Icosian Reflections

…a tendency to systematize and a keen sense

that we live in a broken world.

Poker is a bad game for teaching epistemics. Figgie is a better one.

Editor's note: Somewhat after I posted this on my own blog, Max Chiswick cornered me at a conference and gave me a whole new perspective on this topic. I now believe that there is a way to use poker to sharpen epistemics that works dramatically better than anything I had been considering. I hope to write it up -- together with Max -- when I have time. Anyway, I'm still happy to keep this post around as a record of my first thoughts on the matter, and because it's better than nothing in the time before Max and I get around to writing up our joint second thoughts.

As an epilogue to this story, Max and I are running a beta test for a course on making AIs to play poker and other games. The course is a synthesis of our respective theories of pedagogy re: games, and you can read more here. The beta will run July 15-August 15, in-person in SF, and will be free but with limited signups.


Some trading firms are driven by good decisions made by humans. (Some aren't, but we can set those aside. This post is about the ones that are.) Humans don't make better-than-average-quality decisions by default, so the better class of intellectually-driven quantitative trading firm realizes that they are in the business of training humans to make better decisions. (The second-best class of firm contents themselves with merely selecting talent.) Some firms, famously, use poker to teach traders about decision making under uncertainty.

First, the case for poker-as-educational-tool: You have to make decisions. (Goodbye, Candy Land.) You have to make them under uncertainty. (Goodbye, chess.) If you want to win against smart competition, you have to reverse-engineer the state of your competitors' uncertainty from their decisions, in order to make better decisions yourself. (Goodbye, blackjack.)

It's the last of these that is the rarest among games. In Camel Up -- which is a great game for sharpening certain skills -- you place bets and make trades on the outcome of a Candy Land-style camel race. Whether you should take one coin for sure or risk one to win five if the red camel holds the lead for another round... Turn after turn, you have to make these calculations and decisions under uncertainty. But there's no meaningful edge in scrutinizing your opponent's decision to pick the red camel. If they were right about the probabilities, you shouldn't have expected differently. And if they're wrong, it means they made a mistake, not that they know a secret about red camels.

Poker is different. Your decision is rarely dictated by the probabilities alone. Even if you draw the worst possible card, you can win if your opponent has been bluffing and has even worse -- or if your next action convinces them that they should fold a hand that would have beaten yours. If you only play the odds that you see, and not the odds you see your opponent showing you, you will on average lose.

So as you grind and grind at poker, first you learn probabilities and how they should affect your decisions, then you learn to see what others' decisions imply about what they see, and then you can work on changing your decisions to avoid leaking what you know to the other players that are watching you. Or so I'm told. I would not describe myself as a particularly skilled poker player. I certainly have not ground and ground and ground.

Here's the thing, though: If you are a trading firm and you want to teach traders about making decisions uncertainty, it's not enough that poker teaches it. Nor is it enough that poker, if you grind for thousands of hours, can teach quite a lot of it. A quantitative trading firm is primarily a socialist collective run for the benefit of its workers, but it is secondarily a capitalist enterprise trying to make money. The question, for our trader-curriculum designer, is whether poker is the most effective and efficient tool for teaching the epistemic skills you want. Ideally in the first hundred hours or so.


♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡

In Orson Scott Card's Ender's Game, the child-soldier-generals aren't taught formation tactics by quarterbacking American football. They're all going to Battle School for months(?) of training, and the International Fleet can afford to teach them a new and made-up game. So the Fleet does give the children an entirely new game that's better-aligned with the skills they care about, a kind of zero-gravity capture-the-flag.

Back on present-day earth, our trader-curriculum designer is looking for a game that yields its lessons over dozens of hours of play among a group of traders (or interns) that work for the firm. They're going to do this year after year for class after class of traders and interns. For them, it is absolutely a live option to invent a new game out of whole cloth, teach them all the rules in an hour or two, and use it as the tool for teaching trading epistemics.

Jane Street, the trading firm, recently released a new version of its game Figgie for iOS and Android, so maybe we should talk about that, especially as it compares to poker. Figgie, somewhat like the Battle School game, was invented in-house specifically to train less-experienced soldiers interns in the skills of war trading. The rules are here if you're curious, but this post should make sense even if you don't tab away to read them.


♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡

This might be a good time for a disclaimer. I worked at Jane Street from 2016 until 2022. For large parts of that time, I had responsibility for parts of the internship training program, including countless games of Figgie. I organized the first, second, and third Jane Street recruiting events where we taught Figgie to attendees on college campuses. And I won Jane Street's 2021 inter-office Figgie championship.

Okay, a slightly less self-congratulatory disclaimer: This month I learned that Jane Street had a public Figgie website at all. So I've been out of the world for a while, as it were.

Finally, Jane Street has not reviewed or endorsed the contents of this post, and has no editorial rights over what I write except those defined by the confidentiality agreements I signed as an employee. (I'm not under any non-disparagement agreement to Jane Street or any other former employer, for what it's worth.) This post is a review of the public features of a now-public game. My description of how Figgie might be used in a hypothetical educational curriculum should not be read as a close description of Jane Street's own use of the game, which in nontrivial ways differs on some of the points I suggest here.


♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡

I lied -- I want to talk about poker a bit more. What's bad about poker as a teaching tool? (I'll expand on each of these later on.)

  • Most decisions don't give you feedback on whether you were right for the right reasons, right for the wrong reasons, wrong for the right reasons, or wrong for the wrong reasons.
  • If your playing partners aren't sufficiently skilled at the game, you'll learn bad lessons.
  • It takes too long to get good enough to squeeze the real educational juice out of the game.
  • Players spend the supermajority of their time at the table not playing the game and not making decisions.
  • By convention, a very tiny fraction of game states happen under a very high level of emotional stress, and if you consistently get those wrong and your playing partners realize it, they can manufacture much more of them to make you lose.
  • The mechanics of the game create some instincts that are downright perverse for actual trading.

Figgie, as an educational tool, has the advantages of poker that I listed and avoids these downsides. For that reason, it's a straightforwardly superior game for teaching traders (or anyone else) about making decisions under uncertainty, interpreting decisions made under uncertainty, disguising the interpretation of decisions you are making under uncertainty, and so on. (It has its own bad parts too, and if you use it as your only teaching tool, I suppose your trading firm will get what's coming to it.)

In Figgie, you make decisions, and you make them under uncertainty. More than that, you watch others make decisions under uncertainty and work to reverse-engineer what they know from their decisions. Even more so than in poker, the effects of your decisions interact directly with the nature of the uncertainty in a way that hammers in deep lessons about the hard parts of trading in markets. But also...

In poker, most decisions don't give you feedback about whether you were right for the right reasons. In traditional Texas Hold 'em, players nearly always fold their hands without revealing them to the other players, nor do they reveal their winning hand when their opponent folds. The only situation where anyone sees any cards other than their own is if two players stay in through the final round of betting (and even then, the second player might not show if they realize they've lost to the first-showing player). As a matter of competitive strategy, it's somewhat to your advantage to hide how you're playing certain combinations of cards from your tablemates.

But if you play 30 hands an hour and 5% of deals go to a showdown, there are just 2.25 player hands shown to the table every hour. This is terrible if you're a learning player trying to understand how better players play the game! On the rare occasion that I sat in on after-hours poker games with student-interns, I nearly always insisted that we fix this particular flaw by showing all folded and winning player-hands on any hand with betting, but even then it's not great.

By comparison, in Figgie, you see all four players' hands every game, and you might play 12 games an hour, for 36 chances to see why someone else played how they did. And when you do, the cards themselves can tell you how it worked for them.

If your poker playing partners aren't sufficiently skilled, you'll learn bad lessons. The rarity of revealed hands is particularly bad in a less-skilled or semi-skilled group, because nearly all of your actual feedback about hands won or lost will be based on the assumptions of your opponent in that hand.

If your opponent makes bad assumptions or bad decisions, your decisions won't be rewarded properly, and it can take you a very long time indeed to figure out from first principles that that is happening. If you are playing with a player who thinks that "all reds" is a strong hand, it can take you many, many hands to figure out that they're overestimating their hands instead of just getting anomalously lucky with their hidden cards while everyone else folds!

Is someone who knows more about poker than I do going to tell me that this specific example is wrong-ish? We'll find out!

There are certain strategies in Figgie that work on less-skilled players and don't work well on more-skilled players, as there are in any interesting game. But for the most part, a smart and dedicated group of new Figgie players in their first twenty or so games will have re-discovered roughly reasonable play that will reward better play. The game very nearly teaches itself, including its strategic depth, and makes it easy to update towards better habits even if your entire playgroup starts without a clue. Helping matters further, the misconceptions that you do have tend to get sanded down fairly rapidly by the game's results.

Making all this even worse (for poker), it takes a long time to get reasonably good at poker. The consensus opinion I found on poker forums is that it takes between 500 and 1,000 hours to become "good" at the game (according to forum-posters, I guess). I'll assert that no matter how educational you think poker is, it's not really efficient for your staff to spend three to six full-time months learning the game. And in my personal experience, the first part of that learning curve is a bit of an unforgiving wall where it is hard to be learning any transferable skills while you're still trying to get the game-specific fundamentals down.

By contrast, Figgie's learning curve is relatively forgiving, and it's mostly teaching good lessons even while you're scrambling (so long as you have the mechanics of trading down, which I claim takes barely less time than learning how and when to bet in Hold 'em). Players get a lot out of a few dozen hours without the long slog through gittin' gud.

Poker players spend most of the time at the table not making decisions. One of the greatest hazards for a beginning poker player is that they will make bad decisions because they want to play more poker instead of exiting hands just after seeing their cards. But this is understandable, because correct Texas Hold 'em play involves immediately folding something like 75% of the hands you are dealt!

Unhelpfully, when you correctly fold but two of your eight tablemates get non-foldable hands, then you get to spend several minutes watching them play poker, very likely won't see their cards, and then finally get dealt the next hand (which you are probably supposed to fold). In the rare hand that you do play, you'll spend half your time waiting for your opponent to make a decision. There's a reason that professional online players play four or more different tables at once -- you spend only a small fraction of the time making decisions, and the vast majority of it waiting for others to play poker.

In Figgie, I'd estimate that every player at the table has something to be doing for 75% or more of a 4-minute round, and the dead time between rounds in a fast-moving table can be well under 20%. That's an action-to-dead-time ratio that pulls ahead of the John Wick movies (which blow nearly every other "action" movie out of the water).

A few poker situations turn the emotional stakes way up, past the level that's helpful. To a first approximation, the stakes of a decision in poker go up literally exponentially in the rounds of a single hand. In Hold 'em, it's not unusual for the stakes of the fourth round of betting to be several hundred times the initial stakes (unless someone folds before then). Since it's conventional for the initial stakes to be an amount of money that you'd at least notice losing (say, a dollar), stakes hundreds of times that can be...stressful.

It's commonly argued that it's helpful for traders to train a lower level of risk aversion for non-fatal bets, but I would submit that it's counterproductive to be training that risk tolerance while teaching another important lesson. Though these late-round high-stakes situations are rare under proper play, a player who makes systematically conservative choices in high-stakes situations (specifically, by folding more often) can be exploited by other players pushing them into the high stakes in order to get them to mis-play. So an emotional bias that is tough to scrub from a small set of situations can bias an entire table's worth of play for the worse and the less-educational.

Bets in Figgie range from 1 unit to 59 units, and in practice the vast majority of "big" decisions will only have stakes ten or fifteen times larger than the smallest ones. This amount of range rewards players for thinking about the more-valuable actions first, but still lets a group set the cents-per-betting-unit stakes to be meaningful at the small end without being unproductively stressful at the high end.

Certain poker metaphors are perverse in real trading. There's no natural analogue of a poker bluff in quantitative trading. While you may be trying to hide your very best trading among your merely-good trading so that the extremely-attentive don't find out what you're doing, I sincerely hope that you never have reason to hide your worst trades in with your best ones as part of a mixed strategy! Meanwhile, the skill and instinct of mixing ranges and reading mixed ranges is at the heart of mid- and high-level poker strategy (I am told; again, I'm not a particular expert here).

Figgie, as a game whose core metaphor is directly about distinguishing between positive-sum and adversarial trading, mostly trains instincts that make good fundamental sense in markets. For example:

  • If you overpay for a valuable asset, you lose out on the amount of your overpayment; if you miss out on an asset, you lose the entire potential gain. (The risks here are asymmetric, but also strongly context-dependent!)
  • It's valuable to identify assets that are overpriced as well as those that are undervalued (if and only if you have the ability to sell them).
  • Other traders looking to buy a thing can make you want to buy it more. (The effect on your estimate of its value can be sublinear or superlinear, depending on context.)
  • Other traders looking to buy a thing from you can make you want to sell it less.

There are some artificial tricks to learn ("when someone is buying cards and suddenly stops, it means they got five of that suit"), but much fewer than in poker.


♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡ ♡

I don't want to claim that Figgie is the perfect game; it has its own shortcomings and flaws.

  • It gives an unearned advantage to a kind of aggressive bias-towards-action that not all your trainee-students will have. There's more than one way to be smart than thinking the fastest on your feet, and folks from historically-underrepresented backgrounds will have less of the one that the game rewards.
  • The physical mechanics and symbolic metaphors of the game will be familiar to some and alien to others. (Not everyone knows what the playing-card suits are, or what they're called, or is fluent at making fast change for colored chips. None of those things are helpful for being a better trader.)
  • Dollar-by-dollar negotiation and manual decision-making are of limited direct value in modern quantitative trading, since most of the interesting action is taken over by computer programs. (I'd argue that having some feeling for what you're getting the algorithm to do is helpful, but there's an upper bound on its usefulness.)
  • Not everyone finds the game fun, and some of those that don't find it fun do find it stressful.

These shortcomings, I should note, tend to have the effect of further disadvantaging student-players from historically under-represented groups. Any institutional educator using Figgie should thoughtfully account for that fact, or their efforts will feed structural biases already being pushed by the systems around them.


(comment on this post on LessWrong)