The Undoing Project

Picture this: you're a basketball executive with millions of dollars on the line, trying to decide which college player will become the next NBA superstar. You watch game footage, conduct interviews, and analyze statistics. Yet despite all this data, you consistently make costly mistakes. Jeremy Lin, who would later electrify Madison Square Garden, goes undrafted because scouts can't see past their preconceptions about Asian athletes. Meanwhile, players who look the part but lack the skills receive lucrative contracts based on little more than their resemblance to previous stars.

This scenario isn't hypothetical—it's the reality that drove Houston Rockets general manager Daryl Morey to revolutionize basketball recruiting using insights from behavioral psychology. His story illustrates a profound truth about human nature: our minds, despite their remarkable capabilities, are systematically prone to predictable errors when making judgments under uncertainty. Whether we're diagnosing patients, evaluating investments, or simply trying to understand the people around us, we rely on mental shortcuts that can lead us astray in surprisingly consistent ways.

This exploration reveals how two Israeli psychologists uncovered the hidden patterns in human thinking that affect everything from medical diagnoses to military strategy. You'll discover why our intuitions about probability and risk are often wrong, how our memories distort our judgment in predictable ways, and what happens when we mistake the vivid and memorable for the important and likely. Most importantly, you'll learn to recognize these mental traps in your own thinking and develop strategies to make better decisions when the stakes matter most.

In 2007, the Houston Rockets faced a dilemma that would expose the fundamental flaws in human judgment. Their scouts had found a photograph of Marc Gasol, a seven-foot-one Spanish center, shirtless and looking decidedly unimpressive. His pudgy physique and baby face earned him a cruel nickname among the Rockets staff: "Man Boobs." The ridicule was so pervasive that it drowned out what Daryl Morey's statistical model was screaming: this player would be exceptional.

Morey, the Rockets' analytically-minded general manager, watched helplessly as his staff's visceral reaction to Gasol's appearance overrode the data. The model loved everything about Gasol's performance statistics, his age-adjusted productivity, and his basketball IQ. But the human brain, it seemed, couldn't get past the image of those jiggly pecs. The Memphis Grizzlies selected Gasol with the 48th pick of the draft—a position where the odds of finding even a useful bench player were less than one in a hundred. Gasol would go on to become a two-time All-Star and one of the best draft picks of the decade.

This painful lesson taught Morey something profound about human nature: we are visual creatures whose judgments can be hijacked by a single memorable image. The scouts weren't stupid or lazy—they were human. Their minds had been captured by what psychologists call the "representativeness heuristic," the tendency to judge something based on how closely it resembles our mental prototype. Gasol didn't look like their idea of a dominant NBA center, so they couldn't see his potential, despite overwhelming statistical evidence.

The Marc Gasol incident led Morey to implement a radical rule: he banned nicknames in the draft room. He realized that the labels we attach to people and situations don't just describe them—they actively shape how we perceive them. When you call someone "Man Boobs," you're not just being cruel; you're programming everyone who hears that nickname to focus on physical appearance rather than basketball ability. The human mind, Morey learned, is constantly looking for shortcuts to understanding, and these shortcuts can blind us to reality.

This insight extends far beyond basketball. In any situation where you're evaluating people or making predictions, ask yourself: what mental image is driving my judgment? Are you focusing on the most relevant information, or are you being swayed by vivid but ultimately irrelevant details? The key is to recognize when your brain is taking shortcuts and to deliberately slow down your thinking process.

Danny Kahneman was seven years old when a German SS officer picked him up on the streets of occupied Paris. The boy was wearing his yellow Star of David inside his sweater, terrified it would be discovered. Instead, the soldier hugged him, showed him a photograph of his own son, and gave him money. This moment crystallized something that would shape Kahneman's entire career: people are endlessly complicated and interesting, defying our expectations in ways both wonderful and terrible.

Growing up as a Jewish child in Nazi-occupied France, Kahneman learned that survival depended on understanding human behavior under extreme uncertainty. He watched his teacher and the owners of the local bar where his family hid—people who surely knew they were sheltering Jews but gave no sign of recognition. He observed a young French Nazi who courted his sister, never realizing he had fallen in love with someone he was supposed to hate. These experiences taught him that human judgment operates in mysterious ways, often contradicting what logic would suggest.

Years later, as a young psychologist in the Israeli army, Kahneman was tasked with improving the military's officer selection process. The existing system relied on elaborate group exercises where candidates had to work together to solve problems, like moving themselves over a wall using only a long log. The officers conducting these assessments felt supremely confident in their ability to identify future leaders. They could spot who was stubborn, who was creative, who would crack under pressure.

There was just one problem: their predictions were completely worthless. When Kahneman tracked the candidates' actual performance in officer training, he found no correlation between the assessors' confident judgments and real-world outcomes. The officers were experiencing what he would later recognize as a fundamental feature of human psychology: we can feel absolutely certain about judgments that are essentially random. Like people looking at optical illusions who insist they see one line as longer than another even after measuring proves them identical, the assessors couldn't shake their confidence even when confronted with evidence of their failure.

This experience planted the seeds of a revolutionary insight: human intuition, even expert intuition, is far less reliable than we believe. The confidence we feel in our judgments often has little relationship to their accuracy. Kahneman developed a simple algorithm that outperformed the human assessors, not because it was sophisticated, but because it was consistent. It didn't have good days and bad days, wasn't influenced by irrelevant factors, and didn't mistake confidence for competence.

The confrontation happened in a Jerusalem seminar room in 1969, and it would change how we understand the human mind. Amos Tversky, the golden boy of Israeli psychology—a war hero turned mathematical psychologist—had just presented research suggesting that people were "conservative Bayesians," meaning they updated their beliefs in response to new information much the way statistical theory predicted, just not quite enough. Danny Kahneman, the moody and self-doubting professor, listened with growing incredulity before launching into what colleagues called "pushing him into the wall"—the aggressive intellectual combat that was standard practice at Hebrew University.

Kahneman's attack was devastating in its simplicity: the research Tversky described was "incredibly stupid." If people were even remotely good at statistical reasoning, Kahneman argued, why were his own statistics students so hopeless at grasping basic concepts like the importance of sample size? Why did he himself make elementary statistical errors in his own research? The idea that humans were intuitive statisticians, even conservative ones, struck him as absurd. People weren't bad statisticians—they weren't statisticians at all.

What happened next was extraordinary. Instead of defending his position, Tversky found himself genuinely shaken by Kahneman's critique. For perhaps the first time in his adult life, this supremely confident man experienced serious doubt about ideas he had accepted without question. The two began meeting regularly, and their conversations became legendary among their colleagues—not for their intensity, though they often shouted at each other, but for the constant sound of laughter emanating from behind closed doors.

Their collaboration began with a simple but radical experiment. They created a test for professional psychologists and statisticians, asking them to solve problems that had objectively correct answers. The results were shocking: even experts trained in statistics made systematic errors when reasoning about probability. They would see a few red poker chips drawn from a bag and leap to conclusions about the bag's contents with confidence that was completely unjustified by the limited evidence.

This wasn't just academic nitpicking—it revealed something fundamental about human nature. The same mental processes that allowed people to make quick sense of complex situations also led them systematically astray. People believed in what Kahneman and Tversky called "the law of small numbers"—the mistaken belief that small samples of data would closely resemble the larger populations from which they were drawn. A few data points felt like enough to draw sweeping conclusions, whether you were a psychologist evaluating a new theory or a parent deciding whether your child was gifted based on a single test score.

Dr. Don Redelmeier was examining a young woman who had been rushed to Toronto's Sunnybrook Hospital after a devastating car crash. She had broken bones everywhere—ankles, feet, hips, face—but what worried the medical team was her wildly irregular heartbeat. When they learned she had a history of thyroid problems, the diagnosis seemed obvious: hyperthyroidism was a classic cause of irregular heart rhythms. The staff was ready to treat her thyroid condition immediately.

But Redelmeier, who had been profoundly influenced by reading Kahneman and Tversky's work as a teenager, forced everyone to pause. Something bothered him about the neat story they had constructed. Yes, hyperthyroidism could cause irregular heartbeats, but it was actually a relatively rare cause. The medical team had fallen victim to what the psychologists called the "representativeness heuristic"—they had matched the patient's symptoms to a familiar pattern without considering how common that pattern actually was.

Redelmeier insisted they search for more statistically likely causes of the woman's heart problems. That's when they discovered her collapsed lung, which hadn't shown up clearly on the initial X-ray. Unlike her thyroid, the collapsed lung could kill her. When they treated the lung, her heartbeat returned to normal. The next day, her thyroid tests came back completely normal—her thyroid had never been the problem at all.

This case illustrates how Kahneman and Tversky's insights spread far beyond psychology laboratories into life-and-death situations. Their research had identified a fundamental flaw in human reasoning: when we encounter a problem, our minds immediately search for familiar patterns and explanations. The first story that makes sense feels compelling, and we stop looking for alternatives. In medicine, this can be fatal. The dramatic, memorable case—the alcoholic who seems drunk but actually has a brain hemorrhage—gets missed because doctors see what they expect to see.

The power of their ideas lay not just in identifying these mental traps, but in showing how pervasive they were. Availability bias meant that doctors' diagnoses were influenced by whatever cases they had seen recently. Anchoring bias meant that the first piece of information they received disproportionately influenced their thinking. Confirmation bias meant they looked for evidence that supported their initial hunches rather than evidence that might prove them wrong.

The influence of Danny and Amos's work extends far beyond academic psychology into the practical realm of policy and decision-making. Their insights have quietly revolutionized everything from medical practice to government regulation, often in ways that save lives and improve outcomes without people even realizing it. The transformation began when practitioners in various fields recognized that understanding human cognitive biases could lead to better systems and procedures.

In medicine, their work has helped reduce diagnostic errors that kill thousands of patients annually. Emergency room physicians now use protocols that force doctors to consider alternative diagnoses rather than anchoring on the first explanation that comes to mind. The business world has embraced their insights about loss aversion and framing effects. Companies now understand that customers will fight harder to avoid losing existing benefits than to gain new ones, leading to more effective marketing strategies and product designs.

Government policy has been perhaps most transformed by their work. Cass Sunstein, who served in the Obama administration, used their principles to redesign everything from fuel economy labels to organ donation systems. By understanding how people actually make decisions rather than how economists assumed they made decisions, policymakers could design "choice architecture" that nudged people toward better outcomes without restricting their freedom to choose.

The deeper legacy of their work lies in its fundamental challenge to human overconfidence. In a world where experts routinely make predictions with unwarranted certainty, where leaders base crucial decisions on flawed intuitions, and where individuals consistently overestimate their own judgment, their research offers a dose of intellectual humility. They showed us that the human mind, for all its remarkable capabilities, is not the rational calculating machine we often assume it to be.

This recognition doesn't diminish human intelligence; it simply helps us understand its limits and work within them more effectively. The most profound insight is that being aware of these biases isn't enough—you must build systems and habits that actively counteract them. When making important decisions, especially about people or uncertain outcomes, force yourself to consider base rates and alternative explanations before settling on the story that feels most satisfying.

The most profound insight from this exploration of human judgment can be captured in a single truth: the confidence we feel in our decisions is often inversely related to their accuracy, and the mental shortcuts that make us efficient thinkers also make us predictably wrong.

Recognize that your first impression, no matter how compelling, is just one possibility among many—actively seek out information that contradicts your initial judgment. When making important decisions, especially about people or uncertain outcomes, force yourself to consider base rates and alternative explanations before settling on the story that feels most satisfying. Finally, build systems that slow down your thinking in high-stakes situations, because the same mental processes that help you navigate daily life can lead you astray when the consequences matter most. The goal isn't to eliminate these mental shortcuts—that's impossible—but to recognize when they're likely to mislead you and to have strategies ready to counteract their influence.