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EEOC backs away from disparate impact theory in hiring algorithm case

The EEOC has withdrawn a key allegation in a lawsuit claiming that a company’s AI-based hiring tool caused disparate impact discrimination against older job applicants.

The remaining claims focus on disparate treatment, defined as the intentional exclusion of applicants based on age.

The agency had initially accused iTutorGroup of using an algorithm that screened out older candidates, citing over 200 instances of rejection for applicants over 55.

But the EEOC has now amended its complaint to drop the broader impact-based claim, a move that surprised many observers given its potential implications for AI-driven HR practices.

The shift could signal a more cautious approach from the agency in how it frames enforcement involving hiring algorithms.

Rather than pushing for systemic reform, the EEOC may prioritize cases where there’s clear evidence of intentional bias.

As a result, companies should stay alert to how automated systems might reflect or encode bias, even unintentionally. It is worth considering an internal audit of applicant screening tools, especially those built or trained on third-party data. It is also important to recognize that even without a disparate impact claim, intentional bias, if proven, is still a major legal risk.