My Friends Danny and Amos, Regression Effects, the Chiefs, and Sports Commentary.
In Business Law, our professor talked about the power of System 1 and System 2—our automated selves and our deep-thinking selves—and said he learned about them from a book, Thinking, Fast and Slow, by Nobel Prize in Economics winner Daniel Kahneman. Just a few days later, my Decision-Making Analysis professor also made reference to Systems 1 and 2. Two mentions of the same concept in such short time by two people I admire demanded I investigate.
I ordered Thinking, Fast and Slow. When it arrived, I dove in. I read about 30 pages before the book lost me. It sat on a pile of other greats like A War Like No Other, SPQR, Fear, and Directorate S—all books I’ve started or perused but haven’t fully dedicated the proper time to read deeply.
Not long ago, while walking through the bookstore, I saw a section dedicated to Michael Lewis. I’ve always enjoyed Lewis; I was struck by his first book Liars Poker, and I’ve followed him ever since. Somehow, though, I missed one of his recent works, The Undoing Project, so I picked it up. Sure enough, the book was about Danny Kahneman and Behavioral Economics. I bought and read it in three days. The book outlines Kahneman’s life and relationship with Amos Tversky, another Israeli psychologist. I’m not going to dive into everything they write about here. I will say, though, that Thinking, Fast and Slow has, thus far, had as profound an impact on how I think as Hans-Georg Gadamer’s Truth and Method, a magnum opus that explores the nature of understanding through philosophical hermeneutics.
Lewis’s book proved an excellent introduction to Kahneman. After I finished it, I returned to Thinking, and I’ve been chipping away at it ever since. I’ve talked about Kahneman so much lately that Jennifer has started referring to Kahneman and Tversky as my “good friends Danny and Amos.” It’s a riot, really.
What brings me to this topic today has to do with the Chiefs making the AFC playoffs against the Patriots and the upcoming Super Bowl. I have this tradition—well, I call it a tradition—that I’ve followed for eight of the last nine years where, on Super Bowl Sunday, I go to Wichita State University’s Ablah Library to read and research until an hour before kickoff. This is my protestation to the mindless, useless goings-on of wall-to-wall coverage leading up to kickoff. Pregame has done nothing but devolve over time. I decided years ago I would take this time to learn something new instead of sit around all day watching Chris Berman speculate on unknowable outcomes in between outtakes from the Puppy Bowl.
This leads to my good friend Danny.
Essentially, Kahneman tests and confirms his theory that we as a species are terrible at statistics. Moreover, our System 1—the automated part of how we think—fails to engage System 2, the deep-thinking part of how we think, when probability is involved to process data. Instead, “our mind is strongly biased toward causal explanations and does not deal well with ‘mere’ statistics. When our attention is called to an event, associative memory will look for its cause—more precisely, activation will automatically spread to any cause that is already stored in memory” (Kahneman 182). We assume the story causes the event. When out-of-the-ordinary events occur, Kahneman suggests, we seek stories to explain them instead of recognizing that what we see is a digression from and a regression to the mean. Golfers who succeed on the first day of a tournament usually perform poorly on the second day. This has little to do with the pressure they face; they merely regress to the mean. On the other hand, golfers who perform poorly on the first day typically perform better on the second day. They don’t rise to the occasion; they regress to the mean. Kahneman devotes an entire chapter to the following equation: Success = Talent + Luck. He calls it his favorite equation, and he elaborates with: Great success = A little more talent + a lot of luck. Danny then deconstructs and debunks the Sports Illustrated cover jinx.
We search for stories to explain actions when no story accurately correlates with the cause. The action has an explanation—regression to the mean—but it does not have a relatable cause.
Kahneman goes on to say that “we pay people quite well to provide interesting explanations to regression effects” (182). When I read this, I thought immediately of Super Bowl Sunday. (I also thought of Fran Franschilla, who has increasingly grown on my nerves). Sports commentators do nothing but apply causal explanations to the regression effects of sport. “He’s heating up” means he has regressed to the mean. “He’s gone cold” means he’s regressed to the mean. Ad infinitum. Since the big games are upon us, it may be worth listening to sports broadcasters to ask if they’re creating causal explanations to regressive effects.