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The branch of social science that studies politics is referred to as political science. It may be used positively in the context of a "political solution" which is compromising and non-violent, [1] or descriptively as "the art or science of government", but also often carries a negative connotation. A variety of methods are deployed in politics, which include promoting one's own political views among people, negotiation with other political subjects, making laws , and exercising force , including warfare against adversaries. In modern nation states , people often form political parties to represent their ideas. Members of a party often agree to take the same position on many issues and agree to support the same changes to law and the same leaders. An election is usually a competition between different parties.

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By Jeffrey Dastin. O machine-learning specialists uncovered a big problem: their new recruiting engine did not like women.

But bythe company realized its new system was not rating candidates for software developer jobs and other technical posts in a gender-neutral way. Most came from men, a reflection of male dominance across the tech industry.

They did not specify the names of the schools. Amazon edited the programs to make them neutral to these particular terms. But that was no guarantee that the machines would not devise other ways of sorting candidates that could prove discriminatory, the people said.

The Seattle company ultimately disbanded the team by the start of last year because executives lost hope for the project, according AArticle the people, who spoke on condition of anonymity. It did not dispute that recruiters looked at the recommendations generated by the recruiting engine. The company's experiment, which Reuters is first to report, offers a case study in the limitations of machine learning. N that are looking to automate portions of the hiring process.

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Some 55 percent of U. Employers have long dreamed of harnessing technology to widen the hiring net and reduce reliance on subjective opinions of human recruiters. But computer scientists such as Nihar Shah, who teaches machine learning at Carnegie Mellon University, say there is still much work to do. Machine learning was gaining traction in the technology world, thanks to a surge in low-cost computing power. Their goal was to develop AI that could rapidly crawl the web and spot candidates worth recruiting, the people familiar with the matter said.

The group created computer models focused on specific job functions and locations. The algorithms learned to assign little significance to skills that were common across IT applicants, such as the ability to write various computer codes, the people said.]