Miguel Afonso Caetano"The experiment used 554 resumes and 571 job descriptions taken from real-world documents.
The researchers then doctored the resumes, swapping in 120 first names generally associated with people who are male, female, Black and/or white. The jobs included were chief executive, marketing and sales manager, miscellaneous manager, human resources worker, accountant and auditor, miscellaneous engineer, secondary school teacher, designer, and miscellaneous sales and related worker.
The results demonstrated gender and race bias, said Wilson, as well as intersectional bias when gender and race are combined.
One surprising result: the technology preferred white men even for roles that employment data show are more commonly held by women, such as HR workers.
This is just the latest study to reveal troubling biases with AI models — and how to fix them is “a huge, open question,” Wilson said.
It’s difficult for researchers to probe commercial models as most are proprietary black boxes, she said. And companies don’t have to disclose patterns or biases in their results, creating a void of information around the problem."
Kevin Karhan 
Misuse Case
Cassandrich
Jeremy List