Book summary: Predictably Irrational

A future work colleague recently recommended a book to me that might be useful as a consultant working with data. It's called Predictably Irrational, by Dan Ariely, and it contains a catalogue and commentary on some of the cognitive biases that cause humans to make irrational decisions, particularly in economic settings. He describes experiments (both virtual and real) that demonstrate the effects, argues for their pervasiveness in our lives, and proposes ways to mitigate them.

I wanted to put up this post as a summary of the book and a record of some of my reactions to it, which will hopefully force me to read actively rather than skimming. Hopefully you'll find it useful too.

Summaries of chapters are on the left in black,

my reactions are on the right in purple.

Introduction

Economics is based on a model that says humans make rational decisions according to their preferences, and with complete information. In contrast, behavioral economics considers that people sometimes make irrational decisions. These decisions are not random, however, but can be tested experimentally and predicted. Some of these errors may be mitigated by learning about the forces that shape our irrational choices.

I was just writing about how cognitive bias takes a back seat in data science, but it's driving the car in this book. Having read Dan Kahneman's Thinking, Fast and Slow and spent some time on lesswrong.com, I'm familiar with the concept. It sounds like this book is principally concerned with cognitive bias as it applies to economic decisions, which I assume will be useful in my job. I don't know what Ariely's motivation is yet - is he going to teach us how to use behavioral economics to sell more hamburgers, or to make sure we buy the best hamburger? 

1. The Truth about Relativity:  Why Everything is Relative -- Even When It Shouldn't Be

It's hard to assess the value of something unless it's compared to other similar things. Given three options (A, B, C) with B and C being similar but B superior to C, people will tend to choose option B regardless of the quality of A. This is called the decoy effect. Ariely suggests that it's partly responsible for the creep of materialism, in that when we buy a car we tend to compare it to slightly better cars. He also suggests that to limit the decoy effect's effect on us, we can try to limit the options we have access to. Experiments are presented that show that the effect is real and strong.

I hadn't really thought about how pervasive this effect is in our lives. Ariely points out that it's responsible for the "wingman effect," where you can bring a less attractive friend to a bar when you're looking for a date. You not only look better compared to your friend, but to the rest of the bar as well. It's also used extensively in advertising to make us "creep" up to more expensive items or packages. 

Ariely's writing is very conversational and a bit hyperbolic. The analysis is qualitative, and it's not exactly clear how strong this effect is, and whether the results are statistically significant. I'm interested in how the decoy effect competes or cooperates with updating preferences based on prior information. We don't assign value to a set of speakers without hearing similar speakers in part because we haven't heard any of the speakers yet.

I'm somewhat surprised by the suggestion that we intentionally and artificially limit our access to options in order to curb this effect. This is not the usual approach to cognitive bias, but it's consistent with the view that ignorance is bliss.

2. The Fallacy of Supply and Demand: Why the Price of Pearls -- and Everything Else -- Is Up in the Air

The law of supply and demand is supposed to set the price of goods and services, but this is based on a rational economic model. In reality, the price of things is pretty arbitrary. Ariely introduces the concept of arbitrary coherence, where prices and behaviors may be based on previous prices or behaviors, but the original ones were set arbitrarily. He uses the well-known bias of anchoring, in which our beliefs about numerical quantities are influenced by numbers we've seen or heard recently, even if they have no logical connection. He talks about some experiments he's done that show that not only does anchoring affect the price we're willing to pay for something, but it can even make the difference between being willing to pay for something or demanding to be paid for it, if the thing in question has ambiguous value.

He also shows that the influence of anchors is long-lived: you can't replace them with new anchors easily. Some theories as to why we are willing to pay so much for Starbucks coffee are put forward (we don't compare to similar products because of the difference in atmosphere).

Ariely also talks about self herding, in which we think about how often we've done something before, and take that as independent evidence that that thing is good to do. This shores up the theory that our habits may be quite arbitrary at their roots. His advice is to become aware of these vulnerabilities and question our habits. Consider the rewards and costs of each decision. Mathematically speaking, this theory suggests that supply and demand are not independent, but coupled.

We tend to rationalize our choices after the fact, and Ariely argues that this might not be a bad thing as long as it makes us happy.

Arbitrary coherence is an interesting idea. It reminds me of filamentation in nonlinear optics, or actually just anything in nonlinear optics. Or just anything nonlinear with a random seed. It also a pretty bold claim, and I've never heard anyone else make it. Granted, I don't run in sociological circles. I'll have to run it by some friends. Self-herding as a mechanism is sexy.

This chapter leaves me wanting to see some equations. What happens formally when you assume various kinds of coupling terms between supply and demand? Surely this is solved. I assume it results in prices that are either saturating exponentials, oscillatory functions, or hyperbolic trig functions. This seems like a simple opportunity to extend conventional economics into the field of behavioral economics.

Finally, I feel strongly that rationalization is bad. If you have arbitrary preferences for one car over another one, they can be taken into account formally using decision theory. Even with the craziest preferences in the world, you can still make consistent decisions as long as you don't violate a few axioms. As soon as you allow ad hoc rationalization, decision theory goes out the window. That's a sacrifice I'm not willing to make.

3. The Cost of Zero Cost: Why We Often Pay Too Much When We Pay Nothing

People respond to a cost of $0.00 differently than to other similar costs. For example, consider the following two situations.

People make decisions about these choices as if the relative value of A over B were much greater in Choice 1 than Choice 2, even though the difference in cost is identical, and $0.01 is certainly below the wealth-depletion regime. He gives an example of Amazon, where the inclusion of free shipping for orders above a threshold entices people to spend more than the cost of shipping, and points out that this does not work if they reduce the cost of shipping to a few cents.

He also mentions a thought experiment where you are given a choice between two gift certificates (again, for Amazon). The first is a free $10 gift card, and the second is a $20 gift card that requires you to first pay $7. He speculates that people would be more likely to choose the first.

Seems reasonable. I take issue with the Amazon example though. One one hand, suppose we replace "Amazon" with "turpentine factory." I don't value turpentine, so the decision to take the free option is quite rational. Now suppose we replace "Amazon" with "cold, hard cash." Everyone would obviously choose the second option because everyone values cash as much as cash. So the question seems to depend on how much we value the commodity. I don't see why that's irrational. 

4. The Cost of Social Norms: Why We are Happy to Do Things, But Not When We are Paid to Do Them.

There are market norms, and there are social norms, and it seems that people act as if there is a sharp division between the two. For example, We don't offer payment for a family Thanksgiving dinner, but we might bring an expensive bottle of wine. Essentially, if we apply social norms to situations we tend to undervalue our own time and effort. 

Companies try to sell us things by trying to forge a connection to us. Open source software is another example, where very skilled people spend a lot of their time to work, but would not do so for a small amount of money. Ariely hypothesizes that this effect is responsible for police being willing to risk their lives for relatively small amounts of money. 

Now I feel like we're getting somewhere. This is a familiar concept of course, but this chapter puts it in concrete terms. It reminds me of the subscription program on Twitch.tv, where I subscribe to people for essentially no personal benefit. It puts a name to the awkwardness I feel offering money to friends when they babysit for me. 

It also calls to mind the office culture in my soon-to-be office. They have a family-like atmosphere,  unlimited paid time off, and even award a bonus for taking seven consecutive days off during the year. This may be effective at generating more committed workers. 

I wonder what kind of norms are at play in academic research science. It is certainly true that the amount of money I made was far below what I could have made in the private sector. I also reviewed papers for free even though I paid publication fees when I had papers accepted at journals. Was I motivated by social norms like the quest for scientific truth, the solidarity between academic scientists in a similar situation? Or was I motivated more by the eventual promise of tenure, which is a market-like reward?

5. The Power of a Free Cookie: How Free Can Make Us Less Selfish.

If something is free instead of cheap, we tend to regulate it with social norms instead of supply and demand. So if you offer a tray of free cookies to a group of people sequentially, they will tend to take a small number of cookies. But if you sell those same cookies for $0.05 each to those same people, people tend to buy many of them, even though five cents is basically free.

Ariely suggests that this phenomenon will keep programs like cap-and-trade from working. By putting a price on pollution instead of making it free, companies may feel free to pollute more, since they've paid for it, whereas if it were free they might be bound by social norms.

This seems reasonable, and I can think of anecdotal evidence to support it. Ariely's experiments also show it to be true. I have reservations about his statements on cap-and-trade, since I think the total amount of credits is kept constant. The companies couldn't pollute more in total than before. I also don't think companies are bound strongly by social norms in the first place, but that's speculation on my part.

Frankly, I feel pretty bad when I buy all of something cheap at a grocery store, similar to how people apparently treat free things. Not sure how sharp this division is.

6. The Influence of Arousal: Why Hot is Much Hotter than We Realize.

Ariely describes some fairly interesting experiments that demonstrate two things. (1) We make different decisions when sexually aroused, and (2) we can't accurately predict how different those decisions will be ahead of time. The first of these is pretty obvious, and the second is less obvious and a little worrying.

Specifically, test subjects were more likely to agree to propositions like "I would not use a condom if I thought my partner would chance his/her mind while I went to get it" while aroused than while not aroused. In light of this, Ariely suggests that asking teens to make good decisions while heated up is basically useless. If we want to prevent pregnancy and STD transmission in teens, we either need to keep them from being aroused, or we need to make things like condoms so universally available that teens never really have to think about whether to use them or not.

In this chapter Ariely makes explicit what he's only implied before: in his model of human thought, we are like Dr Jekyll and Mr Hyde. The latter makes decisions that the former would not agree with or necessarily predict correctly. He also brings up id, ego, and superego more than once, and paraphrases Sigmund Freud. He goes so far as to say that "We may, in fact, be an agglomeration of multiple selves." Not being a psychologist, I'm not sure what to make of this model. It was my understanding that Freud's theories were no longer thought to be an accurate description of psychological phenomena, but maybe I'm wrong. In any case, it seems that there should at least be a continuous transition between Dr. Jekyll and Mr. Hyde.

7. The Problem of Procrastination and Self-control: Why We Can't Make Ourselves Do What We Want to Do.

People don't save as much money as they used to, and also not as much as they say they want to. In fact, the average US family has thousands of dollars of credit card debt. People also procrastinate, and are often looking for ways to avoid it. In this chapter, Ariely tells a success story of Ford Motor Company, who managed to get people to follow their maintenance schedule by simplifying it at the cost of part efficiency (i.e. some parts were inspected before it was strictly necessary). He suggests that a similar idea might be applied to medicine, where people tend to fail to get routine checkups done.

He also pitches an idea for a credit card where consumers could decide ahead of time how much money they wanted to spend on certain categories of goods, and what penalties they would face if they attempted to exceed these limits.

Just yesterday I was doing some Pomodoros, which is a way of setting an artificial deadline. Ariely's advice for overcoming procrastination also includes rewarding yourself for doing things you don't wan to do, which is pretty standard advice.

A bit off subject, I'm wondering how much confirmation bias is coming into play while I'm reading this book. Am I too willing to accept that these effects are real? After all, the experimental data are presented anecdotally, with no statistical significances quoted. The person designing them could in principle have fallen victim to any number of well known biases in scientific studies. For the moment, my own recognition of these effects in my life is suspending my disbelief. It's making me very curious to what degree we can quantify these effects.

8: The High Price of Ownership: Why We Overvalue What We Have.

People tend to assign higher value to what they have, and lower value to what other people have. The main experiment presented in this chapter involved interviewing students who had won Duke basketball tickets in a lottery. Owners quoted an average selling price of $\$2400$, and non-owners quoted an average buying price of $175 - a huge difference. Both owners and sellers were more concerned with what they had to lose in the sale than what they had to gain. Ariely speculates that part of this effect comes from the transferrence of our emotional attachment to the buyer. Also, buyers are ignorant of the emotional history that the seller has to a house or a car.

This effect is important on auction sites like Ebay, where "partial ownership"  - the feeling of ownership generated by leading a bidding war for some time - might explain overbidding in the last few minutes of the auction. It also may apply to politics, religion, or other ideologies. We value the ones we hold and undervalue those of others.

How does this compare to "the grass is always greener on the other side of the fence," - where we tend to undervalue what we have and overvalue what others have? Could we set up similar experiments to demonstrate exactly the opposite effect? Could we set up an experiment that quantifies the relationship between these two effects?

9. Keeping Doors Open: Why Options Distract Us From Our Main Objective.

People tend to avoid committing to a single option when many are available, and will sacrifice expected value in order to keep these options available. In experiments, subjects were given a screen with three doors to open. Clicking inside each door gave a randomized payout, and subjects had a limited number of clicks to spend. They turned out to be pretty good at adapting their strategy to maximize expected value. Then a new condition was added, where after 8 consecutive clicks elsewhere a door would be locked permanently. Subjects preferred to jump around keeping doors open, even when the expected value for each door was advertised.

Ariely advises us to focus down on a smaller number of opportunities, and stop investing in things that are getting us nowhere, explicitly citing a woman he knew trying to choose between two boyfriends. He goes so far as to suggest that we "stop sending holiday cards to people who have moved on to other lives and friends." He also models the US Congress as a person reluctant to choose one option among many, which leads to gridlock.

I have a few issues with this chapter. The results of the door experiment are completely nuts, first of all. I can tell you that neither I or my poker buddies would think twice about letting a low-EV door close permanently. In fact, I wonder how robust these effects are against training. I know for example that anchoring is almost impossible to avoid even by experts at cognitive bias studies. Maybe this "commitment bias" is less robust.

Second, while I understand that failing to commit to a serious relationship can have bad consequences, I'm pretty sure that sending holiday cards has basically zero cost. I don't know why cutting off old friends is going to improve my life unless I'm spending so much time writing Christmas cards that I don't have time to hang out with my other friends.

Third, congress is in deadlock not because it's a single entity that fails to commit to a course of action, but because it's made of at least two entities completely committed to conflicting courses of action. I don't see why this bias applies.

10. The Effect of Expectations: Why the Mind Gets What it Expects.

The basic message of this chapter is that our experience depends on what we expect from it. Expensive wine tastes better, even if it's identical to cheap wine. World-famous classical musicians play unnoticed in subways. It's also be responsible for brand loyalty to some extent. MRI images taken from people drinking Coke and Pepsi show that the area of the brain associated with higher functions is preferentially active for Coke, meaning that it's not simply a taste experience, but also a memory experience. Ariely makes a few suggestions to help us make less biased decisions, which involve blinding ourselves to labels.

The mere fact that prior information influences our beliefs in a subjective way is not interesting - it's a fundamental tenet of probability theory. The interesting thing here is that it changes our perception in a way that depends on the time that we learn the information. For example, in a taste test, our reported experience depends strongly on whether we learn the labels before or after tasting, even if reports are made after everything.

Ariely says something interesting in this chapter. Regarding manipulating people's expectations intentionally, he says "I am not endorsing the morality of such actions, just point to the expected outcomes." So he explicitly takes an agnostic position on the ethics of learning about or using cognitive bias effects.

11. The Power of Price: Why a 50 Cent Aspirin Can Do What a Penny Aspirin Cannot.

This chapter covers the placebo effect. In experiments, pills labeled as more expensive work better. In another experiment, an inert drink was offered as a physical or mental boosting agent and had the advertised effect. Ariely suggests that it is ethical to exploit the placebo effect by intentionally prescribing them. He also comments on the ethics of experiments which test whether a treatment functions through the placebo effect.

This seems to be a special case of chapter 10's discussion of expectations. I'm interested in the ethics discussion. By now it's clear that Ariely is in favor of exploiting cognitive bias to put ourselves in positive situations, as opposed to attempting to eliminate it.

12. The Cycle of Distrust: Why We Don't Believe What Marketeers Tell Us.

People are always looking for a catch. In an experiment literally giving away free money to passersby on a college campus, only 20% of people took a $50 bill. Ariely also discusses the Tragedy of the Commons, which is a game theory scenario in which cooperation is optimal but unstable. Defection is preferred over the short term, but causes everyone to lose in the long term.

Examples are given of companies who were able to recover from PR disasters by sustained transparency efforts. Ariely says that companies can get away with lying to some small extent, but then they lose people's trust. Once it's gone it's very hard to regain.

In another experiment, people were very willing to accept obviously true statements like "the sun is yellow" if they came from unnamed sources, but if attributed to entities like Proctor & Gamble or The Democratic Party, they became suspicious (specifically, they started wondering about orange or red colors in the sun). This showed that they were looking for excuses not to believe these entities.

This chapter drives home that trust and distrust don't just cancel out when it comes to people and companies (also probably people and people). Maybe obvious in retrospect, but worth noting. Not sure I have anything more to say about that.

13. The Context of Our Character, Part 1: Why We Are Dishonest, and What We Can Do About It.

This chapter is about dishonesty, and how we think about dishonesty involving cash as different from other dishonesty, even when it has greater equivalent cost.

White-collar crimes cause much financial damage than, say, petty theft. We put lots of resources into dealing with the latter, and very little into dealing with the former. Ariely conducted an experiment at Harvard, which gave people an opportunity to cheat when reporting test scores, in a setting where better scores earned more money. He found that people cheated to a small degree when given the opportunity, but that varying the risk of being caught didn't have much of an effect. He also exposed test subjects to neutral text as well as the Ten Commandments before the test, finding that the latter group cheated less.

He suggests that requiring various professionals to take oaths of honesty policy would curb cheating, even without enforcement.

Again, Ariely uses Freud and the concept of the superego to explain this phenomenon. He states that criminals do not perform cost/benefit analyses before committing crimes. I don't know whether this is true, but I'm sure I personally would do such an analysis.

14. The Context of Our Character, Part 2: Why Dealing With Cash Makes Us More Honest.

People cheat more when cash is not directly involved, even when the link to cash is explicit. In an experiment similar to above where test takers won tokens immediately redeemable for cash, cheating increased significantly. Ariely points out that the rates of cheating measured in this experiment should be taken as a baseline, having been done on otherwise honest students in controlled conditions, with the implication that real-world cheating should occur at a much higher rate. He also contends that companies are very happy to cheat consumers out of money as long as it's not technically cash. He uses blackout days of frequent flier miles as an example: having to spend more miles to make a purchase is effectively equivalent to having to spend more cash.

The results of this experiment were surprising to me, and this is the kind of thing I don't feel like I have a good intuition for. People fail to make consistent decisions when cash vs. cash equivalents are involved. I assume this has implications not only for security, but also for marketing. I'll have to reflect on this for a while.

15. Beer and Free Lunches: What Is Behavioral Economics, and Where Are The Free Lunches?

Ariely discusses an experiment he ran in which he gave away free beer. Given four choices of beer, groups of people tended to disproportionately choose different beers from each other when asked to order out loud in series. Others ordered in secret and tended to gravitate to some beers more than others. When asked to rate the beers afterward, people rated the beers higher if they were ordered in secret. This implies that people are willing to sacrifice expected value in order to appear to be unique.

By "free lunch," Ariely is referring to win-win situations. He suggests that behavioral economics may be able to find many such lunches.

The beer experiment seems to be in conflict with what we've learned about ownership bias. If I chose some particular beer,  wouldn't I be likely to overvalue it and rate it highly? Even so, maybe the effect causes a constant bias regardless of whether it was a secret or public order. The main lesson of the book, Ariely says, is that we are "pawns in a game whose forces we largely fail to comprehend." Or in other words, if you think you're making rational decisions, you're fooling yourself.

Final Thoughts

I learned about a few new things from this book, so I'm happy I read it. I suspect that some of these ideas will be useful in my new job, but it's hard to know for sure without context. Already I'm seeing certain of these biases in my everyday life, which is a good indicator that I've internalized some of this information.

It's not clear to me how strong these effects are, particularly with respect to each other. I wonder to what extent they can be quantified. Ariely has convinced me that they influence our behavior to some degree, but without a full statistical analysis it's hard for me to know how much confidence to have in each one. The premise of the book is that we can predict irrational behavior, but it's going to make decisions without a quantitative measure, i.e. the probability and magnitude of an irrational decision.

I'm more interested in the way Ariely advocate dealing with cognitive biases. His stance is not that we try to eliminate them, or even adjust our calculations to account for known biases, but instead to embrace them. We should put ourselves in situations where our biases lead to good decisions, which may involve limiting the information we allow ourselves to access. And we should recognize that if we are happy because of a bias, that still counts as being happy. It may not be worth trying to correct a bias when doing so would ultimately make us less happy.

Ariely doesn't say anything about the ethics of using these biases to manipulate others, even though he does indeed suggest that certain manipulations would work. I'm looking forward to discussing this with more of the data science community as I meet them.