When I was a senior in college, I applied for a job that required me to play a video game on my phone as part of the interview process. I remember sitting in the architecture library — my finals, thesis and graduation looming — and manically tapping my iPhone screen to manipulate an animated rocket ship. |
What is this measuring? I wondered. And what does this have to do with the job, an entry-level position in the art world? But, aware that the game was likely tracking my tenacity or focus or some other vague but useful dimension of my personality, I dutifully kept tapping and swiping. |
I ended up taking myself out of the running for the job and accepting a different one. But I have never forgotten the disorienting experience of completing what the company called a psychometric, game-based objective assessment of my personality. I remain curious about what they gleaned. |
These types of human-free evaluations are becoming increasingly popular, especially as companies evaluate candidates remotely. But in addition to feeling arbitrary at times, the use of automated tools for hiring can reinforce bias and exclusion, as such tools sometimes favor job candidates whose backgrounds and behavior match those of workers who are deemed successful by their employers, and therefore risk replicating a company's existing demographic makeup. |
This hiring practice is even more consequential because of a pandemic that has exacerbated racial disparities in the work force. Many people already face workplace biases, even without of A.I. — a New York Times analysis of Bureau of Labor Statistics data found that, among other disparities, significantly fewer Black and Hispanic women are working now than any other demographic. |
New York's City Council is working to address one dimension of the problem as it considers proposed legislation that would change how companies approach the use of tech in hiring. In an Op-Ed this morning, Alexandra Reeve Givens, the chief executive of the Center for Democracy and Technology; Hilke Schellmann, a reporter and assistant professor of journalism at New York University; and Julia Stoyanovich, an assistant professor of computer science and engineering, and of data science, at N.Y.U., argue that the legislation could make a material difference if done right. And they recommend adding several protections to the bill that would ensure the new regulations meaningfully combat bias in hiring. |
This story is so much bigger than New York. In getting this regulation right, they argue, the city would not only make hiring fairer for its own residents, but it could also influence similar regulations nationwide. It's, as they write, a "chance to combat new forms of employment discrimination and get closer to the ideal of what America stands for: making access to opportunity more equitable for all." |
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