10 Practical Steps Employers Should Take to Mitigate AI Bias and Manage Workplace Risk
Artificial intelligence has become increasingly embedded in hiring, promotion, and employee management, which means that employers face heightened legal risks. From automated résumé screening to video interview tools and performance analytics, AI tools can amplify bias, create disparate impact, and expose organizations to regulatory scrutiny. Below are 10 practical steps you should consider to mitigate bias and manage risk throughout the AI employment lifecycle. 1. Validate Before You Deploy Before rolling out any AI tool, conduct rigorous pre-deployment testing. This includes bias and disparate-impact audits across protected groups (race, sex, age, disability) and job categories . Require vendors to provide documentation of their own testing, accuracy data, and bias audit results. Don’t assume a high statistical correlation between a model’s features and job performance means the tool is job-relevant. Always ask if the features logically relate to actual job duties. 2. Monitor Ou...