Human brains are extraordinary machines, capable of processing vast amounts of information and making rapid decisions based on patterns observed in the environment. This ability, often termed as statistical learning, allows us to navigate complex social landscapes with remarkable efficiency. However, this same mechanism can also give rise to unintended negative consequences, such as racism. As strange as it sounds, racism might stem from this built-in cognitive process, shaped by the environments we grow up in and the patterns we repeatedly encounter.
Statistical learning is the brain’s way of recognizing patterns and making predictions based on those patterns. When we see something happen repeatedly, our brains begin to expect it. This is a useful skill for survival as it helps us learn language, understand social cues, and predict outcomes based on past experiences. However, this process can also lead to the formation of stereotypes and biases, especially when it comes to race and ethnicity.
In many cities, people of the same ethnicity often end up living in the same neighborhoods. These areas can develop distinct cultural, economic, and social characteristics. For example, in San Jose, Vietnamese and Mexican communities are predominantly clustered on the east side, which is also the poorest part of the city. This geographical and socioeconomic clustering can lead to reinforced stereotypes. If people frequently observe certain ethnic groups face higher levels of poverty and commit more crime, their brains start to associate these characteristics with those ethnic groups.
Once these associations are formed, they can influence our expectations and behaviors, often without our conscious awareness. For instance, if the news reports a crime committed by a homeless person in San Jose, the cognitive bias formed by the observed patterns might lead some people to assume that the perpetrator is more likely to be from the Vietnamese or Mexican community as opposed to the Chinese or Indian one. This is not entirely unfounded statistically but is problematic because it simplifies complex social realities and overlooks the individual variability within these groups.
While statistical learning helps our brains to process information efficiently, it can also lead to oversimplifications and unfair judgments. Race and ethnicity are immutable characteristics that individuals cannot change, and making assumptions based on these factors alone is inherently unjust. People are shaped by a multitude of influences beyond their race or ethnicity, including their personal experiences, education, and individual choices.
To counteract the negative effects of statistics, it is crucial to engage in conscious and deliberate efforts to use a broader range of information when judging individuals. This means considering factors such as personal behavior, qualifications, and context. By doing so, we can move beyond the cognitive shortcuts that lead to traditional racism.
