Participants:

Shareef Farag, Partner, BakerHostetler (LA)James A. Sherer, Partner, BakerHostetler (NY)Ariana Dindiyal, Associate, BakerHostetler (NY)Brittany Yantis, Associate, BakerHostetler (DC)Fulton Wald, Associate, BakerHostetler (NY)

Program outline:

AI is set to affect many disciplines, but its effects carry similar themes.

This presentation discusses AI practice development in the context of job applications according to these themes:

Creation of new information at scale. Present-day job openings are oversaturated with applications, and many HR departments cannot handle the quantity of applications, thus look to AI to help sort through them.

Use of outsourced “black box” technology. As with other AI applications, many HR departments out-source these tools to third party vendors without knowing exactly how the vendors function.

Potential for Bias and back-end audits. Vendors may promote the use of AI not based in science, and/or that relies on biased data sets without self-auditing: this means vendors could be picking candidates who were chosen by biased AI, and the employer might be unaware of this.

New Law. Laws in cities and states have cropped up regarding Automated Employment Decision Tools (AEDT), such as in NYC which now requires employers to disclose when they use AEDT and conduct bias audits to ensure their AI is fair.

Other Legal/Adjacent Standards. “Soft Law” and other similar ethical approaches (e.g., from NIST and the EEOC) can also offer guidance to employers to help avoid lawsuits based on biased AI (or to mitigate their effects).