Computer science professor Tina Eliassi-Rad says she’s proud to be named on an industry list of “100 Brilliant Women in AI Ethics,” which identifies her as one of the top thinkers in the male-dominated field of artificial intelligence. But she’s even prouder of what the carefully-curated list represents.
“Part of the issue in a field such as computer science is that women and other under-represented minorities aren’t always seen. Initiatives like this one show that there are a lot of women who are qualified to do this work,” says Eliassi-Rad.
Mia Shah-Dand, the CEO of the Oakland, California-based research firm Lighthouse3, created the annual list in 2018. Shah-Dand says she wanted to provide a rebuttal to technology leaders who complained that they couldn’t find accomplished, diverse women to hire.
“I was a little frustrated with all the times I would hear, ‘There just aren’t enough qualified women,’” says Shah-Dand. “It’s the same old excuse. Well, we have an entire directory of qualified women now. There is no excuse. At this point in 2021, if you have only men on your staff, it’s intentional.”
According to recent research by the World Economic Forum, women hold only 26% of data and artificial intelligence jobs across the globe, and even fewer have senior roles.
Shah-Dand says she included Eliassi-Rad on her 2021 list because of the professor’s extensive research on racial, gender and other baked-in biases in artificial intelligence algorithms.
“Her emphasis on algorithmic accountability and fairness was particularly interesting,” says Shah-Dand.
Algorithms, which scan large amounts of data and find whatever information its creators want, are increasingly part of our everyday lives. For example, credit card fraud departments use algorithms to detect abnormal spending, while social media algorithms use viewer interests to determine which ads to run.
Eliassi-Rad’s research at Northeastern focuses on the unseen but overwhelming influence that artificial intelligence algorithms can make in people’s lives, especially in social media.
“Part of the problem with algorithms is that they can impact life-altering decisions if they’re used in criminal justice or even your credit score,” says Eliassi-Rad. Microlenders, or individuals who issue small loans, will often check a candidate’s Facebook and Twitter feeds when deciding whether to grant a loan. A chance connection with someone who has defaulted on a loan could trigger a denial, says Eliassi-Rad.
“Sometimes if you don’t get the right loan in life, you can’t better yourself,” she says.
Eliassi-Rad’s career in computer science was sparked by her father’s early work with autonomous vehicles. She avidly read the many magazines he brought home and decided computer science was the perfect balance between math and electrical engineering. Her focus recently sharpened as she learned about the different class, race, and gender biases in machine learning.
She likens the data used in algorithms to an iconic photo of a police officer’s German shepherd attacking a Black high school student during a 1963 civil rights event in Birmingham, Alabama.
“The German shepherd isn’t racist, it’s the people teaching the dog,” Eliassi-Rad says. Even if the data used in an algorithm isn’t biased, the algorithm may still produce biased findings.
“As you are developing an algorithm you are making choices, and those choices have consequences,” Eliassi-Rad says.
Eliassi-Rad and Shah-Dand say the list of top women in AI ethics does more than provide a roster of qualified computer science professionals who also happen to be female, LGTBQ, or women of color. It creates a community to foster networking and support while providing role models for future generations.
“It’s sort of like a sisterhood,” says Eliassi-Rad, who received an Outstanding Mentor Award from the Office of Science at the US Department of Energy in 2010. “I hope young women see this and think, ‘I can be somebody like this person.’”
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