The (Honest) Truth About Dishonesty

When a scandal breaks, we run after the villain: the greedy executive, the crooked politician, the inspector who took a bribe. Dan Ariely proposes another view. For him, the greater damage does not come from the big crooks, but from lots of ordinary people making small slips that nobody calls a crime.

Think about everyday life: the extra change you got back and kept quiet about, the illegally tapped cable TV signal, the receipt left off the books to pay less, the sort-of-forced doctor's note to stretch a holiday into a long weekend. Each case looks like nothing. Added up across millions of people, they weigh far more than one big isolated scam.

That is why the book works as research and as a mirror at the same time. The question is not 'why are other people dishonest,' but 'why do I, who consider myself honest, cheat a little and still sleep well.' That question organizes everything that follows, chapter by chapter.

The starting point is an idea from economics: the model of rational crime, which the author calls SMORC, an acronym in English. According to this model, anyone weighs three things before cheating: how much they will gain, what the chance of getting caught is, and what the punishment will be if they are caught.

It sounds sensible and inspires a lot of public policy: more enforcement, bigger fines, a camera on every corner. If the model were right, raising the risk and lowering the gain would be enough to make cheating disappear. Someone who evades taxes, for example, would stop the day the fine hurt more than the savings.

The author, a name tied to behavioral economics, is suspicious of this math. He set up experiments to test each piece of the model, one at a time, and found that people behave very differently from the calculating bandit the theory imagines. The result is what the following chapters present.

The main tool in the studies is a simple task. Participants get a sheet with twenty groups of numbers and have five minutes to find, in each group, two numbers that add up to ten. The more groups they solve, the more money they earn. At the end, each person checks their own sheet.

In the control group, the researcher checks everything and the average comes out to about four correct. In the version where participants can shred the sheet and just report their result, the reported average rises to about six. Since nobody knows each person's real performance, the gap between the averages reveals the size of the cheating.

The most curious part is how it is distributed. Almost nobody made up an absurd result, like twenty out of twenty. Most people inflated their score by one or two. A few big cheaters do not explain the increase: it is lots of people doing a little, each one thinking it does not count.