FOR IMMEDIATE RELEASE
FairGap Publishes Guidance on Model Review Language and Audit Evidence
New articles help boards and counsel separate adverse impact from disparate treatment, and document bias audits for later scrutiny.
August 17, 2026. FairGap today published guidance at fairgap.com for boards, senior compliance counsel, and model-risk owners reviewing AI systems that affect people. The articles focus on language that boards can use without collapsing distinct legal ideas, and on the evidence a bias audit should leave behind for counsel.
The pieces cover adverse impact versus disparate treatment in model review language boards understand, and what evidence a bias audit should leave for counsel. Both are written for readers who expect claims to hold up under hostile questioning.
"Precision is not pedantry in this work," a FairGap representative said. "If the minutes use the wrong term, the remediation plan will chase the wrong problem."
The guidance is free on the FairGap blog. FairGap continues to support independent algorithmic bias audits and model-risk review for regulated AI systems.
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FairGap helps organizations review algorithmic systems for fairness and model risk, with attention to audit scoping, board language, and evidence that counsel can reuse.
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