Apple co-founder Steve Wozniak among those claiming they received higher limits than their spouses despite linked finances
Goldman Sachs foray into credit cards in partnership with Apple, has sparked allegations that its AI-powered credit scoring system has gender bias.
Over the weekend, Bloomberg reported an allegation from technology firm executive David Heinemeier Hansson that he has been given a Goldman Sachs-issued Apple credit card with a limit 20 times that of his wife despite her having a higher credit score than he has.
Hansson later told Bloomberg that he did not believe Goldman Sachs’ intent was gender bias but that it was the outcome as a result of “delegating credit assessment to a black box.”
Apple co-founder Steve Wozniak joined the conversation on Twitter saying that he and his wife has also been given vastly different credit limits despite having “no separate bank or credit card accounts or any separate assets.”
The same thing happened to us. We have no separate bank accounts or credit cards or assets of any kind. We both have the same high limits on our cards, including our AmEx Centurion card. But 10x on the Apple Card.
— Steve Wozniak (@stevewoz) November 10, 2019
The allegations prompted a response from a spokesman for Linda Lacewell, the superintendent of the New York Department of Financial Services, who told Bloomberg:
“The department will be conducting an investigation to determine whether New York law was violated and ensure all consumers are treated equally regardless of sex. Any algorithm, that intentionally or not results in discriminatory treatment of women or any other protected class of people violates New York law.”
No bias says Goldman
A spokesman for Goldman Sachs told Bloomberg that its credit scoring systems are not biased.
“Our credit decisions are based on a customer’s creditworthiness and not on factors like gender, race, age, sexual orientation or any other basis prohibited by law,” said Andrew Williams.
The issue is likely to fuel further debate among the financial services sector as the use of AI/machine learning in credit assessment increases.
