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Can AI Revolutionize the Hiring Process?

By George Khoury, Esq. | Last updated on

For some companies, hiring can really be an incredibly burdensome process. In addition to the usual red tape that any hire must go through, the selection process can be downright daunting if an employer receives more applications than it can reasonably review.

Fortunately, thanks to artificial intelligence, tools are being developed to improve the hiring process for employers, recruiters, and even lawyer job seekers. Also, a newly launched tool promises to help by extracting exact qualifications from an employer's job description or post, then matching those to only qualified candidates. Basically, the AI is doing the grunt work that recruiters or human resources personnel normally do.

Replacing People Isn't Revolutionary, or Is It?

While the thought of some AI program doing the work of a real person isn't new or revolutionary, there are definitely some interesting benefits from removing humans from the employment screening process. For example, an AI isn't likely to make an assumption about an individual based on the perceived race or gender a person might deduce from an applicant's name. Unconscious, implicit bias is real.

And while the obvious benefit comes from a reduction in labor costs associated with hiring as a result of replacing a person with an AI, another potential positive result could be an improved quality of candidates. For example, if a company receives 1,000 applications, without an AI screener, it might only reasonably review the first 100 or so. If there's an AI to help screen, all applications can be reviewed, and only the top dozen reviewed by an actual hiring manager.

Removing Human Error

While an AI program may be able to help a company avoid discriminatory hiring practices, AI can actually compound human errors. AI programs tend to learn from interactions with humans and data created by humans. This essentially means that an AI is only as good as the data it learns from and the parameters it's given, and if those are tinged with bias, the results are likely to be as well.

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