AI can predict your political ideology just by taking a brain scan

​Artificial intelligence can predict a person’s political ideology simply by analyzing scans of functional connections in the brain. The AI ​​was accurate about 70 percent of the time, which is roughly equivalent to predicting a person's political beliefs based on their parents' ideologies. While this research is certainly exciting, it is essentially pattern hunting with big data, and uncovering the neural roots of ideology will be more difficult.

"Do people's brains reflect their chosen political orientation, or does the functional structure of their brains choose their political orientation?"

A team of researchers from Ohio State University, the University of Pittsburgh, and New York University presents this thought-provoking chicken-or-egg dilemma. Their new research shows that artificial intelligence can accurately guess a person's political ideology simply by analyzing their brain scans. The work is published in the journal PNAS Nexus.

Neuroscience and Politics

Scientists have previously used brain scanning technology to delve into the neuroscientific basis of political beliefs. For example, researchers previously found that conservatives tended to have larger gray matter volumes in their amygdala (a region associated with fear, anxiety, and aggression), while liberals tended to have larger anterior cingulate cortex (additionally, they were associated with ethics and morally relevant). Another experiment showed that the brains of liberals and conservatives respond differently to words in political videos that "introduce strong emotions."

In the current study, researchers observed and recorded functional connections in the brains of 174 healthy young adult subjects as they performed a variety of simple tasks, such as pressing a pop-up button as quickly as possible. button to win a monetary reward, match a name to a face, or answer true or false questions about the story they just read. The subjects' brains were also scanned while in a calm state - awake and relaxed, with their eyes closed.

Measurements of functional connectivity (FC) are relatively rare in political neuroscience. FC refers to how different parts of the brain show similar activity at the same time, as if they are communicating with each other. The researchers used a state-of-the-art artificial intelligence deep learning technology called BrainNetCNN. The technique, run on an Ohio State supercomputer, analyzed functional connectivity data from all tasks and related it to subjects' self-reported political ideology, which was rated from very liberal to very conservative.

BrainNetCNN is able to use this data to predict a person's political ideology with about 70% accuracy, similar to what you would expect from guessing a person's ideology based on their parents' beliefs - This is actually considered one of the strongest predictors of ideology in political science.

"This study shows that the biological and neural roots of political behavior are much deeper than previously thought," the researchers wrote.

Neuropolitics? Not So Fast

While this research is certainly exciting, it is essentially pattern hunting with big data. That's fine, but a model is only robust and broadly applicable if it's based on a large, diverse research group. In this case, the subjects were young people, seven out of ten of whom were liberals. Therefore, the model may not work if tested on other Americans (or people in general). Furthermore, AI cannot tell us anything about the neurological roots of ideology; it is not designed for that. Answering this question would be a higher task.

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