The college football season is upon us. On game day, the team captains will meet at the 50-yard line for the coin toss. “Heads or tails?” the referee will ask. The home team gets the seeming advantage of picking their option. It is a 50/50 proposition. Yet, 80% of the time, the captain of the home team will choose heads. Hmmm. Why? The answer may lie in how our brains’ function, or, rather, how they malfunction. It is called cognitive bias. In this coin toss example, the cognitive bias is “framing.” Because the referee states “heads” as the first option, more people chose “heads.”

Daniel Kahneman and Amos Tversky pioneered the research on cognitive bias as part of the field of behavioral science.1 Kahneman described the theory in his book, Thinking, Fast and Slow. 2 According to behavioral scientists, humans are incapable of easily processing large amounts of information. As a result, in decision-making the brain relies on intuition and known experience to make a quick and efficient choice. Kahneman described this process as System 1. System 1 works well when presented with small amounts of information. For example, 2+2 is easily solved as 4. But, what about 27 x 93? This more complex problem cannot be solved by System 1. Instead, the brain must resort to System 2. This requires gathering information and relying on learned skills, such as math, to solve the problem. Here is where the brain falters. Rather than take the time to fully analyze the problem presented, the mind reverts to System 1 thinking.3

This mode of thinking is labeled as biased, not in the pejorative sense, but because the method of decision making does not yield the optimal answer. System 1 was necessary and useful when it allowed a quick escape from a lion lying in wait. Fight or flight requires immediate action. A thorough analysis of the odds of being eaten by a lion could end badly.

In the last fifty years, cognitive bias has become widely accepted as an explanation of human decision making relating to microeconomics and legal rights and duties. This was a departure from the neoclassical theory of a rational and efficient marketplace that had gained acceptance following World War II. This theory was based on the principle that “human behavior can be viewed as involving participants who [1] maximize their utility [2] from a stable set of preferences and [3] accumulate an optimal amount of information and other inputs in a variety of markets.” 4 The rational theory posited that each individual decision would be made in order to maximize total wealth, including the acquisition and disposition of legal rights. Different people, with the same information, would reach the same decision. This theory was adopted by lawyers who had a free market view of government– if government stayed out of the way, the decisions of rational actors would properly order legal rights. It is reflected in the Coase Theorem, proposed by Ronald Coase in 1960. The Coase Theorem stated that property rights would be efficiently distributed, as the person who valued it the most at any given time would acquire it.

The impetus behind the work of Kahneman and Tversky was their observation that the theory of rational actors was not an accurate description of human behavior. They conducted numerous experiments, which led them to develop the Prospect Theory.5 The three principles of the Prospect Theory are: (1) people did not act rationally (bounded rationality); (2) people’s actions were influenced by their emotions and feelings, not efficient utility (bounded willpower); and (3) people were self-serving (bounded self-interest). Individual decisions were not part of a greater rational framework where participants looked to maximize their state of wealth. As Kahneman wrote, “The effective carriers of values are gains and losses, or change in wealth, rather than states of wealth as implied by the rational model.”6 The Prospect Theory led to the formulation of the “endowment effect”–people value an item they own more than one they wish to acquire. Because of the endowment effect, sellers make excessive demands for property they own. Buyers refuse to pay, and the property remains with the seller, which may not be the most efficient outcome. Kahneman described this as a “kink” in the supply and demand curves, as property rights did not trade hands efficiently.

Another significant finding related to the endowment effect was that people are risk adverse when dealing with gains, but risk taking when dealing with losses, even when such decisions are not optimal. This is called “loss aversion.” For example, investors are reluctant to sell a stock at a loss, even though the best strategy is to sell a losing stock and invest the proceeds in a different stock.7 Even those most proficient at a skill are affected by loss aversion. An analysis of over 2,500,000 putts in professional golf tournaments over a one year season, showed that the best golfers in the world were much more cautious on birdie putts (gain) so as to ensure a par, rather than a bogey (loss); the golfers were loss adverse on birdie putts in order to ensure at least a par. 8 A golfer who was less risk adverse could lower their aggregate score by one stroke over the season and earn seventeen percent more, or an average of $640,000.00.9

There is an ongoing and sometimes bitter debate between the behaviorists and the neoclassicals, particularly as to the use of cognitive bias to shape legal policy.10 The thrust of the debate is that the rationalists think cognitive bias is junk science. The behaviorists respond that they are only reporting actual results and freely admit that there is no explanation as to why people are subject to cognitive bias.

The criticisms of cognitive bias are not well founded. Consider a 50/50 probability event in another setting. Like a coin toss, roulette is equal odds of a binary choice of the ball landing on black or red. The odds are the same on the first spin and every spin into eternity. However, people fall prey to the idea that prior spins influence the current spin. This cognitive bias is called the “Gambler’s Fallacy.”11 In 1913, in a Monte Carlo casino, this thinking was costly. The ball kept landing on black. As word spread quickly, more and more players placed their bets on red. The gamblers believed that so many consecutive spins with the ball landing on black meant that ball had to land on a red number, and soon. Twenty-six consecutive rolls of black proved very expensive to those betting on red. Millions of dollars were lost in a short time span.

Gambler’s Fallacy occurs not because people do not know the laws of probability, but rather it occurs because people ignore the laws of probability and other forms of learned thinking.12 When presented with facts and evidence that contradict our opinions and beliefs, we ignore the information. This is called confirmation bias: the tendency to accept information which validates our opinion, the refusal to seek out information which is contrary to our opinion, and the rejection of information which shows why we are wrong. For example, although statistics show that the casino always wins, gamblers are convinced they have a method or a system that will beat the odds.

Most recently, the use of functional MRI brain imagery and other studies of the brain, show that different parts of the brain are activated consistent with cognitive bias when making decisions under risk.13 In one study, people who had lesions on their amygdala, the region involved in decision-making showed higher risk taking propensity in loss situations.14 In another study, the effect of marketing tactics on the brain function confirmed outcomes consistent with cognitive bias.15

There is an enormous body of scientific work that validates cognitive bias.16 The contention of the neoclassical advocates that cognitive bias is not a valid model of human decision making is belied by simple observation, as well as statistical modeling which shows the effect of cognitive bias. The larger debate about what are the best policies and laws is an important one, but it fails to consider that human decision making is not going to stop while the debate continues. We are constantly bombarded with information and are required to make decisions under risk. The job of a lawyer is to advise clients, which is decision-making. As we will see in next month’s article, the impact of cognitive bias on legal decision-making has been widely studied and documented. Lawyers, clients, judges17, and juries18, are all subject to cognitive biases. A lawyer who understands cognitive bias and can consider whether to adjust his decision making will have an advantage, which will benefit both the lawyer and his client.

References

1. Kahneman won the Nobel Prize in Economic Research in 2002 for his Prospect Theory, which is discussed below. The award is not made posthumously, so Tversky who died in 1996 was ineligible. Their work and life-long friendship is the subject of a book by Michael Lewis, The Undoing Project.
2. Daniel Kahneman, Thinking, Fast and Slow (2015).
3. Kahneman called these System 1 processes, “heuristics.” A heuristic is a system or process to solve a problem “that employs a practical method, not guaranteed to be optimal, perfect, or rational, but instead sufficient for reaching an immediate goal.”
4. Richard Posner, Economic Analysis Of Law (2003).
5. Daniel Kahneman & Amos Tversky, Prospect Theory: An Analysis of Decision Under Risk. Econometrica, (March 1979), Vol. 47 at 263.
6. Amos Tversky & Daniel Kahneman, Rational Choice and the Framing of Decisions, The Journal of Business, Vol. 59, No, 4, Part 2: The Behavioral Foundations of Economic Theory, (October 1986), at 251.
7. Odean, Terrance, Are Investors Reluctant to Realize Their Losses? The Journal Of Finance, Oct. 1998, Vol. LIII, No. 5 at 1775, (investors sell winning positions too soon and hold losing positions too long, demonstrating cognitive bias of loss aversion); Shlomo Benartzi, Risk Aversion or Myopia? Choices in Repeated Gambles and Retirement Investments, Management Science, Mar.1999, Vol. 45, Issue 3 at 297, (retirement investors myopic in short term investment decisions with decided risk aversion).
8. Devin G. Pope, D. G. & Maurice E. Schweitz, Is Tiger Woods Loss Averse? Persistent Bias in the Face of Experience, Competition, and High Stakes, Am. Econ. Rev., (February 2011), Vol. 101 at 129. The study is particularly compelling because professional golf uses sophisticated computer programs and GPS to record every stroke, including the exact distance of each putt, as well as the slope and curve of the greens. Sports is a rich area of study of cognitive bias, because of the breadth and depth of statistical measurements. 3
9. Id. At 164.
10. See, e.g., Gregory Klass & Kathryn Zeiler, Against Endowment Theory: Experimental Economics and Legal Scholarship, 61 UCLA L.Rev. 2 (2013); Cass R. Sunstein, Christine Jolls, & Richard H. Thaler, Theories and Tropes: A Reply to Posner and Kelman, 50 Standford Law Review, 1593 (1998) There are political agendas apparent in the debate. For example, Against Endowment Theory, excoriates the behaviorists for the imposition of unwarranted public policy while members of the Obama Administration, tantamount to an oppression of liberty, including the formation of the CFPB. The behaviorists contend that the science requires that policy be adjusted to help people do what is best for them. Richard Thaler. & Cass Sunnstein, Libertarian Paternelism is not an OxyMoron. 70 University of Chic. L.Rev. 1159 (2003) University of Chicago Public Law & Legal Theory. (Working Paper No. 43) (2003), (“Equipped with an understanding of behavioral findings of bounded rationality and bounded self-control, libertarian paternalists should attempt to steer people’s choices in welfare-promoting directions without eliminating freedom of choice.”).
11. Gambler’s Fallacy is the tendency to assume that independent random events are influenced by previous random events.
12. The two rules are the Rule of Small Numbers and the Rule of Large Numbers. The Rule of Small Numbers states that a small sampling, e.g., twenty-six spins on a roulette wheel, does not adequately represent the possibility of the event occurring. It is a rule that should not be followed. The Rule of Large Numbers states that a sufficiently large sampling does represent the possibility of an event occurring. The results of a million spins of the wheel will show the true odds. This is the rule to apply.
13. Brian Knutson, et al., Neural Antecedents of the Endowment Effect Neuron, June 2010, Vol. 58, at 814 (brain activity related to exposure of subject to sale and purchase of goods consistent with endowment theory of reference dependent decision making, not rational actor theory); Talluri, et. al, Confirmation Bias Through Selective Overweighting of ChoiceConsistent Evidence. Current Biology, October 2018, Vol. 28, at 3128 (subject responses to stimuli show tendency to reaffirm initial choice consistent with confirmation bias).
14. Deborah Talmi, et al., Framing Effect Following Bilateral Amygdala Lesion. Neuropsycholgia, May 2010, Vol. 48, at 1823.
15. Hilke Plassmann, et al., Marketing Actions Can Modulate Neural Representations of Experienced Pleasantness. Proceedings of National Academy of Science, January 2008, Vol. 105, at 1050.
16. See, e.g., Chris Guthrie & Dan Orr. Anchoring, Information, Expertise, and Negotiation: New Insights from Meta-Analysis 21 Ohio State Journal on Dispute Resolution 597 (2006) (statistical aggregation of multiple studies on the anchoring effect shows high correlation between anchoring and outcome).
17. See, e.g., Andrew J. Wistrich, Chris Guthrie & Jeffrey J. Rachlinski, Inside the Judicial Mind, 86 Cornell L.Rev. 777 (2001) (judges equally susceptible as other decision makers to cognitive bias); Lee Epstein, Some Thoughts on the Study of Judicial Behavior, 57 Wm. & Mary L.Rev. 2017 (2016) (judicial decisions influenced by judges political views).
18. Gretchen B. Chapman & Brian H. Bornstein, The More You Ask for the More You Get: Anchoring in Personal Injury Verdicts, Applied Cognitive Pyschol., July 2000, Vol. 10, at 519. Oren Tasini is a Partner with Killgore Pearlman. He was one of the Founding Members of the National Association of Dealer Counsel.