Review of “Cheaters, Liars or Both? A New Classification of Dishonesty Profiles” (2020)
Adrián Muñoz (writer), Beatriz Gil-Gómez de Liaño (writer), David Pascual-Ezama (writer), Drazen Prelec (writer).
Read in 2020.
A typology of dishonesty in games of random chance. The result of a first version of an experiment, using a secretly monitored web site to simulate a coin flip with laboratory volunteers and Mechanical Turk workers (both being paid more real money for a “white” result), are summarized as follows in the paper.
| Lab | MTurk | ||||
|---|---|---|---|---|---|
| (n=93) | (n=52) | (n=85) | (n=43) | ||
| Flip the coin - obtain white - report white | LUCKY | 44% | - | 49% | - |
| Flip the coin - obtain black - report black | HONEST | 22% | 41% | 19% | 37% |
| Flip the coin - obtain black - repeat until white - report white | CHEATERS NON-LIARS | 10% | 17% | 3.5% | 7% |
| Flip the coin - obtain black - report white | LIARS | 13% | 23% | 3.5% | 7% |
| Do not flip the coin at all - report white | RADICAL DISHONEST | 11% | 19% | 25% | 49% |
The so-called “radical dishonest” category comprises people who both cheated (did not follow instructions) and lied (reported a result they did not get). These were identified by reporting a result too quickly to have gone to any web site other than the monitored one the researchers had prepared. The experiment is repeated with a die roll, permitting degrees of dishonesty but obtaining the same basic typology.
The discussion is interesting but doesn’t quite explain why the “MTurker” samples were more prone to radical dishonesty. I speculate that it has to do with motivational crowding out: Being alredy engaged in a primarily monetary relationship, they would maximize return on investment, rather than profit itself.