predicting its ascent into mainstream porn for years. Many of these predictions were merely wish fulfillment, but some of us had a model of the world which explained why gooning might gain broad appeal.
Alas, the studio system was slow to catch on—gooning first appeared in studio porn in a Nympho.com scene starring Angela White in 2019. Angela and other performers continued to post gooner-themed content on OnlyFans, but it would take another three years before the fetish appeared in another studio scene, Brazzers’ Sexually Rated Programming in 2022. Clussy developed in a similar way—a niche community was enthusiastically posting clown porn for years, a few people in that community suspected it may have mainstream appeal, and then suddenly one day it went viral.
A prediction market could aggregate this hidden information. Such a market would contain a huge matrix of conditional predictions about content and sales—lots of variations of contracts like “if Brazzers releases a toefucking scene in September 2022, it will sell >1,000 DVD copies by January 2023.” If the price of a contract stabilizes at a high price, say $0.90, that’s a strong signal to the studio about the expected return on this investment; industry insiders could use this as market research.
In the long term, this would eliminate information asymmetries between performers and creators, helping studio execs understand value of things like clown aesthetics much more quickly—not to mention the gooners who could fund their OnlyFans subscriptions for years by betting on this. There’s a lot of alpha in porn addiction!
the market shall remain, in midst of other woe
When prediction markets are used to make important decisions, participants may try to manipulate market prices to influence decision makers. Suppose I want cakesitting to appear in as many porn scenes as possible (not hypothetical). I could dip into my savings and overbid on contracts which predict high sales of cakesitting videos—this will drive up the prices of those contracts, which performers might interpret as a signal that cakesitting videos will be profitable. I’ll lose all my money when the predictions don’t come true, but for some period of time my market activity could affect what kind of porn videos are produced.
The advantage of a prediction market over a survey or a committee of experts is that the system will self-correct quickly when this type of manipulation occurs. If I bid up the prices of contracts predicting high cakesitting sales, other traders can profit from my deliberate irrationality by selling me these contracts at exorbitant prices and purchasing contracts predicting low cakesitting sales, which will be at a discount. This will move the contract prices back in line with the market’s aggregated belief about cakesitting, negating the effect of my trades. If the market is liquid enough, this correction could happen within seconds. Empirical studies suggest that prediction market manipulation is difficult even where liquidity is low—as a result, it’s probably cheaper for me to simply buy custom cakesitting clips from performers than to play the market.
More serious problems arise when market participants can directly influence the outcome of events—for example, someone could buy a contract like “Kira Noir will make >500 sales on ManyVids in December 2022” and then purchase a few videos to ensure the prediction comes true. Or, more maliciously, they could buy the opposing contract and then DDoS ManyVids to prevent video sales.
Additionally, while insider trading isn’t an issue for prediction markets (they are happy to gobble up any information, regardless of the source), conflicts of interest can create perverse incentives. Consider a contract like “Johnny Sins will not shoot >20 scenes in 2023.” Johnny Sins himself might want to buy this contract, not because he thinks it will come true, but as a hedge against getting sick or injured—if this happens, then his profits on the market are form of insurance against his lost income from not shooting. This might influence his behavior, allowing him to take more risks with his health, secure in the knowledge that his income is insured.
I suspect these are not insurmountable design problems, and with the right safeguards prediction markets could be put to practical use in the adult industry. One possible solution is to implement a private market, which only industry professionals can use, rather than a market which is open to the public.
Brief digression on legal implications: Real-money prediction markets are mostly illegal in the United States, where they are classified as online gambling. Iowa Electronic Markets and PredictIt exist at the mercy of the CFTC, and PredictIt is being shut down under mysterious circumstances. Newcomer Kalshi has full CFTC approval, but this comes with heavy restrictions on what topics are allowed on the platform. There’s also Polymarket and Augur on the Ethereum blockchain, which cheerfully admit they may be illegal in some countries but no one can stop you from using them. Finally, it is legal to run prediction markets for made-up “reputation points” or non-cash prizes.
the pornarchy manifesto
Suppose we actually create an online porno-prediction market where the public can buy and sell predictions about adult content. Fans pour in and bet on their favorite stars, and industry insiders suggest new types of contracts to include. As the system grows, more sophisticated traders enter with independent research and statistical analysis, adding information to the market and making prices more accurate. Over time we observe that the market is robust, immune to long-term manipulation, and often makes correct and surprising predictions. Studios consult it frequently and use market prices to determine what kind of content to shoot and who to cast.
If the market’s judgements are so reliable, why not cut the humans out of the loop and give the invisible hand direct authority over production? Economist Robin Hanson proposes exactly this in his futarchy manifesto:
The basic rule of government would be: When a betting market clearly estimates that a proposed policy would increase expected national welfare, that proposal becomes law.
Adapting this concept to the adult industry, under pornarchy the studio system will cede as much decision-making power as possible and simply shoot a scene if the market predicts it will be profitable. If there is a conditional prediction on the market like “if Brazzers releases a scene featuring a Angela White stuck in a dryer, it will sell over 1,000 DVDs” and price of this contract stays above some threshold (say, $0.80) for a certain amount of time, then an automated personal assistant activates and fires off emails to schedule the shoot. The performers and director and crew take it from there—but other conditional bets on the market might control aspects of production such as set design and lighting.
What kind of porn would this system create? We don’t really know! In general when analyzing an optimization process which is smarter than you, you can’t predict exactly what it will do, but you can be confident it will achieve its goals. It does seem likely that a prediction market would bring new fetishes to the surface much faster than the industry does today, cranking up the speed on the hedonic treadmill.
For a performer inside this system, futarchy governance would probably feel confusing, bizarre, unpredictable—your schedule could change on a whim, and you might not understand why the market decided this. You could be shooting clown ASMR for months and then one day with no explanation you could be, literally, fisted by the invisible hand.