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Writer's pictureAJ SK

Facebook Ads management: Did it help?

Earlier this year, Facebook promised to change the way it manages the advertisements for housing, employment, and credit that run on its platform. It claimed these changes to be the result of historic settlement agreements with leading civil rights organisations and ongoing input from civil rights experts. However, a research by a team of computer scientists found that the algorithm Facebook uses to deliver advertisements can still skew toward specific demographic groups despite the changes the company made. The team had Alan Mislove, a professor of computer science at Northeastern University.

Mislove worked with a team of researchers including Northeastern doctoral candidates Piotr Sapiezynski and Avijit Ghosh, undergraduate student Levi Kaplan. According to Mislove, removing the ability of advertisers to specifically target people by race, gender, and age should result in advertising audiences that include a diverse mix of people. In practice, Facebook’s algorithm relies on a myriad of other characteristics about its users that ultimately serve as proxies for race, gender, and age. The team used voter data to create audiences that were intentionally biased by race, gender, age, and political views. These were publicly available. They then fed them to both the new and existing advertising tools to test whether the corresponding algorithm would reproduce each bias. They found that both Lookalike and Special Ad audiences replicated the demographic skews. Mislove believes that the results illustrate the difficult task of ensuring fairness in algorithms. In practice, an algorithm is given millions of inputs, each one of which is correlated in other ways to these protected features. Algorithms don’t care. They have a specific objective and they’re going to use the combination of features that will result in completing that objective

“It’s very hard right now, in the sense that the protected identities really permeate our society. It’s going to be much harder and much more subtle than simply removing certain features at the outset”, Mislove says.

Shahjadi Jemim Rahman

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