Catapulting Talent DEI Progress through AI

Diversity, Equity and Inclusion (DEI) workplace initiatives have made significant progress over the last decade to reduce diversity representation gaps relative to the communities in which companies operate. Progress has stalled due to the June 2023 Students for Fair Admission (SFFA) SCOTUS case on college affirmative action and its spillover into corporate DEI initiatives. Activists have challenged programs that confer preferences on protected demographics groups.

At this same juncture, some organizations have stalled in the maturity curve of integrating DEI into the talent life cycle through leaders in the business due to transformation challenges. One obstacle is that humans are inherently prone to bias that is hard to mitigate. The current solution to debias talent decisions is to train humans on how to mitigate their own biases, but this is often expensive and ineffective.

A working hypothesis is that AI powered debiasing tools can lead to increased equity in talent decision-making. The commonplace assumption is that AI will build human biases into systems and accelerate those biases. However, if algorithms, datasets, and models are built using DEI domain expertise, the opposite could also be true. Because AI systems and algorithms can be intentionally designed to mitigate bias, an effort to build a movement led by key influencers leveraging AI to debias decisions could catapult talent DEI progress.