The Mah Jongg Problem: Why Smart People Follow Bad AI Advice - and What Boards Need to Do About It
This article highlights the 'Mah Jongg Problem,' where individuals, even those with expertise, tend to defer to AI suggestions, often without critical evaluation, simply because the AI presents information confidently. This behavioral bias, termed automation bias, poses significant governance challenges for organizations, as it can lead to decisions that are not truly owned by human judgment, creating accountability gaps and potential legal liabilities, as exemplified by the UnitedHealth case. Internal audit and assurance professionals should recognize this phenomenon as a critical risk in AI adoption, requiring robust governance frameworks that emphasize human oversight and accountability.