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This AI is trying to predict what congress will do

Posted: 6 April 2017 | By Darcie Thompson-Fields

An artificial intelligence system is trying to make sense of US Congress.

PredictGov uses machine learning to attempt to determine the future congressional bills. The system is the invention of Vanderbilt University computer science Ph.D. John Nay, law Professor J.B. Ruhl and their team. It pulls from decades of congressional data and hundreds of variables, including sponsor, amendments, economic trends and political shifts.

The website predicted that the Affordable Care Act replacement bill would be shelved, awarding it a 15 per cent chance of enactment.

“Beyond predicting the likely outcome, we provide understanding of the context of the bill,” said Nay, according to The Huffington Post.

“A bill is just a vehicle… Many potential policies often hop on and off along the way to the unlikely destination of the U.S. Code.”
Each bill’s score updates every 24 hours, accounting for amendments on the politically agnostic platform.

The Affordable Care Act’s replacement bill’s score of 15 per cent is higher than average; at most, 6 per cent of bills introduced into Congress become law. Only legislation with little or no controversy gets a probability score of 40 percent or higher.

You can explore PredictGov’s predictions here.

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