Three Gambling Lessons From College
No One Invites Gamblers to Give Commencement Speeches So I Wrote One As Proof of Concept
On the subway this month, I keep seeing diplomas and philosophy books I read in college. I’m excited for a possible philosophy renaissance (or small sample anomaly?), but I have to admit I remember very little of what these books said. The sightings got me to think about what I truly retained from college and how it helped me. Here are some gambling lessons from college.
I: The IQ Test and Correlated Errors
I had the lowest IQ score in my freshman neuroscience lecture course (n ~75). I know this because the professor tested us, emailed each individual his/her result, and then showed the scatterplot of the results on a projector at lecture. He noted that those with low scores could still succeed with social skills and determination. If this sounds cruel, recall that 2010 was a different era in terms of expected empathy from authority figures in liberal spaces; we have to judge people by the times in which they lived.
The professor believed two things strongly:
That there was a single form of intelligence - fluid intelligence - that was highly correlated with real world outcomes.
Fluid intelligence could be measured by the Raven’s Progressive Matrices Test. The test asks test-takers to observe a series of images and then pick the next image that fits the pattern.
I think the best argument against the test is not statistical but logical. The test has the same logical structure as “1,4,11… pick the next number”. There are infinite numerical functions that could generate any subsequent number; likewise, there are infinite image patterns that could generate “the next image”. Even if the test was extremely correlated with other measures of intelligence, the logical problem would remain. My view is a minority view.
In 2016, the professor became famous as a political pundit and built a popular political science model that said Hillary Clinton had a 95+% chance of winning. A key feature of the model was that state polling errors were uncorrelated. As it turned out, the errors were quite correlated; “shy Trump voters who didn’t trust pollsters” lived in multiple U.S. states.
Overconfidence is a human attribute that generates correlated errors. The same impulse that might make you think human intelligence could be adequately captured by a “pick the next image matrix test” might lead you to build an error covariance matrix with a few too many zeros.
People often say gambling imposes a tax on overconfidence. That’s true but it gets even better: it imposes a tax on models that strip the world of its richness.
II: The Oligarch’s Son and Loose Money
The arrival of the oligarch’s son on campus heralded new hustles: could the sale of a state-owned industry in the 90s indirectly fund your massive party? Did he have an alcohol guy?
One of my roommates was good at poker and he told me about a game the oligarch’s son had spun up that was now attracting people. I joined despite being a pretty mediocre player.
The joy of this game was that its expected value was largely determined by the delicate dance at its onset: who would sit to the left of the oligarch’s son. He played like a “maniac”, constantly raising and re-raising bets; to be the first beneficiary of that was very high-value. But the collective problem was that we couldn’t make it too obvious - lest our benefactor get offended - and so began the dance to sit close to him.
High-stakes gambling is built around relationships like this. Athletes, actors, and middle-aged executives look for an adrenaline rush or companionship or a certain fleeting feeling of danger; professionals seek them out and become economically dependent on them. The friendships formed between groups are real but economic in basis. Professionals must make decisions about their time: study the game more or try to find a new game with an even worse, even richer player.
But really, it’s not just high-stakes gambling that is like this. At elite schools, people without money also seek out the people with money and connections. The economy rewards competence but it also rewards proximity to money. At least in my life, it’s seemed to me that getting closer to loose money is often the better play than honing one’s professional craft. That’s one reason why I trade prediction markets instead of equity options.
III: What’s Next
The smartest guy I knew in college (~2011) bought bitcoin because he thought it would be fun to go long a burgeoning religion. I told him Bitcoin was valueless. In 2013, he said “cloud is going to be big”, learned to code really well, and then became a tremendously successful SWE. I thought SWE might be a fad. He told me sometime in 2019 that video ads were “about to get 20x more prevalent” and the internet “a lot worse”. I thought it was overblown. Shortly thereafter, he quit, went to divinity school and now works as a mental health counselor at an outpatient ER. He says I should read Jung. I’ve given up doubting.
We are all subject to social forces mostly beyond our control. Poker has had at least two deaths: Black Friday and the recent tax bill. Sports gambling got two leases on life: PASPA and then the rise of prediction markets. Each of these shifts causes new entrants and exits. The looming Supreme Court case on prediction markets is likely the next big shift.
I really liked one philosopher I read in college. His name was Rudolf Carnap. In 1934, Carnap, a famous member of the Vienna Circle, wrote that his attempts to find the logical structure of the world had not born fruit. In fact, he now concluded that the world had no logical structure at all. For example, there was not one universal set of mathematical axioms; rather, one could construct equally valid mathematical systems with different axioms. He found giving up on absolute truth liberating because he could experiment with different logics, languages and systems. Before fleeing to the U.S., he concluded his last major European work with this line:
"But now this barrier is overcome: before us lies the open sea of free possibilities."
When the 7 train emerges from underwater in Queens, a diverse group of people who speak different languages turn back to see the Manhattan skyline rise above the East River. It’s when I witness this that a philosophy quote from college comes back to me.