Study shows how A.I. can accurately predict how people vote in elections

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A recent experiment from a research team at BYU examined the ways in which artificial intelligence can predict how different demographics will vote in elections. 

The study – conducted by a team of political and computer science professors and graduate students at BYU – examined ways in which AI could be used as a substitute for human responders in survey-style research. 

ChatGPT 4 displayed on smartphone with OpenAI logo seen on screen in the background, in Brussels, Belgium.   (Jonathan Raa/NurPhoto via Getty Images)

To see whether this was possible, the team tested the accuracy of programmed algorithms of a GPT-3 model, which mimics the relationship between human ideas, attitudes and sociocultural contexts of various demographics. 

In one experiment, the researchers created artificial personas, assigning attributes like race, age, ideology and religiosity. Then, using data from the American National Election Studies (ANES), the team tested to see whether their "personas" voted the same way people did in the 2012, 2016 and 2020 U.S. presidential elections. 

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Ultimately, the researchers found a "high correspondence" between how the AI personas voted, and how the American public did in those elections. 

David Wingate, a computer science professor and co-author on the study, said he was "absolutely surprised" to see how accurately the experiment matched up. 

What was notable, Wingate said, was that the algorithm model hadn’t been trained to "do political science," but on a "hundred billion words of text