Nudge: The Final Edition

by Richard H. Thaler

The same principles of good design and functional architecture apply in the world of choices as well. Our primary mantra is a simple one: if you want to encourage some action or activity, Make It Easy.

Often we can do more to facilitate good behavior by removing some small obstacle than by trying to shove people in a certain direction.

Defaults are ubiquitous and powerful. They are also unavoidable in the sense that for any node of a choice architecture system, there must be an associated rule that determines what happens to the decision maker if she does nothing.

If people know their preferences, and know that they dislike the outcome that is embedded in the default, they will probably change it.

Active choosing has the advantage of overcoming inertia, inattention, and procrastination; choice architects can find out what people actually prefer, without having to guess.

To work, prompted choice has to have a default (to establish what happens if you disregard the prompt).

We believe that required choice, favored by many who like freedom, is often the best way to go. But consider two objections to that approach. First, Humans will often consider required choice to be a nuisance or worse, and would much prefer to have a good default.

Second, required choosing is often more appropriate for simple yes-or-no decisions than it is for more complex choices.

Humans make mistakes. A well-designed system expects its users to err and is as forgiving as possible.

Leaving the gas cap behind is a special kind of mistake psychologists call a “postcompletion” error.7 The idea is that when you have finished your main task, you tend to forget things relating to previous steps.

Another strategy, suggested by Don Norman, is to use what he calls a “forcing function,” meaning that in order to get what you want, you have to do something else first. So if you have to remove the card in order to get your cash, you will not forget to do so.

An excellent way to help Humans improve their performance is to provide feedback. Well-designed systems tell people when they are doing well and when they are making mistakes.

But warning systems have to avoid the problem of offering so many warnings that they are ignored.

If all of the flavors are familiar, most people will be able to predict with considerable accuracy the relation between their choice and their ultimate consumption experience. Call this relation between choice and welfare a mapping.

A good system of choice architecture helps people to improve their ability to map choices onto outcomes and hence to select options that will make them better off.

When we face a small number of well-understood alternatives, we tend to examine all the attributes of all the alternatives and then make trade-offs when necessary. But when the choice set gets large, we must use alternative strategies, and these can get us into trouble.

A self-nudge can be called a “snudge,” and for most of us, life can be improved via well-chosen snudges.

People work to counteract their own self-control problems, often by redesigning the architecture within which they make choices—for example, by making certain options harder or less fun, or by eliminating them together.

One strategy to use is what Amos Tversky called “elimination by aspects.” Someone using this strategy first decides what aspect is most important (say, commuting distance), establishes a cutoff level (say, no more than a thirty-minute commute), then eliminates all the alternatives that do not come up to this standard.

When people are using a simplifying strategy of this kind, alternatives that do not meet the minimum cutoff levels may be eliminated even if they are fabulous on all other dimensions.

As alternatives become more numerous and more complex, choice architects have more work to do, and are much more likely to influence choices (for better or for worse).

Collaborative filtering is an effort to solve a problem of choice architecture. If you know what people like you tend to like, you might well be comfortable in selecting products you don’t know, because people like you tend to share your tastes.

A cautionary note: Surprise and serendipity can be fun for people, and good for them too, and it may not be entirely wonderful if our primary source of information is about what people like us like.

Structuring choice sometimes means helping people to learn, so they can later make better choices on their own.

Sensible architects will align the incentives of the most important decision makers. One way to start to think about incentives is to ask four questions about a particular choice architecture: Who chooses? Who uses? Who pays? Who profits?

When the answers to the first three questions above is one person, markets tend to work reasonably well, at least so long as people have adequate information and are not suffering from behavioral biases.

Do choosers actually notice the incentives they face? In free markets, the answer is usually yes, but in important cases it can be no.

a behavioral analysis of the incentives of car ownership will predict that people will underweight the opportunity costs of car ownership and possibly other less salient aspects, such as depreciation, and may overweight the very salient costs of using a taxi.*

One tool in the choice architect’s arsenal can be easy to neglect: when to schedule an intermission.

Small shops compete via curation, while online megastores use navigation tools to make finding and choosing among so many options easy.

Serendipity can be fun, for books, music, and movies, as well as wine. Good curation combines getting rid of bad options and introducing novel ones.

some people have a simple philosophy: Just Maximize Choices. That’s not always a bad idea, but it can be problematic without sophisticated choice architecture tools. Instead, a well-curated small selection and/or a good default can produce quite satisfactory outcomes.

the first mantra of nudging is to make it easy to take the desired action. A good complement to this advice is to make the desired activity fun.

Twain said that “work consists of whatever a body is obliged to do. Play consists of whatever a body is not obliged to do.”

When lotteries are used to motivate people, it is important to get the details right. Participants are likely to find a lottery more enticing if they find out whether they would have won.

Lotteries are just one way to provide positive reinforcement. Their power comes from the fact that the chance of winning the prize is overvalued.

An alternative to lotteries is a frequent-flyer-type reward program, in which the points can be redeemed for something fun.

In whatever manner it came to be, the adoption of money, or other measures of value, allowed for greater efficiency because relying on barter is highly limiting.

The benefit is that through regularization, consumers can easily compare the offers from competing suppliers.

The fine print contains that information the seller is required to tell you but does not want you to read. The fine print is where you can find the disclosures.

there is an initial question whether to require certain information to be disclosed. Maybe markets are working plenty well enough, and a mandatory disclosure is unnecessary. Then there is a second question, which is how to require that information be disclosed. The second question is always one of choice architecture.

Here we make the radical suggestion that it is time for disclosure rules to make use of at least twentieth-century technology.

Smart Disclosure is a set of policy rules meant both to solve the problem of the fine print and to facilitate better decisions by consumers.

First, complex information should be disclosed and made available in a format that is both standardized and machine readable.

Second, any organization, public or private, that keeps track of information involving the behavior of individuals or households should gener...

we expect that only the most obsessive and tech-savvy consumers would ever make use of such files themselves. Rather, the data would be imported into software designed to help people make better choices.

We call companies that help consumers to search among various options choice engines. A key thing to note about choice engines is that their ability to function depends crucially on their access to timely and accurate data on prices and availability.

Netflix has possession of something valuable, which is your own past behavior. That gives them an advantage over any competitor that is starting fresh.

But shouldn’t you have a right to make use of your past viewing behavior as well?

Perhaps the most basic principle of good choice architecture is our mantra: Make It Easy. If you want to encourage some behavior, figure out why people aren’t doing it already, and eliminate the barriers that are standing in their way.