Predicting crime by examining the brain

A group of neuroscientists at the University of New Mexico propose to use brain imaging technology to improve risk assessments, reported The Marshall Project. Kent Kiehl, a professor of psychology, neuroscience and the law at the University of New Mexico, said that by measuring brain structure and activity they might better predict the probability an individual will offend again.

Neuroprediction, as it has been dubbed, evokes uneasy memories of a time when phrenologists used body proportions to make pronouncements about a person’s intelligence, virtue, and — in its most extreme iteration — racial inferiority.

Yet predicting likely human behavior based on algorithms is a fact of modern life, and not just in the criminal justice system. After all, what is Facebook if not an algorithm for calculating what we will like, what we will do, and who we are?

In a recent study, Kiehl and his team set out to discover whether brain age — an index of the volume and density of gray matter in the brain — could help predict rearrest.

Age is a key factor of standard risk assessments. On average, defendants between 18 to 25 years olds are considered more likely to engage in risky behavior than their older counterparts. Even so, chronological age, wrote the researchers, may not be an accurate measure of risk.

The advantage of brain age over chronological age is its specificity. It accounts for “individual differences” in brain structure and activity over time, which have an impact on decision-making and risk-taking.

After analyzing the brain scans of 1,332 New Mexico and Wisconsin men and boys — ages 12 to 65 — in state prisons and juvenile facilities, the team found that by combining brain age and activity with psychological measures, such as impulse control and substance dependence, they could accurately predict rearrest in most cases.

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