AILSA CHANG, HOST:
All right. Let's take a couple minutes now to examine some of the questions you might have that this Swedish hiring robot poses. Ifeoma Ajunwa of Cornell University has studied the use of artificial intelligence in the hiring process here in the U.S. Welcome.
IFEOMA AJUNWA: Thank you very much for having me.
CHANG: Is it possible for AI to completely eliminate human bias in the hiring process?
AJUNWA: I would say no because you still have to remember that AI isn't fully automated. What we call AI are really machine learning algorithms. And so the people who are creating them do have to be conscious of the ways that human bias could still be encoded in those algorithms. And they would have to make really conscious decisions to eliminate those bias to begin with.
CHANG: So we just heard about this, quote, unquote, "unbiased" social robot that's going to be used in job interviews in Sweden. Is there anything remotely similar to that being used now here in the U.S.?
AJUNWA: Certainly, yes. There are many hiring algorithms that are now in use in the United States. My co-author and I conducted an informal survey of the top 20 Fortune 500 companies, which are mostly retail companies. And many of those companies require candidates to submit their resumes online, where ostensibly the resume will then pass through some hiring algorithms.
And before you think, oh, this is just, you know, relegated to the blue collar market or just the hourly workforce, also, white-shoe companies like Goldman Sachs have also moved to automated hiring. So starting in 2016, Goldman Sachs moved to video interviews, for example, to interview its entering class of summer associates.
CHANG: Well, what about legal concerns with using AI for hiring? I mean, would someone even have grounds to sue for, say, discrimination if they didn't get a job and the hiring decision was made by an algorithm?
AJUNWA: So that's where it gets more complicated - right? - because a job applicant could suspect that the reason they were refused a job was based on characteristics such as race or gender, and this is certainly prohibited by law. But the problem is how to prove this. So the law requires that you prove either intent to discriminate or you show a pattern of discrimination. Automated hiring platforms actually make it much harder to do either of those.
And a lot of times, the algorithms that are part of the hiring system, they are considered proprietary, meaning that they're a trade secret. So you may not actually be able to be privy to exactly how the algorithms were programmed and also to exactly what attributes were considered. So that actually makes it quite difficult for a job applicant.
CHANG: Ifeoma Ajunwa teaches employment and labor law at Cornell University. Thank you so much for joining us today.
AJUNWA: Thank you so much.
NPR transcripts are created on a rush deadline by Verb8tm, Inc., an NPR contractor, and produced using a proprietary transcription process developed with NPR. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.