Summary of Nudge, presented to IxDA LA

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This is a presentation that covers the basic concepts of the book Nudge, by Richard Thaler and Cass Sunstein. We read this book at our UX Book Club meeting, and I presented an introduction to it at the LA IxDA meeting.

Text of Summary of Nudge, presented to IxDA LA

  • anintroduc+onto Nudge ImprovingDecisionsAbout Health,Wealth,andHappiness by Richard H. Thaler & Cass R. Sunstein presented by Sarah G. Mitchell What I am presenting is only an introduction to this rich and in-depth book. If youre interested in what I cover here, I encourage you to read the book. Both of the authors are economists and professors, and Cass Sunstein now leads the White House Office of Information and Regulatory Affairs. In the book they focus on public policy, and situations like healthcare, the environment, and saving for retirement, but many of the concepts they cover have relevance to the kinds of situations and choices we design.
  • Whatisanudge? A nudge is any aspect of the design of a choice (choice architecture) that alters peoples behavior in a predictable way, without forbidding anything or actually changing the choice at all. The example that went out in the event invitation was the clever internet cafe named their wireless network Have you tried the carrot cake.
  • Whydoweneednudges?
  • Freedomofchoice isbest,right? Many economists (and some of the engineers I know) like to say that we dont know better than the user/chooser, that we should present all options to people, and let them choose. The authors say this makes the false assumption that almost all people, almost all of the time, make choices that are in their best interest, or at least are better than choices someone else would make for them.
  • They are assuming that we are all like Spock. (Or maybe like a true Vulcan, since Spock is actually half human, as we all know.) And like Spock we always only choose the most logical choice. However, while part of our mind really is like Spock, we all have TWO decision makers in our head who battle it out for each decision - our Spock (in scientic terms, our Reective Cognitive System) and but also our Homer (Automatic Cognitive System).
  • vs. Gut Mind (Automa+cCogni+veSystem) (Reec+veCogni+veSystem) They are assuming that we are all like Spock. (Or maybe like a true Vulcan, since Spock is actually half human, as we all know.) And like Spock we always only choose the most logical choice. However, while part of our mind really is like Spock, we all have TWO decision makers in our head who battle it out for each decision - our Spock (in scientic terms, our Reective Cognitive System) and but also our Homer (Automatic Cognitive System).
  • Heres a classic example. Spock would look at this image and see clearly that the two tabletops are exactly the same size. But most of us feel pretty sure that the one on the left is longer and skinnier than the one on the right.
  • Thereisnosuchthingas anudgelesschoice. So the conclusion the authors draw from this is that SOMETHING is always inuencing your choices. People are inuenced by small factors in the design of an experience, so even if you dont consciously design your choice architecture, it is still there, affecting the actions of the choosers.
  • CAFETERIALINEIMAGE Heres another example. In this cafeteria, Spock would only put food on his tray that is good for him, only taking as much as he needs and only what he can afford. But our Homer is in there, reacting instinctively to many things, like which things are at the beginning versus the end, and which things are up at eye level and which are below. In fact, in one study mentioned in the book, the researchers were able to increase or decrease selection of specic foods by 25%, just by rearranging them.
  • So say you are designing a cafeteria layout. What should you do? Ignore the fact that the layout affects what people buy? Randomly rotate the placement of foods? Set it up to sell the most of the expensive stuff? Or set it up so people choose more healthy foods? The book encourages that last option with what they call libertarian paternalism - Nudging the user (through placement, in this example) to make the best choice for his well being - WHAT OUR SPOCK WOULD WANT, while not restricting choice at all. They are not banning junk food, just making it less likely that someone will choose it on their own.
  • Whendoweespecially neednudges?
  • When is our Spock particularly weak and our Homer particularly strong. This happens predictably in the following scenarios:
  • Whenweseethebenets now,costslater.
  • I enjoy the benet of this donut now, I pay the cost (to my health, waistline) later. I enjoy coming home to a cool house because my AC was running all day, I pay the costs (both bills and environmental) later.
  • Whenencounteringdecisions wemakeinfrequently.
  • We get better at everything through practice. If you had to optimize your investments as frequently you have to drive your car, youd probably be better at it.
  • Whenfeedbackisnot immediate.
  • Think of the impact digital cameras had on hobby photography, largely because you can see right away what your picture looks like. Making investment decisions is kind of like the old lm photography model. You rearrange some stuff, and hope when you go back to see the results you can remember what you did and extrapolate what worked and what didnt.
  • Whenitishardtoimaginethe possibleoutcomes.
  • Imagine ordering at a restaurant from a menu in a language you do not understand. For many people, this is what it is like to try to decide between investing in a capital appreciation fund vs a dynamic dividend fund. The language of the choice selection makes it very hard to imagine what the options really mean to you.
  • PredicDngHomers AcDons So we know that our gut, our Homer, has more inuence our decisions in those types of situations. Fortunately, hes pretty predictable, and therefore relatively easy to set up safeguards agains. Ill cover 3 of the main ways to predict what people will do.
  • 1. Wehavepredictable mentalbiases.
  • AnchoringBias: Weareheavilybiasedby wherewestart.
  • Say I told you, the population of Chicago is 3 million. What is the population of Milwaukee? You might guess something like 1 million.
  • If I instead told you, The population of Green Bay is 100,000. What is the population of Milwaukee? Most people guessed around 300,000. (The actual population is around 580,000.)
  • AvailabilityBias: Weoveres+matethe likelihoodofeventswecan easilyremember. ?
  • We are much more scared of vivid and easily imagined threats (like plane crashes or tornadoes), than we are of mundane but much more common dangers (like asthma attacks). We are 20x more likely to die of asthma attack than tornado, so if we were purely rational, wed be 20x more scared of asthma than tornadoes.
  • RepresentaDvenessBias: Wesome+messeepaMerns wheretherearenone.
  • Based on the beauty pageant contestants youve seen in the media lately, you might think that ALL of them are dumb as a post. (Thats not true.) Another example: If you wore your old hat during two games which your team won, you might assume that its a lucky hat, and that if you dont wear it during the next game, your team will lose. (Sorry, theres no connection.)
  • UnrealisDcOpDmism: Almostallofusthinkweare beMerthanaverage.
  • 90%predict theywill scorehere. - + In one study the authors conducted, 90% of their students predicted they would nish in the top 2 percentiles in their class.
  • LossAversion: Wearehappywhenwegain something,buttwiceas unhappywhenweloseit.