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Artificial Intelligence is Coming for Hiring, and It Might Not Be That Bad (bloomberg.com)
Even with all of its problems, AI is a step up from the notoriously biased recruiting process, a report argues. From the report: Artificial intelligence promises to make hiring an unbiased utopia. There's certainly plenty of room for improvement. Employee referrals, a process that tends to leave underrepresented groups out, still make up a bulk of companies' hires. Recruiters and hiring managers also bring their own biases to the process, studies have found, often choosing people with the "right-sounding" names and educational background. Across the pipeline, companies lack racial and gender diversity, with the ranks of underrepresented people thinning at the highest levels of the corporate ladder. "Identifying high-potential candidates is very subjective," said Alan Todd, CEO of CorpU, a technology platform for leadership development. "People pick who they like based on unconscious biases."
AI advocates argue the technology can eliminate some of these biases. Instead of relying on people's feelings to make hiring decisions, companies such as Entelo and Stella.ai use machine learning to detect the skills needed for certain jobs. The AI then matches candidates who have those skills with open positions. The companies claim not only to find better candidates, but also to pinpoint those who may have previously gone unrecognized in the traditional process.
AI advocates argue the technology can eliminate some of these biases. Instead of relying on people's feelings to make hiring decisions, companies such as Entelo and Stella.ai use machine learning to detect the skills needed for certain jobs. The AI then matches candidates who have those skills with open positions. The companies claim not only to find better candidates, but also to pinpoint those who may have previously gone unrecognized in the traditional process.
the important question is, will the so called "artificial intelligence" (in reality, a data analysis algorithm running on fast computing infrastructure, using fuzzy logic to arrive at faster good enough probabilistic solution, rather than harder best solution, to a problem) look at only data relating to candidates' competency about the job allied to? or will it look at other data too? "diversity" quotas of the employer, personal appearance and tact, social interaction and team work skills, etc? and how exactly?
...garbage out.
If the training data is biased, the AI will learn to be biased. There have been numerous reports on this.
One of our competitors trademarked the term "hypothesis". From now on, we will call them "boneheaded ideas".
A hiring system should be biased by definition. Biased to the best candidates. If not, you are doing it wrong.
There is no way that AI in the hiring process will fix the 'diversity problem.' Mainly because the problem largely doesn't exist and is mostly PC-thuggary.
I never hear about the diversity problem in nursing or preschool school teachers where men are effectively absent from the workforce, or how women want diversity in construction jobs or automotive repair.
The sexes are different. The races are different. The cultures are different. You will not get a equal mix of them.
Not really now since under Trump there is for the first time more job openings than workers.
I know for programmers, there have been more openings most places than available workers. We've had more job openings for programmers than employees(!) for around five years despite the fact we pay over 20% more than average. There just aren't enough workers.