Accumulated thoughts on finding life partners.

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I see a number of blog posts and books like this, this, and this that will develop an interesting theory and then relate it to the dating problem but in a cursory fashion, as a subset of a more abstract problem. Here I try to aggregate these pieces together into a series of considerations that may be useful?

The TLDR; go on lots of dates, exploring more than you otherwise would. Commit to more serious relationships when they are great but don’t be afraid to end them. Be biased towards meeting more people rather than committing to any one person at least until your later 20s.

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What is your utility function?

I recall some study where they had people list their “type” before doing a round of speed dating. The people they liked the most in the speed dating were often quite different from the people they said they liked abstractly! Scott Alexander writes about the weirdness and diversity of interpersonal interactions that come from different vibes or “auras”:

A few years ago I had lunch with another psychiatrist-in-training and realized we had totally different experiences with psychotherapy.

We both got the same types of cases. We were both practicing the same kinds of therapy. We were both in the same training program, studying under the same teachers. But our experiences were totally different. In particular, all her patients had dramatic emotional meltdowns, and all my patients gave calm and considered analyses of their problems, as if they were lecturing on a particularly boring episode from 19th-century Norwegian history.

Variance in interpersonal vibes is very real and incredibly important, I think it partly explains why what we think we like on paper is totally different from reality. And this doesn’t even account for the fact that what we think we like may be simply limited because we don’t know what else is out there (see the next section). A friend, upon ending his first serious relationship and starting another said, “I had no idea what I was even compromising on.”

A fun extension on vibes dominating over expressed preferences is research on pheromones and maximizing MHC diversity. Potential partners “smell better” if they have very different proteins that present segments of pathogens to the immune system. This is a way for evolution to encourage a very high diversity of immune systems, hedging against any particular pathogen wiping everyone out.

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The Traffic Test

Wait But Why has a nice two post series on finding a life partner that starts here and re-states many of the points made in this post. The most memorable part for me is the Traffic Test:

I enjoy spending time with most of my friends—that’s why they’re my friends. But with certain friends, the time is so high-quality, so interesting, and so fun that they pass the Traffic Test.

The Traffic Test is passed when I’m finishing up a hangout with someone and one of us is driving the other back home or back to their car, and I find myself rooting for traffic. That’s how much I’m enjoying the time with them.

Passing the Traffic Test says a lot. It means I’m lost in the interaction, invigorated by it, and that I’m the complete opposite of bored.

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Heavy Tailed distributions

The distribution of possible relationships is heavy tailed whereby there is a much higher probability of outcomes at the extremes than otherwise. Ben Kuhn writes:

Because heavy-tailed distributions are unintuitive, people often make serious mistakes when trying to sample from them:

They don’t draw enough samples.

They underestimate how good of an outcome it’s possible to get.

They find it hard to tell whether they’re following a strategy that will eventually work or not, so they get incredibly demoralized.

This heavy tail is really important! A lot is at stake:

The difference between, say, a 90th and 99th-percentile relationship is relatively easy to observe: it only requires considering 100 candidates, many of whom you can immediately rule out. What’s harder to observe is the difference between the 99th and 99.9th, or 99.9th and 99.99th percentile, but these are likely to be equally large. Given the stakes involved, it’s probably a bad idea to stop at the 99th percentile of compatibility.

And things are worse because this assumes that all of these candidates are interested in dating you. Meanwhile, the distribution of possible outcomes is huge and average outcomes are bad¹:

In the US today, almost 50% of partnerships end in divorce, whereas the 99th percentile probably involves the couple being (on average) extremely happy with each other for 50+ years. In other contexts, this seems likely to be even more true; for example, in some low-income countries with regressive gender norms, over 25% of women who have ever had a partner experience domestic violence each year, which probably makes the average partnership extremely bad.

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Micromarriages

Finding a life partner is a binary event. It is also very difficult. This means most attempts like deciding whether or not to go on another date or to a party will almost always fail and feel disheartening. Chris Olah introduces the idea of “micromarriages” as a motivational tool to help handle this despair. You should imagine that every action you take to expose yourself to your potential life partner wins you “micromarriage” points and that in expectation, if you acquire enough of them, you will find a (marriage) partner.

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Sunk Costs and FOMO

Is the person you’re currently seeing the best you’ll ever meet? Ben Kuhn suggests a useful prior when considering the sunk costs of ending your current relationship: assume you have to put in the same amount of time and effort that you did last time.

Of course you may need to update this prior if you have moved locations, now have very different life circumstances, etc. but very often these considerations don’t apply or should only be small updates to the prior.

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Optimal Stopping Problems

This is the explore versus exploit dilemma in the form of how many different people you should date before committing to any particular one. This problem was initially called the “Secretary Problem” and has a number of formal mathematical solutions, however, they all make unrealistic assumptions like that you want to find the very best person and only this person, even finding the second best is considered a total failure. It also assumes that you have no prior knowledge about the distribution of people, that you have a clear utility function, and that it is costless to search and score different people.

None of these assumptions hold for dating so the Optimal Stopping Problem, while an interesting framework, is probably worth ignoring. A good summary of the Optimal Stopping Problem can be found in the book “Algorithms to Live By” and additional discussion of its practicality that inspired the above writing can be found here.

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Fertility

There are some really exciting innovations going on right now that will redefine who can have a baby and when. I think with 80% probability that within the next 5 years it will be scientifically possible (legislation will take longer) to create sperm and eggs from a skin cell. See this Twitter thread for a great summary of the players and opportunities involved:

Inside the startup companies trying to turn adult cells into oocytes.

🍼 Eliminate age limit ♀️ having kids

🍼 Large-scale embryo selection👀

🍼...♂️+♂️ Reproduction?

Early, but famous tech figures backing: Altman, Wojcicki, Armstrong, etc

🧵coming
https://t.co/s76ZeYCeEP

— Antonio Regalado (@antonioregalado) October 28, 2021

This research will have a number of consequences, an important one being the age at which women can have kids! For anyone in their late twenties or thirties reading this post, it means you may have more time to find a partner to start a family than you previously assumed.

However, it is likely people will still want to have kids when they are young enough that child birth and raising them aren’t too onerous. Moreover, you don’t want everyone else to find a partner and settle down while you are still single. There may also be some amount of averse selection where the people who are still available and single at older ages are lemons!

These caveats aside, this technology and others like it will give everyone more time and optionality to… say it with me… keep drawing samples from the heavy tail!

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Short and Long Term compatibility

A friend with a strong conviction about his current relationship draws this strength from the fact that they are highly compatible partners in both the short and long term. Maybe this is an obvious criteria but I found breaking down time over the short and long term to be a useful way of framing relationships.

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Get Online

An easy way to acquire more “micromarriages” by drawing more samples from the heavy tailed distribution of potential life partners is online dating! It does not need to be mutually exclusive from meeting people through friends/life events. In fact it is complimentary because it will expose you to all sorts of people from very different social graphs you may otherwise never meet (note that this can be a great or terrible thing).

Also, if you still think that online dating is weird or unpopular then I’ve got news for you:

If you’re going to stick with just one app then I recommend Hinge. You have to add answers to three prompts (there are a bunch you can choose from) like “unusual skills” and the answers to these can really help you get a first approximation to what someone is like.

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6 Months to Get to Know Someone?

As important as it is to draw lots of samples from the heavy tail, evaluating someone for life partner potential takes a lot more than a resume. Especially when figuring out if the person is in the 99 versus the 99.9th percentile. This raises the interesting question of how long it takes to get to know someone really well. It will certainly depend upon how open/vulnerable you are, how much time you spend together, the number of difficult situations that are encountered, etc.

It would also be ridiculous if getting to know someone better increased linearly. It should be some sort of step function with diminishing returns over time and probably follows its own heavy tailed power law in terms of the amount of information provided by each experience!

In light of this, I genuinely don’t know what the answer is and how to weigh this against the opportunity cost of dating other people. My current weak heuristic is around 6 months.

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A Piece of Your Heart

Going through dates and especially relationships hurts. This article in summary argues for drawing more samples than you otherwise might from a number of angles: heavy tails; longer fertility; online dating; However, I do want to acknowledge the difficulty of ending a relationship with two aspects in particular:

First, deciding to end a relationship feels like self sabotage. We live in a cold, harsh world where affection and trust are hard to come by. Here your partner is, providing these scarce resources, and here you are saying that you don’t want them anymore and that they should go away! Who are you to have the conviction and hubris to cast away such pure gifts that anyone would be lucky to receive?

Second, any relationship worth being in – where at some point you come to genuinely love the other person – will capture and keep a piece of your heart. Beyond the emotional heart loss, I have read that couples microbiomes will synchronize over time from kissing. And longer term couples will also use each other as external memory caches e.g. “honey what was the name of that place again?” so breaking up is literally losing your microbiome and a bank of your memories.

To put it succinctly, breaking up f’ing sucks. But life is long, the tails are heavy, who you end up with is easily one of the most important decisions you will make. As Wait But Why puts it:

When you choose a life partner, you’re choosing a lot of things, including your parenting partner and someone who will deeply influence your children, your eating companion for about 20,000 meals, your travel companion for about 100 vacations, your primary leisure time and retirement friend, your career therapist, and someone whose day you’ll hear about 18,000 times.

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Thanks to Max Farrens, Miles Turpin, Joe Choo-Choy, and Alexander Bricken for influential discussions and reading drafts of this piece. All remaining errors are mine and mine alone.

Footnotes