Algorithms make many important decisions for us, like our creditworthiness, best romantic prospects and whether we are qualified for a job. Employers are increasingly using them during the hiring process out of the belief they’re both more convenient and less biased than humans. However, as I describe in a new paper, this is misguided.

In the past, a job applicant could walk into a clothing store, fill out an application and even hand it straight to the hiring manager. Nowadays, her application must make it through an obstacle course of online hiring algorithms before it might be considered. This is especially true for low-wage and hourly workers.

The situation applies to white-collar jobs too. People applying to be summer interns and first-year analysts at Goldman Sachs have their résumés digitally scanned for keywords that can predict success at the company. And the company has now embraced automated interviewing.

The problem is that automated hiring can create a closed-loop system. Advertisements created by algorithms encourage certain people to send in their résumés. After the résumés have undergone automated culling, a lucky few are hired and then subjected to automated evaluation, the results of which are looped back to establish criteria for future job advertisements and selections. This system operates with no transparency or accountability built in to check that the criteria are fair to all job applicants.