British political candidate uses artificial intelligence to draw up election manifesto

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British political candidate uses artificial intelligence to draw up election manifesto
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British voters face a crowded field of 13 candidates in an upcoming special election for a Parliament seat. One, independent Andrew Gray, used artificial intelligence to come up with campaign promises that he says reflect what residents want.

, who says he has no policies of his own, crowdsourced constituents’ sentiments and used machine learning to come up with his political manifesto. He calls the technology a faster and fairer way for politicians to widely reflect views of the people they represent.said. “It doesn’t change necessarily the role of the representative. It just means that we kind of know what’s going on much more quickly and we can represent them more fairly.

Conservative lawmaker Nigel Adams’ abrupt resignation triggered Thursday’s parliamentary by-election in Selby and Ainsty, a mixed urban-rural district in northern England. It’s expected to be a hotly contested battle between the ruling Conservatives, the opposition Labour party and the rising Liberal Democrats. A host of smaller parties and independents also are running.‘s policies, developed with the use of Pol.

Pol.is, developed by a Seattle group a decade ago, has notably been used in Taiwan to find policy solutions to deadlocked issues.says Pol.is “isn’t ChatGPT,” one of the new generative AI systems that has dazzled users with the ability to produce text, images and video mimicking human work. “It’s just slightly more sophisticated polling than what is already happening.”

“The A.I. isn’t that clever that it can spit out exactly what the policies are,” he says, and still needs “human moderation and … analysis of what would be a sensible policy position.”uses Pol.is to canvas residents on local issues through his website. People can comment on a topic, such as internet speeds. Other users can click “agree,” “disagree” or “pass/unsure.” They can’t respond directly but can post their own comments.

As the conversation builds, Pol.is uses machine learning in real time to group the statements, mapping them out to show where there are gaps between viewpoints as well as areas of agreement, which ideally can encourage consensus.

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