Americans think that about one in three people in the U.S. is an immigrant. In reality, it’s more like one in six. So what? This kind of overestimation is often treated as a sign of fear, ignorance, or political bias. Cue the fact-checkers, the infographic warriors, and the policy wonks trying to “correct” public opinion. But what if the real issue… is just cognitive?
A new study by Brian Guay and colleagues, which I found via Dan Willingham, turns this whole story on its head. They analysed over 100,000 estimates from 22 countries and found that the problem isn’t what people believe about groups—it’s how they think about proportions. Across the board, people overestimate small groups and underestimate large ones. This isn’t about minorities or politics. It’s about math and brains.
Why does this happen? Because we humans are bad at guessing proportions. When unsure, our brains pull estimates toward a middle-ground “prior” we carry around—an internal sense of what seems reasonable. So we inflate small numbers, deflate big ones, and do all this on a nonlinear, log-like mental scale. It’s a psychological quirk, not a political statement.
The researchers built a model—aptly called “Uncertainty-Based Rescaling”—to capture this behaviour and tested it against the usual suspects: “perceived threat” and “social contact.” Those theories claim people see minorities as larger because they fear them or encounter them more often. Sounds intuitive. But the data say otherwise. Even minority respondents overestimate their own group size. Even non-political categories (like “passport holders” or “microwave owners”) follow the same distorted curve. You don’t need group-specific explanations when a general psychological one fits better.
None of this means prejudice isn’t real. But it does mean we should stop misinterpreting noisy estimates as meaningful bias indicators. If your anti-racism campaign is based on “correcting” population guesses, you might be aiming at a cognitive artefact instead of an actual problem.
In short, before we argue about what people think, we should look at how they think.
Abstract of the review:
Americans dramatically overestimate the size of African American, Latino, Muslim, Asian, Jewish, immigrant, and LGBTQ populations, leading to concerns about downstream racial attitudes and policy preferences. Such errors are common whenever the public is asked to estimate proportions relevant to political issues, from refugee crises and polarization to climate change and COVID-19. Researchers across the social sciences interpret these errors as evidence of widespread misinformation that is topic-specific and potentially harmful. Here, we show that researchers and journalists have misinterpreted the origins and meaning of these misestimates by overlooking systematic distortions introduced by the domain-general psychological processes involved in estimating proportions under uncertainty. In general, people systematically rescale estimates of proportions toward more central prior expectations, resulting in the consistent overestimation of smaller groups and underestimation of larger groups. We formalize this process and show that it explains much of the systematic error in estimates of demographic groups (N=100,170 estimates from 22 countries). This domain-general account far outperforms longstanding group-specific explanations (e.g., biases toward specific groups). We find, moreover, that people make the same errors when estimating the size of racial, nonracial, and entirely nonpolitical groups, such as the proportion of Americans who have a valid passport or own a washing machine. Our results call for researchers, journalists, and pundits alike to reconsider how to interpret misperceptions about the demographic structure of society.