Stereotypes Affect Our Predictions
The decisions we make for others can be skewed by how we perceive a group.
We make a lot of little decisions for ourselves. Soup or salad? Blue socks or black? But we also make bigger decisions within our society. Take, for example, a doctor, who decides whether or not to write someone a prescription. Or a state politician, who has to determine whether or not to support a new housing policy. You would think that the more information we have about other people, the better job we’d do at predicting what they need and what might cause them pain or pleasure, right? Wrong.
New research, published in Psychological Science, sheds light on what is called “affective forecast.” Affective forecast is the term psychologists use for the prediction we make about how other people will feel.
“Doctors might try to gauge the amount of pain people are in when deciding the kinds of drugs to prescribe them, employers might consider how happy their employees would be made by a smaller or larger holiday bonus, and politicians may consider the pain and distress that people are experiencing when deciding whether to intervene in a humanitarian crisis,” wrote psychological scientist and study author Mina Cikara of Harvard University when explaining the term.
She and her collaborators looked at whether or not having more information about other people makes us better, or worse, judges of how they will feel. They found that the more information we have, the more stereotypes kick in, tilting our views and making us worse judges.
They asked participants to report a political affiliation—Democrat or Republican—and were then asked how an individual (a “person,” a “Democrat” or a “Republican”) would feel the day after their party won or lost the majority in the senate. The data showed that when people made predictions for one party or the other, they overestimated emotions, either happy or sad, compared to how they judged a neutral “person” would feel. The researchers found the same thing to be true with a Harvard v. Yale annual game, forecasting how fans would feel. They were more accurate gauging the emotions of a fan, when the fan’s affiliation was unspecified. It turns out that the less we know about someone, the more we’re able to consider him or her like ourselves, like “naturally anyone would feel...”
The researchers hypothesize that this bias in affective forecasting may in fact explain America’s increasing political and economic polarization.
Wrote another researcher involved on the study, Harvard University’s Tatiana Lau. “When we overestimate how other members of our own group and the other group feel, and out-group members do likewise, we are building a vicious cycle of expectancy violations that can escalate conflict and other partisan divides, whether at the voting booth, at the negotiation table, or at the trade policy summit.”
Here’s one instance where knowing less is more.