Page Text: The End of Women
18 minute read
The technological and social changes of the last 60 years have created extreme disruptions in the way men and women carry out the mating dance. The battle of the sexes has reached a fever pitch as we are exposed to more potential partners in a day than we historically were in a lifetime, and yet mostly people operate on an implicit model of sexually monogamous relationships leading toward marriage. Sexual conflict is inevitable as the battle over women’s bodies intensifies, and the battle among women for top men does too.
“patio11’s Law”: The software economy is bigger than you think, even when you take into account patio11’s Law.
XBTUSD’s Law: Online dating has a larger effect on mating than you think, even when you take this law into account.
When you change the liquidity of a market , you fundamentally change that market. OLD has changed the level of scarcity with which each market participant approaches the market; OLD has parallels to the secretary problem , which is a mathematical model that describes the optimal searching algorithm to find a mate. When thinking about algorithms, it’s often useful to start with the “dumbest thing that could work” which in this case would be “always pick the 7th person you date”. If we follow this rule, we’re essentially picking an integer at random. The probability, then, of picking the best element from an integer sequence of length N with this rule is 1/N. Once we have a base case, we can ask ourselves, could we do better?
To beat this, consider how people go about solving secretary problems in the real world. The strategy most adults adopt is to date around for a while, gain some experience, figure out one’s options and probable range, and then choose the next best thing that comes around.
In terms of the secretary problem, such a strategy would be: Scan through the first r integers and then choose the first option that is greater than any of the integers in [1,r]. The formal proof of this problem gives us the answer 1/e or ~.37.
How does this help us? The optimal solution is to estimate how many people one believes one might reasonably date in the future, say 20? We plug this into the equation, where N = 20 and N/e ~ 7. This result says that, if one wants to maximize one’s probability of ending up with the best possible match, one should date 7 people and, then, marry the next person who is better than all of those men.
However, the typical secretary problem assumes we want to maximize the chances of landing the best match, and considers all other outcomes equally bad. Most people in the dating market are not thinking this way — they want to maximize the probability that they end up with a pretty good spouse. It’s not all or nothing. In addition, people vary on key characteristics: some spouses are smarter, more handsome, wealthier, loyal, and so forth, but all positive attributes are rarely combined in a single person. Luckily, there’s a modification to the solution that maximizes the probability of finding a high-value husband or wife. The strategy is the same except we use a cutoff of the square root of N rather than N/e. So if you believe you will have the opportunity to date roughly 20 people between 18 and 35 for example, you would (somewhat seriously) date 4.5 people and then marry the next one that’s better than anyone you’ve dated previously.
This formula tells us how likely we are to find a good match as N grows, and how important it is that our early data gives us accurate information about who would be a good match. If we have a random set of integers between 1-10 (10 being a perfect match) and we only have 1 number in the set, the average match we will get is a 5. Long ago this was reality, as marriages were often arranged for reasons other than “love” or “being a good match.” Marriage was typically a political tool or an economic necessity. The “job” of a marriage was to enable both persons in it to survive, reproduce, and reinforce the community; the job of a contemporary marriage is different, for most people, and often includes nebulous things like self-fulfillment or positive feelings, rather than concrete things like “puts food on the table” or “watches the children, who don’t die from preventable mishaps.”
As our ability to fill the set with better and better candidates the likelihood of getting a better match increases. As our lifetime N grows, the solution to the secretary problem continues to grow with the square root of the number of people we can date. People should be dating more people as the pool gets better and as the potential N we can date grows. As a result, people’s standards have risen with the growth in the number of potential partners they meet in a lifetime. The secretary problem is somewhat related to the internet infinity fallacy . Our N is not infinite, and the quality of each n matters greatly for us to secure a great match. More importantly, the early data we collect tells us how to set the bar for mate value or match value in our searching algorithm.
When searching for a partner there are a few things to consider: your mate value, the mate value of the person you’re evaluating, and how good of a match you are. Many of us are, not surprisingly, prone to mis-judging our own value. Mate value is both an average across the population, and different for each person evaluating that potential mate. So we have mX (individual mate value as seen by person X) and mA (average mate value as seen by the crowd). Most people are trying to partner with the person who has the highest mate value to them (mX not mA). In the short term, mate value is fixed as seen by any individual, but people’s preferences are largely shaped by the culture and context and the way we meet each other. In a society where marriages are arranged by families, people might value their mates based on their ability to provide (childcare, resources, farming) for the family. Loyalty, determination, flexibility and conflict resolution skills might also be extremely important in an arranged marriage. The more difficult it is to separate from a spouse, the more important it is to be long-term focused, to accept your partner as they are and work through any conflict. You’re stuck with each other, do you make the best of it, or do you complain? In Albert Hirschman’s formulation , we have three choices in dissatisfaction: exit, voice, and loyalty. Arranged marriages emphasized voice and especially loyalty, but modern mating markets emphasize exit. In an arranged marriage, physical attractiveness might be completely irrelevant. You can’t do much about it, you’re either attracted to your partner or not.
In contrast, in modern western society, online dating has radically altered what traits are salient and thus which we most value. For example, men’s height is offered as a filter. In a world where height is discontinuous, it’s hard to imagine a woman in a social setting being a hard “no” on a man 5’10” vs 5’9” and yet online, many women set a minimum height and then forget about it. Online, things scale to an extent that it changes from a difference of degree to a difference in kind. When women had trouble lining up dates at all, they wouldn’t have strong filters on physical traits, but online the pool is infinite and therefore women must filter by something, because men want casual sex with women more than women do men.
When women collect data through dating to calibrate their filters for the secretary problem, the data they are receiving is blended. “What is the highest mate value of a man who will mate with me” and “what is the highest mate value of a man who would marry me” are two different questions, but it is often difficult for women to distinguish the difference in their dating experiences . Typically, the highest mate value of a man for a short term relationship > highest mate value of a man for a long term relationship. When women are younger, they are more likely to be collecting data from men’s short term relationship preferences, but assuming that eventually they could convert one of these men to being a high mate value long term relationship. Unfortunately this is unlikely to be true. If a woman is using the algorithm most daters use (“to date around for a while, gain some experience, figure out one’s options, and then choose the next best thing that comes around”) they might be setting the bar too high based on a short term relationship and searching for the next option that beats that high water mark. If she sets the watermark unrealistically high during the data collection phase, the algorithm will fail her and she will already have found the best match during the level setting phase of the algorithm. Even more importantly, the tools we use to set our filters and the way in which we date changes how we experience dating itself. These problems are also made more or less acute by the male-female ratio in a given dating market .
In the modern era of app dating, women, who are already passive consumers of the dating world (accepting or rejecting offers more than making them), begin to fully shift into a filtering mindset. When the brain goes into cognitive overload and has too many choices, it attempts to reduce the search space until it reduces to a manageable amount. Online, women find that most of the men they swipe “yes” on they match with. Men are three times more likely to swipe right than women, selecting, on average, about 46 per cent of profiles, versus 14 per cent selected by women . This teaches women that their task is to match with the men who maximize the qualities the interface surfaces and then hope those men ask them out on dates. There are a number of critical problems with this strategy. While having too many great matches to go on dates with might seem like a good problem, it trains women to select for qualities that are unlikely to result in a satisfying or positive dating experience. The vast majority of humans take the default path, which requires the least thought and energy, so we are passive consumers of how these apps train us to evaluate potential partners.
Male pursuit remains inextricably intertwined with our cultural expectations of courtship. Fewer than 1 per cent of heterosexual women who self-identified as feminists said they wanted to be the pursuer. Fifty-four per cent were happy to do a bit of both, leaving a full 45 per cent who preferred to be pursued. As the behavioural economist Dan Ariely explains it, women tend to employ a ‘budget’ approach to dating, getting pickier the larger the pool gets , whereas men are more opportunistic, swiping right, basically, on anyone they’d fuck. The app dating experience changes both how we perceive our available options, and which options we see as the most preferable.
In short, there is no adaptive value of sexual conflict per se. Many conflicts and their outcomes are purely maladaptive byproducts for both sexes. If women and men could agree in advance on a compromised middle-ground solution that was perfect for neither but acceptable for both given the circumstances, they could avoid many of these costs. For each offensive adaption, however, selection favors defensive adaptations in the other, producing a never ending coevolutionary arms race-an endless cycle of reciprocal adaptations and counteradaptations. Like the Red Queen of Lewis Carroll’s classic, each must continue running as fast as possible just to avoid losing ground.
-David Buss
Both sexes employ evolutionary adaptations to counteract the other sexes’ defenses. If nature was about “happiness,” we would all lay our evolutionary cards on the table and mate with everyone, but the species would fail, or not be optimized. It will always be the female of the species role to select for the best genetic material and the highest likelihood of that offspring succeeding and the males job to attempt to mate with as many healthy females as possible. App dating has permanently altered female’s ability to select good long term mates shifting their preferences towards criteria they historically valued only in short term mating.