Should Testing Be Used Ineffective And Inefficient - amazonia.fiocruz.br

Should Testing Be Used Ineffective And Inefficient Video

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 Teting 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.

MASCULINE LANGUAGE

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 to the people, who spoke on condition of anonymity.

It did not dispute that recruiters looked at the recommendations generated read article the recruiting engine. The company's experiment, which Reuters is first to report, offers a case study in the limitations of machine learning.

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N that are looking to automate portions of the hiring process. 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, here 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 PROBLEM, OR THE CURE?

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. Gender bias was not the only issue. With the technology returning results almost at random, Amazon shut down the project, they said.

Other companies are forging ahead, underscoring the eagerness of employers to harness AI for hiring. Kevin Parker, chief executive of HireVue, a startup near Salt Lake City, said automation is helping firms look beyond the same recruiting networks upon which they have long relied. L and Hilton. O LinkedIn, the world's largest professional network, has gone further. It offers employers algorithmic rankings of candidates based on their fit Should Testing Be Used Ineffective And Inefficient job postings on its site. Still, John Jersin, vice president of LinkedIn Talent Solutions, said the service is not a replacement for traditional recruiters. Some activists say they are concerned about transparency in AI. Still, Goodman and other critics of AI acknowledged it could be exceedingly difficult to sue an employer over automated hiring: Job candidates might never know it was being used.

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As for Amazon, the company managed to salvage some of what it learned from its failed AI experiment. Another said a new team in Edinburgh has been formed to give automated employment screening another try, this time with a focus on diversity. Retail Updated. By Jeffrey Dastin 8 Min Read.]