Updated: Oct 20, 2022
Uncertainty is a normal part of life. Whether in our professional lives or personal lives, we frequently face decisions laced with uncertainty. Of course, the vast majority of our decisions occur outside a casino! For this article, we define casinos, confidence games, and similar as uncertainty-orchestrated situations. We believe that uncertainty-orchestrated situations have much to teach us about uncertainty and ourselves. The goal of this article is to a) explore a few uncertainty-orchestrated situations, b) apply fundamental decision-making concepts, and c) help us learn to make better, more confident decisions.
Author's personal statement: I really do not care much for gambling and I certainly do not condone swindling people out of their hard-earned money. I do not even find gambling entertaining. As such, I am an objective observer when it comes to gambling. Ironically, my mother loves to gamble. She has developed an amazing ability to both have fun and limit her losses. Perhaps there is hope for me yet!?
As a starting point, the following are some of my favorite books, movies, and games related to gambling, forecasting, and a "confidence game"-based con:
Bringing Down The House by Ben Mezrich
The Confidence Game by Maria Konnikova
Catch Me If You Can by Frank Abagnale
Superforecasting by Philip Tetlock and Dan Gardner
Bad Blood by John Carreyrou
Focus, a movie written and directed by Glenn Ficarra and starring Will Smith and Margot Robbie
The Sting, a movie directed by George Roy Hill and starring Paul Newman and Robert Redford
Games such as Backgammon, Hearts, Bridge, Rummy, and Blackjack.
Generally, I refer to uncertainty-orchestrated situations as the uncertainty environment described by these books, movies, and games. Those situations may involve casinos, confidence game locations, or even your home if you are hosting a game of hearts.
Later in the article, I offer three examples to show:
What a favorite scene from the Will Smith movie “Focus” teaches us about cognitive biases;
What the backgammon board game teaches us about probability, hedging, and risk management principles; and
What a nuclear physicist teaches us about forecasting with a simple "back of the envelope" approach.
The admission of a fish: Since these books, movies, and games may involve gambling in some form, you may wonder why a “gambling-agnostic” person like me would appreciate them. First off, if I could find a way to profit from gambling, I would probably like gambling. The truth is, much of my economics training and life experiences tell me I would fail miserably at gambling. When asked about buying a lottery ticket, I am more likely to grumble about the regressive taxation of the poor. Based on this sentiment, I appreciate that I am pretty low on the gambling food chain. To wit:
A casino or related house system is designed to beat even the most experienced gamblers, which leads to
Experienced gamblers honing their skill to beat novice fish gamblers. This leaves the stark reality that
I am a lowly fish, outgunned by the sophisticated house systems and experienced gamblers.
Therefore, as a fish (aka: chum) - I see little gambling upside.
To be fair, it is possible for a fish to move up the food chain. Some gamblers learned to exploit imperfections in the sophisticated house gambling systems to earn positive net payouts. Sure, it does periodically happen. The "Bringing Down The House" story is about such a house beating scheme. A group of MIT students and a professor developed a fascinating team system to beat the house. But much the way it is the nature of financial markets to quickly close bid-ask spreads, the casino ultimately discovered the MIT crew's house-beating gambling system and quickly shut it down. For me, this becomes a question of risk, return, and swimming with the current. The risk, mostly the cost in time and the opportunity cost of not doing other cool stuff with my life, is likely far in excess of the potential return. Achieving this return involves matching wits and swimming against the current of a very sophisticated house gambling system. A system designed to separate me from my money. I am reminded of Thomas Jefferson’s famous aphorism:
“On matters of style, swim with the current, on matters of principle, stand like a rock.”
Gambling can be a lifestyle and I'm a self-admitted fish. There is a certain freedom in accepting my plight as a fish - I can get on with my otherwise fulfilling life and avoid the sharks.
The admission of a curious character: The essential reason I like these books, movies, games, and their related uncertainty-orchestrated situations is brought about from curiosity. My curiosity is prompted from my experiences as a behavioral economist and my deep appreciation for probability theory and behavioral science. I study disciplines that channel giants in the fields, like Thomas Bayes and Daniel Kahneman. While I may not like casino gambling, I do appreciate the many things I can learn from others who gamble. Undeniably, life involves a series of gambles. The great majority of these occur outside a casino.
I enjoy playing probability-inspired games and my career and occupations make regular use of probability. As a means to explore my curiosity, gambling makes extensive use of probability. In a gambling environment, the gambler is a study in behavioral economics - especially the impact of loss aversion, sunk costs, and a variety of cognitive biases. Cognitive biases are on full display in a casino and are the target of a confidence game. The books, movies, and games listed above provide examples and ideas for how probability and cognitive biases affect people. They certainly feed my curiosity. I consider them as a means to explore and test, but without suffering the plight of an oblivious fish. To dig deeper, please see the article: Curiosity Exploration - An evolutionary approach to lifelong learning
Next, allow me to provide a few curiosity-enabled examples:
The movie Focus and exploring anchoring bias. Anchoring bias is one of our big decision-making cognitive biases. I consider the “Big 4” decision cognitive biases as anchoring bias, availability bias, representativeness bias, and groupthink. Anchoring is typically leveraged by salespeople and foundational to a confidence scheme. The Will Smith and Margot Robbie movie provides a fun and high-impact example of anchoring bias. SPOILER ALERT: The next couple of paragraphs reveal a movie scene.
The exemplar scene is when the Smith character makes a seemingly sure-to-lose bet at a football game with a high-flying tycoon. This scene is super entertaining and the "good guys" win the bet. This occurs by a seemingly outrageous stroke of luck, as the Smith character won the bet when both the tycoon and the Robbie character pick the same player's number 55. On its face, if:
each football team has 80 players and
each football team has a similar number set from which to choose,
then the probability baseline of 2 independent and random number pickers selecting the same number would be VERY LOW. [ (1/80)^2 = .02% ] Earlier in the movie, it was revealed the Robbie character was an insider. Because she is an insider, it is not surprising that she picked “55.” So this raises the baseline probability to 1/80 or just over a 1% chance that the tycoon would pick “55”. While an improvement over .02%, it is still a horrible bet for the Smith character. So how did he win the bet?
This scene is later explained as a prototypical example of anchoring bias and using psychology to greatly improve a random probability baseline. They show how the tycoon was anchored to the number "55" by a series of subtle but effective nudges as the tycoon approached the football stadium and his suite. The tycoon's set of player number alternatives was craftily reduced by a series of well-placed psychological anchors. By the way, the anchoring nudges described in the movie are comparable to when a car salesperson suggests you take a car out for a test drive.
To be fair, we can all imagine how this “made for Hollywood” bet could have gone wrong for the Smith character. But it is still a nice example of the impact of psychological anchors in our decision-making. To dig deeper, including more context on decision cognitive biases, please see the article: Great decision-making and how confidence changes the game)
Backgammon and learning risk management by playing a game: I’ve often thought of backgammon as one of my best risk management teachers. The game is a deceptively simple and powerful metaphor for managing risk in our life‘s pursuits.
While backgammon’s rules are simple, the application of probability and risk management principles is what makes the game very relevant to the game of life. Also, game success isn’t just about applying probabilistic knowledge*. Probabilistic knowledge is game table stakes. As an experienced backgammon player knows, no matter how skillful they are, a beginner could always humble you. No matter how sophisticated our choices and how good we are at dominating the odds, randomness will have the last word. Dice add a realistic element of uncertainty representative of the dynamic game of life. Every roll-of-the-dice turn requires an application of the U.S. Marines motto:
"Improvise, Adapt, and Overcome."
Long-term game success is also about understanding how to hedge positions and how to manage your risk of ruin. Long-term winning strategies include managing our cognitive biases [i] and providing emotional control, like control of greed, fear, and pride. Also, long-term winning strategies include knowing when to take a small game loss to protect yourself from ruin and maximize match winnings.
“One may be risk loving yet completely adverse to ruin.”
- NN Taleb
Einstein’s suggestion to honor the intuitive mind is certainly relevant to backgammon and risk management.
"The intuitive mind is a sacred gift and the rational mind is a faithful servant. We have created a society that honors the servant and has forgotten the gift."
For backgammon, our "faithful servant" applies probability, and the "sacred gift" provides for long-term winning strategies. Both are necessary for game success! To dig deeper, please see the article: Fearless: Learning risk management by playing a game.
Forecasting and the wisdom of Enrico Fermi: Dr. Fermi was a world-leading physicist that lived during World War Two. His lab was based at the University of Chicago and his contributions include nuclear power development. He was deeply involved in the Manhattan Project. Separate from his work on nuclear energy, he developed a simple but very effective way to make forecasts. While this is technically not meant as a gambling method, Fermi’s method helps with life's gambles as it involves predicting uncertain future events.
The method includes breaking the question down into the pieces needed to properly answer the forecast question. The method will help separate the knowable from the unknowable. This also enables us to intuitively use the concepts of conditional probability. Then, the smaller parts of the question individually have less impact on the variability of our total uncertainty. It also focuses the forecaster on a small number of more answerable questions. In today’s networked world, there is an amazing amount of information available if someone knows the proper question to ask google. To dig deeper, please see the article: Changing Our Mind.
From a cognitive bias standpoint, reducing a bigger question to its component parts, helps us do two things:
The smaller questions help us avoid representativeness bias, which is answering a harder question by inappropriately substituting an easier question; and
The smaller questions help us avoid anchoring bias and getting stuck in our beliefs. Often, people may get inappropriately anchored in a starting point because it is “what we have always believed.”
The Fermi method helps us get unstuck in our beliefs and achieve the mindset advanced by author Philip Tetlock:
“…beliefs are hypotheses to be tested, not treasures to be guarded.”
The Fermi method was showcased in the book Superforecasting. Check out Fermi’s famous example for estimating the number of piano tuners in Chicago! The question of piano tuners is obscure and relatively difficult to determine, even with google resources. However, if we break it down into the following pieces, the question becomes more able to be properly estimated:
The number of pianos in Chicago
How often pianos are tuned each year
How long does it take to tune a piano
How many hours a year the average piano tuner works
Tetlock suggests the best forecasting decisions share a few methodological similarities:
Unpack the question into components.
Distinguish as sharply as you can between the known and unknown and leave no assumptions unscrutinized.
Adopt the outside view and put the problem into a comparative perspective that downplays its uniqueness and treats it as a special case of a wider class of phenomena.
Then, and only after the outside view has been taken, adopt the inside view that plays up the uniqueness of the problem.
Pay attention to the different views of others.
Synthesize the views of others.
Express your judgments as finely as possible, using a finely-grained probability scale.
The casino, confidence games, and other uncertainty-orchestrated situations are a teacher. One can learn from them without suffering the fate of a fish. Seeking mastery of probability and human nature are useful decision-making habits for the game of life.
[i] A cognitive bias associated with backgammon is attribution bias. This is also known as self-serving bias. This bias originates from the psychological concept known as locus of control. The bias suggests that we naturally attribute winning a game of backgammon to our ability. (An internal locus of control). Whereas we naturally attribute a backgammon loss to bad luck. (An external locus of control) The truth is a single point in between. Because of the random variability introduced by dice to backgammon, the truth is likely closer to luck than ability. To dig deeper into locus of control and how attribution bias impacts relationships, please see the article:
Hulett, Choosing Joy, The Curiosity Vine, 2022