<
https://www.geekwire.com/2024/ai-overwhelmingly-prefers-white-and-male-job-candidates-in-new-test-of-resume-screening-bias/>
"As employers increasingly use digital tools to process job applications, a new
study from the University of Washington highlights the potential for
significant racial and gender bias when using AI to screen resumes.
The UW researchers tested three open-source, large language models (LLMs) and
found they favored resumes from white-associated names 85% of the time, and
female-associated names 11% of the time. Over the 3 million job, race and
gender combinations tested, Black men fared the worst with the models
preferring other candidates nearly 100% of the time.
Why do machines have such a outsized bias for picking white male job
candidates? The answer is a digital take on the old adage “you are what you
eat.”
“These groups have existing privileges in society that show up in training
data, [the] model learns from that training data, and then either reproduces or
amplifies the exact same patterns in its own decision-making tasks,” said Kyra
Wilson, a doctoral student at the UW’s Information School.
Wilson conducted the research with Aylin Caliskan, a UW assistant professor in
the iSchool. They presented their results last week at the AAAI/ACM Conference
on Artificial Intelligence, Ethics and Society in San Jose, Calif.
The experiment used 554 resumes and 571 job descriptions taken from real-world
documents.
The researchers then altered the resumes, swapping in 120 first names generally
associated with people who are male, female, Black and/or white. Nothing else
in the resumes changed — such as experience, college degrees, etc. So when the
AI selected a white male candidate over a Black male candidate, the only
difference in the resume was the name associated with it; every other factor
was identical.
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."
Via Esther Schindler.
Cheers,
*** Xanni ***
--
mailto:xanni@xanadu.net Andrew Pam
http://xanadu.com.au/ Chief Scientist, Xanadu
https://glasswings.com.au/ Partner, Glass Wings
https://sericyb.com.au/ Manager, Serious Cybernetics
