Have you ever noticed the faces in Facebook ads seem to match your gender, race or age? That isn’t an accident, Northeastern computer science researchers say.
Have you ever noticed the faces in Facebook ads seem to match your gender, race or age? That isn’t an accident, Northeastern computer science researchers say.
A new paper published by a group of researchers from Northeastern’s Khoury College of Computer Sciences found that Facebook’s algorithm delivers advertisements differently based on who is pictured in the ad.
“When you choose to include a picture of a Black person, that will significantly make it more likely the ad will be delivered to Black users,” says Alan Mislove, professor and senior associate dean for academic affairs in Khoury and one of the authors of the research. “When you choose to include a picture of a woman versus a man, in general it will go more to women, except images of young women, which go more to older men.”
Discriminatory advertising is well-documented on Facebook. In June, the U.S. Department of Justice secured a settlement agreement after charging Meta with algorithmic bias for its housing advertisement delivery system. The paper itself is part of a broader focus on algorithmic auditing and ad delivery for Mislove, who co-authored the paper with Khoury associate research scientist Piotr Sapiezynski, Ph.D. candidate Levi Kaplan and third-year cybersecurity student Nicole Gerzon.
The researchers’ previous work showed how problematic Facebook’s ad delivery system was, skewing ad delivery along largely demographic lines. Job ads in the lumber industry are delivered disproportionately to white men, while jobs for janitorial positions go disproportionately to Black women, according to Mislove.
Mislove says this often happens independent of what advertisers have told Facebook’s ad delivery system. The way it works is advertisers upload their ad to Facebook and then specify their targeted audience, such as 18- to 35-year-olds in Boston.
“That’s a big population,” Mislove says.
