University of Southern California researchers who examined
the ad-delivery algorithms of Facebook and LinkedIn found that Facebook’s were
skewed by gender beyond what can be legally justified by differences in job
qualifications.
Men were more likely to see Domino’s pizza delivery driver
job ads on Facebook, while women were more likely to see Instacart shopper ads.
The trend also held in higher-paying engineering jobs at
tech firms like Netflix and chipmaker Nvidia. A higher fraction of women saw
the Netflix ads than the Nvidia ads, which parallels the gender breakdown in
each company's workforce.
No evidence was found of similar bias in the job ads
delivered by LinkedIn.
Study author Aleksandra Korolova, an assistant professor of
computer science at USC, said it might be that LinkedIn is doing a better job
at deliberately tamping down bias, or it might be that Facebook is simply
better at picking up real-world cues from its users about gender imbalances and
perpetuating them.
“It’s not that the user is saying, ‘Oh, I’m interested in
this.’ Facebook has decided on behalf of the user whether they are likely to
engage," she said. "And just because historically a certain group wasn’t
interested in engaging in something, doesn’t mean they shouldn’t have an
opportunity to pursue it, especially in the job category.”
Facebook said in a statement Friday it has been taking
meaningful steps to address issues of discrimination in ads.
“Our system takes into account many signals to try and serve
people ads they will be most interested in, but we understand the concerns
raised in the report," it said.
Facebook promised to overhaul its ad targeting system in
2019 as part of a legal settlement.
The social network said then it would no longer allow
housing, employment or credit ads that target people by age, gender or zip
code. It also limited other targeting options so these ads don’t exclude people
on the basis of race, ethnicity and other legally protected categories in the
U.S., including national origin and sexual orientation.
Endlessly customizable ad targeting is Facebook’s bread and
butter, so any limits placed on its process could hurt the company's revenue.
The ads users see can be tailored down to the most granular details — not just
where people live and what websites they visited recently, but whether they’ve
gotten engaged in the past six months or share characteristics with people who
have recently bought new sneakers, even if they have never expressed interest
in doing so themselves.
But even if advertisers can’t do the targeting themselves,
the study shows what critics have stressed for years -- that Facebook’s own
algorithms can discriminate, even if there is no intent from the job
advertisers themselves.
“We haven’t seen any public evidence that they are working
on the issues related to their algorithms creating discrimination,” Korolova
said.
Since it isn't possible to show every user every
advertisement that is targeted at them, Facebook's software picks what it deems
relevant. If more women show interest in certain jobs, the software learns it
should show women more of these sorts of ads.
LinkedIn said the study's findings align with its internal
review of job ads targeting.
“However, we recognize that systemic change takes time, and
we are at the beginning of a very long journey," the company said in a
statement.
U.S. laws allow for ads to be targeted based on
qualifications but not on protected categories such as race, gender and age.
But anti-discrimination laws are largely complaint-driven, and no one can
complain about being deprived of a job opportunity if they didn't know it
happened to them, said Sandra Wachter, a professor at Oxford University focused
on technology law.
“The tools we have developed to prevent discrimination had a
human perpetrator in mind,” said Wachter, who was not involved in the USC
study. “An algorithm is discriminating very differently, grouping people
differently and doing it in a very subtle way. Algorithms discriminate behind
your back, basically."
While Domino's and Instacart have similar job requirements
for their drivers, Domino's delivery workforce is predominantly male, while
Instacart's is more than half female. The study, which looked at driver ads run
in North Carolina compared to demographic data from voter records, found that
Facebook's algorithms appeared to be learning from those gender disparities and
perpetuating them.
The same trend also occurred with sales jobs at retailer
Reeds Jewelers, which more women saw, and the Leith Automotive dealership,
which more men saw.
The researchers call for more rigorous auditing of such
algorithms and to look at other factors such as racial bias. Korolova said
external audits such as the USC study can only do so much without getting
access to Facebook’s proprietary algorithms, but regulators could require some
form of independent review to check for discrimination.
“We’ve seen that platforms are not so good at self-policing
their algorithms for undesired societal consequences, especially when their
business is at stake,” she said.
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