The past decade has seen significant advancements in how candidates are evaluated for employment positions, with a number of innovative methods being developed that take advantage of technologies such as artificial intelligence and machine learning. While these tools can transform candidate experiences and make them more engaging and immersive, they can also pose novel risks and exacerbate bias and discrimination if the appropriate safeguards and mitigations are not in place.

As such lawmakers, particularly in the US, are increasingly proposing laws seeking to impose requirements for the use of so-called automated employment decision tools (AEDTs). The first law of its kind to do this was New York City Local Law 144, which imposed bias audit requirements for AEDTs, but other states have since followed suit. In this blog post, we give an overview of how New York City set the president for AEDT bias audits and examine some of the U.S. states following in the footsteps of New York City.