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Illustration: Sarah Grillo/Axios

One of the fastest-growing workplace applications of artificial intelligence is in hiring, but imperfect algorithms leave qualified women and candidates of color out — and can ultimately build weaker teams.

Why it matters: Algorithms are most often used to make the initial applicant screening process — the resume review — more efficient. But their role cannot be underestimated, as around 95% of all job applicants are rejected based on resumes.

But, but, but: Using AI to recruit isn't inherently bad, says Danielle Li, a professor at MIT and c0-author of a new working paper on algorithmic hiring. It's about using the right kind of algorithm.

Li and her colleagues tested different types of algorithms using a Fortune 500 company's data. The AI's test was to select candidates for first-round interviews for jobs in consulting, financial analysis and data science — all of which pay well and have been criticized for lacking diversity.

One algorithm used a traditional machine learning approach, making predictions about the future based on data from the past.

  • For example, if a company had hired several white, male computer science degree-holders from Stanford and those people had been relatively successful at the firm, the algorithm would demonstrate a strong preference for those applicants.
  • "This approach works if you think history is complete," Li tells Axios. "You have to assume that the things that predicted quality in the past will predict quality in the future. But we know that that's not true."

Another algorithm used a much more exploratory approach, incorporating bonus points for applicants who had untraditional majors, came from different places or had unusual work histories. The algorithm was not instructed to prefer applicants of color or female applicants.

  • This approach treated hiring as a dynamic problem, Li says, valuing giving applicants the opportunity to show their chops.
  • This algorithm increased the share of Black and Hispanic candidates selected for first-round interviews from 10% (with human evaluators) to 23%. The share of women selected went from 35% to 39%.

The bottom line: "Lots of companies have taken interest in using AI tools in the recruiting process," Li says. "In that world, algorithms stand to have a big impact."

Go deeper

Bryan Walsh, author of Future
Nov 14, 2020 - Technology

AI talent appears open to working on defense — with caveats

An aerial view of the Pentagon. Photo: Bill Clark/CQ Roll Call, Inc. via Getty Images

A new survey offers some evidence that most artificial intelligence experts are positive or neutral when it comes to working with the Pentagon on AI-enabled projects.

Why it matters: Employee concerns have led some tech companies to pull back from working on defense-related projects in the past, but for many in the AI world, the chance to work on intellectually challenging projects — and the Pentagon's not insignificant budget — seems too good to pass up.

54 mins ago - Podcasts

Former Georgia Gov. Roy Barnes on the Senate runoffs

The future of U.S. politics, and all that flows from it, is in the hands of Georgia voters when they vote in two Senate runoffs on January 5.

Axios Re:Cap digs into the election dynamics with former Georgia Gov. Roy Barnes, a Democrat who served between 1999 and 2003.

1 hour ago - Health

Cuomo orders emergency hospital protocols as COVID capacity dwindles

Gov. Andrew Cuomo (D). Photo: Lev Radin/Pacific Press/LightRocket via Getty Images

New York Gov. Andrew Cuomo said on Monday that struggling state hospital systems must transfer patients to sites that are not nearing capacity, as rising coronavirus cases and hospitalizations strain medical resources.

Why it matters: New York does not expect to get the same kind of help from thousands of out-of-state doctors and nurses that it got this spring, Cuomo acknowledged, as most of the country battles skyrocketing COVID hospitalizations and infections.