The art of ‘truthiness’ vs. ‘truthiness’

The study, published in Psychological Science, found that humans discriminate against questionable claims less than they do when someone is lying. If you told the researcher you can replace the 36 wearing socks with…

The art of 'truthiness' vs. 'truthiness'

The study, published in Psychological Science, found that humans discriminate against questionable claims less than they do when someone is lying. If you told the researcher you can replace the 36 wearing socks with a 45 wearing socks, she found that people judged the 48 from both groups equally, showing how a lack of trust can hold people back from taking action. In a follow-up post in The Conversation, Elizabeth Vester, a sociologist at Florida State University who researches dishonesty, said she had only read the paper, and while she had no reason to believe the study was fraudulent, she decided to retract it since the findings did not apply to her own work.

For example, she discovered that people would not trust people who are unreliable. People who would be unreliable in a storytelling example, she said, would be equally unreliable in a role-playing experiment. While this has obvious implications when it comes to honesty, Vester argues that it doesn’t go too far by implying that people can be trusted equally in every situation. Those things won’t stop people from taking honest actions, Vester writes, but they could lead to more work and be stifled by pestering, so it’s best to make sure people know the rules of the game and then abide by them.

The science of lying

Of course, honesty isn’t just an empirical phenomenon. When people lie, they’re usually doing so on purpose and aren’t simply lying to catch other people off guard. From a psychological perspective, lying is a learned behavior. It involves different actions than honest action. Take an example from mathematician Paul Taylor. Taylor takes an ethical, accounting-based stance on cheating and finds it hard to give the benefit of the doubt to his younger self. According to a fascinating talk by Taylor, he’s haunted by the thought that he should have made his kindergarten teacher believe that he was a big kid (bigger than his peers, of course), and that he could have taken home a prize that his classmates didn’t win.

When Taylor told this story to another mathematician, John Maynard Keynes, who was also a former physics teacher, he was shocked to learn that he thought nothing of the same. “I realise how complete this peculiarly embarrassing confession has had to be,” Taylor says.

Keynes took the story as an example of an obedience problem, which the economists Esmond Martin and Lijun Ren developed in the 1930s to demonstrate how people could be fooled. Any test that Ernst Bloch used for anti-fraud purposes, Keynes took to imply that no test was reliable. He called his method “impossible bonsai” to represent the effect that people can have on the tests they take.

When asked if Taylor should have insisted on making his teacher believe he was larger than other kids because there were no other kids to choose from, he said he shouldn’t have felt guilty. For someone who didn’t love rules, he was likely to miss the point entirely. He acknowledged that being little made him uncomfortable around his classmates, so he was not too persuasive with his arguments.

Ultimately, he came to realize that he could break rules, so long as he was able to do so in his own way. To understand the importance of rules, Keynes pointed out that losing your place on a train during the journey means that nobody else will win on a bid to start a new conversation or a run into an animal. Without a point of reference, no one wants to give up their seat on a train. In the games and fairs of Keynes’ day, everyone must act in accordance with the rules.

Some people in the testing world use incentives for interaction in order to ensure that people play fair. Randomness in activity, such as seat-selection or phone numbers being randomly dialed, makes sure that people show up to a race or event and do not get chucked off. But incentives can also be used to teach you behaviour that may be more challenging. The ripple effect of someone making a positive or negative point, for example, can have a significant impact.

When Cornell statistician David Weidemann looked for the role of alternate scoring in a game, he found that a positive or negative action makes as much of a difference as a negative or positive score on a tally of a game. When players are making those decisions based on emotion, it’s possible to make a new game of Spelling Bee a winnable game. At the same time, when people want to beat an opponent, or are attempting to acquire power, they can make another game they’ve lost so easy to win that players are forced to take them seriously. In the community, similar consequences might be more difficult to set in motion. When presenting his findings, Weidem

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