Compliance Stuff

On June 9, 2026, the U.S. Department of Justice (DOJ) issued a significant legal opinion concluding that the Equal Employment Opportunity Commission’s (EEOC) longstanding interpretation of Title VII disparate impact liability is unconstitutional. The opinion questions aspects of the Uniform Guidelines on Employee Selection Procedures (UGESP), the federal framework that has guided employers’ validation of employment tests and selection procedures for nearly 50 years. While the DOJ opinion does not change Title VII itself and is not binding on federal courts, it signals a potentially significant shift in federal enforcement priorities and creates new uncertainty for employers. For HR, compliance, legal, and talent acquisition professionals, the key question is straightforward: Should employers change how they evaluate seemingly neutral employment practices, including tests and other selection procedures? At least for now, the answer is generally no. A Brief Refresher: Disparate Impact an...

Employers are increasingly using artificial intelligence and other algorithmic tools to support workplace decisions, including recruiting, screening, interviewing, promotion, workforce planning, and performance management. These tools can improve efficiency and consistency, but they also introduce important compliance, reputational, and employee-relations considerations. Two concepts that often arise in AI governance are bias audits and validation testing. Although related, they serve different purposes. A bias audit generally evaluates whether the use of a tool is associated with materially different outcomes across protected or demographic groups. Depending on the jurisdiction and the tool at issue, a bias audit may be legally required before use. For example, New York City’s automated employment decision tool law requires certain employers and employment agencies to obtain a bias audit within one year before using covered tools and to provide related notices and disclosures . And o...

Artificial intelligence has become commonplace in recruiting, screening, interviewing, testing, promotion, and employee monitoring. Properly designed and governed, AI can streamline processes and improve consistency . However, in employment decision-making, AI can introduce legal and operational risks for the employer, even when the AI tools are built and operated by third-party vendors. Businesses should understand where and when liabilities may arise and use vendor contracts to mitigate and allocate those risks before deploying AI as part of employment decisions. Legal Risks in Using AI for Employment Decisions A legal risk in using AI as part of employment decisions is that AI tools can encode or amplify historical bias . Disparate treatment claims can arise where systems use or infer protected characteristics such as age, race, religion, sex, disability, or genetic information—either directly or through proxies like geography or graduation dates. Disparate impact claims can follow ...

Recently, there have been many questions regarding the collection of demographic data from employees and applicants by employers.  Executive Order 14173  and other  executive and agency actions  by the Trump administration have caused organizations to rethink whether information on race/ethnicity and sex should be collected and, if so, under what circumstances. However, record keeping requirements stemming from  Title VII of the Civil Rights Act  (Title VII) and the  Uniform Guidelines on Employee Selection Procedures  (UGESP) to collect demographic information from employees and applicants alike clearly remain, which are further strengthened by precedence in the courts. One such court case is  Equal Employment Opportunity Commission (EEOC) v. Crothall Services Group, Inc (Crothall) . In this case, EEOC alleged that Crothall violated § 709(c) of Title VII and an EEOC recordkeeping guideline, 29 C.F.R. § 1607.4(A) by failing to maintain record...