Tag: Sunk Cost Effect

A Discussion on the Work of Daniel Kahneman

Edge.org asked the likes of Christopher Chabris, Nicholas Epley, Jason Zweig, William Poundstone, Cass Sunstein, Phil Rosenzweig, Richard Thaler & Sendhil Mullainathan, Nassim Nicholas Taleb, Steven Pinker, and Rory Sutherland among others: “How has Kahneman's work influenced your own? What step did it make possible?”

Kahneman's work is summarized in the international best-seller Thinking, Fast and Slow.

Here are some select excerpts that I found interesting.

Christopher Chabris (author of The Invisible Gorilla)

There's an overarching lesson I have learned from the work of Danny Kahneman, Amos Tversky, and their colleagues who collectively pioneered the modern study of judgment and decision-making: Don't trust your intuition.

Jennifer Jacquet

After what I see as years of hard work, experiments of admirable design, lucid writing, and quiet leadership, Kahneman, a man who spent the majority of his career in departments of psychology, earned the highest prize in economics. This was a reminder that some of the best insights into economic behavior could be (and had been) gleaned outside of the discipline

Jason Zweig (author of Your Money and Your Brain)

… nothing amazed me more about Danny than his ability to detonate what we had just done.

Anyone who has ever collaborated with him tells a version of this story: You go to sleep feeling that Danny and you had done important and incontestably good work that day. You wake up at a normal human hour, grab breakfast, and open your email. To your consternation, you see a string of emails from Danny, beginning around 2:30 a.m. The subject lines commence in worry, turn darker, and end around 5 a.m. expressing complete doubt about the previous day's work.

You send an email asking when he can talk; you assume Danny must be asleep after staying up all night trashing the chapter. Your cellphone rings a few seconds later. “I think I figured out the problem,” says Danny, sounding remarkably chipper. “What do you think of this approach instead?”

The next thing you know, he sends a version so utterly transformed that it is unrecognizable: It begins differently, it ends differently, it incorporates anecdotes and evidence you never would have thought of, it draws on research that you've never heard of. If the earlier version was close to gold, this one is hewn out of something like diamond: The raw materials have all changed, but the same ideas are somehow illuminated with a sharper shift of brilliance.

The first time this happened, I was thunderstruck. How did he do that? How could anybody do that? When I asked Danny how he could start again as if we had never written an earlier draft, he said the words I've never forgotten: “I have no sunk costs.”

William Poundstone (author of Are Your Smart Enough To Work At Google?)

As a writer of nonfiction I'm often in the position of trying to connect the dots—to draw grand conclusions from small samples. Do three events make a trend? Do three quoted sources justify a conclusion? Both are maxims of journalism. I try to keep in mind Kahneman and Tversky's Law of Small Numbers. It warns that small samples aren't nearly so informative, in our uncertain world, as intuition counsels.

Cass R. Sunstein (Author, Why Nudge?)

These ideas are hardly Kahneman’s most well-known, but they are full of implications, and we have only started to understand them.

1. The outrage heuristic. People’s judgments about punishment are a product of outrage, which operates as a shorthand for more complex inquiries that judges and lawyers often think relevant. When people decide about appropriate punishment, they tend to ask a simple question: How outrageous was the underlying conduct? It follows that people are intuitive retributivists, and also that utilitarian thinking will often seem uncongenial and even outrageous.

2. Scaling without a modulus. Remarkably, it turns out that people often agree on how outrageous certain misconduct is (on a scale of 1 to 8), but also remarkably, their monetary judgments are all over the map. The reason is that people do not have a good sense of how to translate their judgments of outrage onto the monetary scale. As Kahneman shows, some work in psychophysics explains the problem: People are asked to “scale without a modulus,” and that is an exceedingly challenging task. The result is uncertainty and unpredictability. These claims have implications for numerous questions in law and policy, including the award of damages for pain and suffering, administrative penalties, and criminal sentences.

3. Rhetorical asymmetry. In our work on jury awards, we found that deliberating juries typically produce monetary awards against corporate defendants that are higher, and indeed much higher, than the median award of the individual jurors before deliberation began. Kahneman’s hypothesis is that in at least a certain category of cases, those who argue for higher awards have a rhetoric advantage over those who argue for lower awards, leading to a rhetorical asymmetry. The basic idea is that in light of social norms, one side, in certain debates, has an inherent advantage – and group judgments will shift accordingly. A similar rhetorical asymmetry can be found in groups of many kinds, in both private and public sectors, and it helps to explain why groups move.

4. Predictably incoherent judgments. We found that when people make moral or legal judgments in isolation, they produce a pattern of outcomes that they would themselves reject, if only they could see that pattern as a whole. A major reason is that human thinking is category-bound. When people see a case in isolation, they spontaneously compare it to other cases that are mainly drawn from the same category of harms. When people are required to compare cases that involve different kinds of harms, judgments that appear sensible when the problems are considered separately often appear incoherent and arbitrary in the broader context. In my view, Kahneman’s idea of predictable coherence has yet to be adequately appreciated; it bears on both fiscal policy and on regulation.

Phil Rosenzweig

For years, there were (as the old saying has it) two kinds of people: those relatively few of us who were aware of the work of Danny Kahneman and Amos Tversky, and the much more numerous who were not. Happily, the balance is now shifting, and more of the general public has been able to hear directly a voice that is in equal measures wise and modest.

Sendhil Mullainathan (Author of Scarcity: Why Having Too Little Means So Much)

… Kahneman and Tversky's early work opened this door exactly because it was not what most people think it was. Many think of this work as an attack on rationality (often defined in some narrow technical sense). That misconception still exists among many, and it misses the entire point of their exercise. Attacks on rationality had been around well before Kahneman and Tversky—many people recognized that the simplifying assumptions of economics were grossly over-simplifying. Of course humans do not have infinite cognitive abilities. We are also not as strong as gorillas, as fast as cheetahs, and cannot swim like sea lions. But we do not therefore say that there is something wrong with humans. That we have limited cognitive abilities is both true and no more helpful to doing good social science that to acknowledge our weakness as swimmers. Pointing it out did it open any new doors.

Kahneman and Tversky's work did not just attack rationality, it offered a constructive alternative: a better description of how humans think. People, they argued, often use simple rules of thumb to make judgments, which incidentally is a pretty smart thing to do. But this is not the insight that left us one step from doing behavioral economics. The breakthrough idea was that these rules of thumb could be catalogued. And once understood they can be used to predict where people will make systematic errors. Those two words are what made behavioral economics possible.

Nassim Taleb (Author of Antifragile)

Here is an insight Danny K. triggered and changed the course of my work. I figured out a nontrivial problem in randomness and its underestimation a decade ago while reading the following sentence in a paper by Kahneman and Miller of 1986:

A spectator at a weight lifting event, for example, will find it easier to imagine the same athlete lifting a different weight than to keep the achievement constant and vary the athlete's physique.

This idea of varying one side, not the other also applies to mental simulations of future (random) events, when people engage in projections of different counterfactuals. Authors and managers have a tendency to take one variable for fixed, sort-of a numeraire, and perturbate the other, as a default in mental simulations. One side is going to be random, not the other.

It hit me that the mathematical consequence is vastly more severe than it appears. Kahneman and colleagues focused on the bias that variable of choice is not random. But the paper set off in my mind the following realization: now what if we were to go one step beyond and perturbate both? The response would be nonlinear. I had never considered the effect of such nonlinearity earlier nor seen it explicitly made in the literature on risk and counterfactuals. And you never encounter one single random variable in real life; there are many things moving together.

Increasing the number of random variables compounds the number of counterfactuals and causes more extremes—particularly in fat-tailed environments (i.e., Extremistan): imagine perturbating by producing a lot of scenarios and, in one of the scenarios, increasing the weights of the barbell and decreasing the bodyweight of the weightlifter. This compounding would produce an extreme event of sorts. Extreme, or tail events (Black Swans) are therefore more likely to be produced when both variables are random, that is real life. Simple.

Now, in the real world we never face one variable without something else with it. In academic experiments, we do. This sets the serious difference between laboratory (or the casino's “ludic” setup), and the difference between academia and real life. And such difference is, sort of, tractable.

… Say you are the manager of a fertilizer plant. You try to issue various projections of the sales of your product—like the weights in the weightlifter's story. But you also need to keep in mind that there is a second variable to perturbate: what happens to the competition—you do not want them to be lucky, invent better products, or cheaper technologies. So not only you need to predict your fate (with errors) but also that of the competition (also with errors). And the variance from these errors add arithmetically when one focuses on differences.

Rory Sutherland

When I met Danny in London in 2009 he diffidently said that the only hope he had for his work was that “it might lead to a better kind of gossip”—where people discuss each other's motivations and behaviour in slightly more intelligent terms. To someone from an industry where a new flavour-variant of toothpaste is presented as being an earth-changing event, this seemed an incredibly modest aspiration for such important work.

However, if this was his aim, he has surely succeeded. When I meet people, I now use what I call “the Kahneman heuristic”. You simply ask people “Have you read Danny Kahneman's book?” If the answer is yes, you know (p>0.95) that the conversation will be more interesting, wide-ranging and open-minded than otherwise.

And it then occurred to me that his aim—for better conversations—was perhaps not modest at all. Multiplied a millionfold it may very important indeed. In the social sciences, I think it is fair to say, the good ideas are not always influential and the influential ideas are not always good. Kahneman's work is now both good and influential.

The Art of Thinking Clearly

(Update: While the book will likely make you smarter, there is some question as to where some of the ideas came from.)

The Art of Thinking Clearly

Rolf Dobelli's book, The Art of Thinking Clearly, is a compendium of systematic errors in decision making. While the list of fallacies is not complete, it's a great launching pad into the best of what others have already figured out.

To avoid frivolous gambles with the wealth I had accumulated over the course of my literary career, I began to put together a list of … systematic cognitive errors, complete with notes and personal anecdotes — with no intention of ever publishing them. The list was originally designed to be used by me alone. Some of these thinking errors have been known for centuries; others have been discovered in the last few years. Some came with two or three names attached to them. … Soon I realized that such a compilation of pitfalls was not only useful for making investing decisions but also for business and personal matters. Once I had prepared the list, I felt calmer and more levelheaded. I began to recognize my own errors sooner and was able to change course before any lasting damage was done. And, for the first time in my life, I was able to recognize when others might be in the thrall of these very same systematic errors. Armed with my list, I could now resist their pull — and perhaps even gain an upper hand in my dealings.

Dobelli's goal is to learn to recognize and evade the biggest errors in thinking. In so doing, he believes we might “experience a leap in prosperity. We need no extra cunning, no new ideas, no unnecessary gadgets, no frantic hyperactivity—all we need is less irrationality.”

Let's take a look at some of the content.

Guarding Against Survivorship Bias

People systematically overestimate their chances of success. Guard against it by frequently visiting the graves of once-promising projects, investments, and careers. It is a sad walk but one that should clear your mind.

Pattern Recognition

When it comes to pattern recognition, we are oversensitive. Regain your scepticism. If you think you have discovered a pattern, first consider it pure chance. If it seems too good to be true, find a mathematician and have the data tested statistically.

Fighting Against Confirmation Bias

[T]ry writing down your beliefs — whether in terms of worldview, investments, marriage, health care, diet, career strategies — and set out to find disconfirming evidence. Axing beliefs that feel like old friends is hard work but imperative.

Dating Advice and Contrast

If you are seeking a partner, never go out in the company of your supermodel friends. People will find you less attractive than you really are. Go alone or, better yet, take two ugly friends.

Think Different

Fend it off (availability bias) by spending time with people who think different than you do—people whose experiences and expertise are different from yours.

Guard Against Chauffeur Knowledge

Be on the lookout for chauffeur knowledge. Do not confuse the company spokesperson, the ringmaster, the newscaster, the schmoozer, the verbiage vendor, or the cliche generator with those who possess true knowledge. How do you recognize the difference? There is a clear indicator: True experts recognize the limits of what they know and what they do not know.

The Swimmer's Body Illusion

Professional swimmers don’t have perfect bodies because they train extensively. Rather, they are good swimmers because of their physiques. How their bodies are designed is a factor for selection and not the result of their activities. … Whenever we confuse selection factors with results, we fall prey to what Taleb calls the swimmer’s body illusion. Without this illusion, half of advertising campaigns would not work. But this bias has to do with more than just the pursuit of chiseled cheekbones and chests. For example, Harvard has the reputation of being a top university. Many highly successful people have studied there. Does this mean that Harvard is a good school? We don’t know. Perhaps the school is terrible, and it simply recruits the brightest students around.

Peer Pressure

A simple experiment, carried out in the 1950s by legendary psychologist Solomon Asch, shows how peer pressure can warp common sense. A subject is shown a line drawn on paper, and next to it three lines—numbered 1, 2, and 3—one shorter, one longer, and one the same length as the original one. He or she must indicate which of the three lines corresponds to the original one. If the person is alone in the room, he gives correct answers because the task is really quite simple. Now five other people enter the room; they are all actors, which the subject does not know. One after another, they give wrong answers, saying “number 1,” although it’s very clear that number 3 is the correct answer. Then it is the subject’s turn again. In one-third of cases, he will answer incorrectly to match the other people’s responses

Rational Decision Making and The Sunk Cost Fallacy

The sunk cost fallacy is most dangerous when we have invested a lot of time, money, energy, or love in something. This investment becomes a reason to carry on, even if we are dealing with a lost cause. The more we invest, the greater the sunk costs are, and the greater the urge to continue becomes. … Rational decision making requires you to forget about the costs incurred to date. No matter how much you have already invested, only your assessment of the future costs and benefits counts.

Avoid Negative Black Swans

But even if you feel compelled to continue as such, avoid surroundings where negative Black Swans thrive. This means: Stay out of debt, invest your savings as conservatively as possible, and get used to a modest standard of living—no matter whether your big breakthrough comes or not

Disconfirming Evidence

Munger Destroy ideas

The confirmation bias is alive and well in the business world. One example: An executive team decides on a new strategy. The team enthusiastically celebrates any sign that the strategy is a success. Everywhere the executives look, they see plenty of confirming evidence, while indications to the contrary remain unseen or are quickly dismissed as “exceptions” or “special cases.” They have become blind to disconfirming evidence.

Still curious? Read The Art of Thinking Clearly.

The Mind of a Con Man

Overnight, Diederik Stapel went from respected professor to the biggest con man in academic science. For more than a decade his biggest experiment was deceiving others. In the end, Stapel had committed fraud in at least 55 papers.

Stapel did not deny that his deceit was driven by ambition. But it was more complicated than that, he told me. He insisted that he loved social psychology but had been frustrated by the messiness of experimental data, which rarely led to clear conclusions. His lifelong obsession with elegance and order, he said, led him to concoct sexy results that journals found attractive. “It was a quest for aesthetics, for beauty — instead of the truth,” he said. He described his behavior as an addiction that drove him to carry out acts of increasingly daring fraud, like a junkie seeking a bigger and better high.

Academic science is becoming a business too. “There are scarce resources, you need grants, you need money, there is competition,” Stapel said. “Normal people go to the edge to get that money. Science is of course about discovery, about digging to discover the truth. But it is also communication, persuasion, marketing. I am a salesman. I am on the road. People are on the road with their talk. With the same talk. It’s like a circus.”

Sunk Costs

…The experiment — and others like it — didn’t give Stapel the desired results, he said. He had the choice of abandoning the work or redoing the experiment. But he had already spent a lot of time on the research and was convinced his hypothesis was valid. “I said — you know what, I am going to create the data set,” he told me.

How he did it

The key to why Stapel got away with his fabrications for so long lies in his keen understanding of the sociology of his field. “I didn’t do strange stuff, I never said let’s do an experiment to show that the earth is flat,” he said. “I always checked — this may be by a cunning manipulative mind — that the experiment was reasonable, that it followed from the research that had come before, that it was just this extra step that everybody was waiting for.” He always read the research literature extensively to generate his hypotheses. “So that it was believable and could be argued that this was the only logical thing you would find,” he said. “Everybody wants you to be novel and creative, but you also need to be truthful and likely. You need to be able to say that this is completely new and exciting, but it’s very likely given what we know so far.”

A Simple Checklist to Improve Decisions

We owe thanks to the publishing industry. Their ability to take a concept and fill an entire category with a shotgun approach is the reason that more people are talking about biases.

Unfortunately, talk alone will not eliminate them but it is possible to take steps to counteract them. Reducing biases can make a huge difference in the quality of any decision and it is easier than you think.

In a recent article for Harvard Business Review, Daniel Kahneman (and others) describe a simple way to detect bias and minimize its effects in the most common type of decisions people make: determining whether to accept, reject, or pass on a recommendation.

The Munger two-step process for making decisions is a more complete framework, but Kahneman's approach is a good way to help reduce biases in our decision-making.

If you're short on time here is a simple checklist that will get you started on the path towards improving your decisions:

Preliminary Questions: Ask yourself

1. Check for Self-interested Biases

  • Is there any reason to suspect the team making the recommendation of errors motivated by self-interest?
  • Review the proposal with extra care, especially for overoptimism.

2. Check for the Affect Heuristic

  • Has the team fallen in love with its proposal?
  • Rigorously apply all the quality controls on the checklist.

3. Check for Groupthink

  • Were there dissenting opinions within the team?
  • Were they explored adequately?
  • Solicit dissenting views, discreetly if necessary.
  • Challenge Questions: Ask the recommenders

4. Check for Saliency Bias

  • Could the diagnosis be overly influenced by an analogy to a memorable success?
  • Ask for more analogies, and rigorously analyze their similarity to the current situation.

5. Check for Confirmation Bias

  • Are credible alternatives included along with the recommendation?
  • Request additional options.

6. Check for Availability Bias

  • If you had to make this decision again in a year’s time, what information would you want, and can you get more of it now?
  • Use checklists of the data needed for each kind of decision.

7. Check for Anchoring Bias

  • Do you know where the numbers came from? Can there be
  • …unsubstantiated numbers?
  • …extrapolation from history?
  • …a motivation to use a certain anchor?
  • Reanchor with figures generated by other models or benchmarks, and request new analysis.

8. Check for Halo Effect

  • Is the team assuming that a person, organization, or approach that is successful in one area will be just as successful in another?
  • Eliminate false inferences, and ask the team to seek additional comparable examples.

9. Check for Sunk-Cost Fallacy, Endowment Effect

  • Are the recommenders overly attached to a history of past decisions?
  • Consider the issue as if you were a new CEO.
  • Evaluation Questions: Ask about the proposal

10. Check for Overconfidence, Planning Fallacy, Optimistic Biases, Competitor Neglect

  • Is the base case overly optimistic?
  • Have the team build a case taking an outside view; use war games.

11. Check for Disaster Neglect

  • Is the worst case bad enough?
  • Have the team conduct a premortem: Imagine that the worst has happened, and develop a story about the causes.

12. Check for Loss Aversion

  • Is the recommending team overly cautious?
  • Realign incentives to share responsibility for the risk or to remove risk.

If you're looking to dramatically improve your decision making here is a great list of books to get started:

Nudge: Improving Decisions About Health, Wealth, and Happiness by Richard H. Thaler and Cass R. Sunstein

Think Twice: Harnessing the Power of Counterintuition by Michael J. Mauboussin

Think Again: Why Good Leaders Make Bad Decisions and How to Keep It from Happening to You by Sydney Finkelstein, Jo Whitehead, and Andrew Campbell

Predictably Irrational: The Hidden Forces That Shape Our Decisions by Dan Ariely

Thinking, Fast and Slow by Daniel Kahneman

Judgment and Managerial Decision Making by Max Bazerman