Goldman Sachs was cleared of gender bias in Apple Card credit limits, but the investigation cost them the entire consumer lending business.
A tech entrepreneur received a credit limit 20x higher than his wife’s despite shared assets and her higher credit score. Steve Wozniak reported a similar experience. NY DFS investigated nearly 400,000 applicants and found no intentional discrimination. But the reputational damage and regulatory scrutiny contributed to Goldman exiting consumer lending entirely. The algorithm didn’t use gender directly but used inputs that correlated with gender in ways nobody independently evaluated before deployment.
disparity
investigated
consumer lending
Even a cleared investigation can destroy a business line. AVAAS causal attribution would have identified which input variables correlated with gender before the algorithm reached production, giving Goldman the evidence to either fix it or defend it proactively.
This entry is one of 37 documented cases in the AVAAS evidence ledger, a public record of AI and automated-system failures with a verified source on every entry.
Every case here reached a person.
AVAAS certifies how AI systems behave at the decision point, with documented third-party evidence of conformity to a published standard.
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