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  • Before the 1970s, people looking for jobs in the US would open up thehelp wanted

  • section of their newspapers and see this. One set of opportunities for women, and one

  • for menWe don't see job ads like this anymore,

  • largely because it's been illegal for decadesBut also because advertising is now much more

  • targeted. Instead of one classified page, we have our social feeds, each crafted by

  • algorithms for an audience of oneSo when this ad went out on Facebook and reached

  • a group of people that was 91% men, those outside that audience probably didn't know

  • it existed. And the same goes for this ad, which Facebook

  • displayed for an audience that was 88% womenThat disparity wasn't because the advertiser

  • told Facebook to target users by gender. I know that because this is the advertiser.

  • My name is Muhammad Ali, I go by Ali. He's part of a research group at Northeastern

  • University that has spent thousands of dollars buying ads to try to figure out who Facebook

  • will show them to, and why.

  • If an ad shows up on your Facebook or Instagram

  • feed, there are two parties that decided you should see it. First, the advertiser included

  • you in their target audienceeither by uploading a list of specific email addresses, phone

  • numbers, or previous visitors to their website, Or by choosing from thousands of attributes

  • that facebook offers, like Californians, under 40 who like basketball.

  • Second, Facebook decided who in that pool would actually see the ad through an automated

  • calculation based in part on what they know about you.

  • It's that second step that Ali and his colleagues wanted to study. If they uploaded a list of

  • randomly-generated American phone numbers, and then turned off all the targeting except

  • adults in the US, who would Facebook deliver the ad to?

  • So you set up a bodybuilding ad and a cosmetic ad and said we don't wanna target this any

  • further than the random phone numbers that we put in. Right? And then what were your

  • results? When Facebook started telling you who was actually seeing this ad, what did

  • they tell you? So, yeah, immediately, like we sort of expected

  • that the body building ad was more relevant to men. And that's exactly what we saw. I

  • think somewhere close to 80 to 85 percent of the audience was just men.

  • And the link that we advertise to elle.com about the makeup kits that you could buy that

  • went primarily to women. They were able to collect the results of the

  • ads over time so they knew the gender skew was there early on, suggesting that it wasn't

  • introduced by user behavior. Their experiment showed that Facebook automatically

  • analyzes the content of an ad to compare it to a user's interests.

  • How do they know what the user cares about? Well they have data from your profile and

  • everything you and your friends have done on facebook and instagram, as well as websites

  • you've visited, things you've purchased, apps you've installed, your location, your

  • devices, and moreAll this information fuels automated predictions

  • about whether you are likely to engage with any given ad. And that prediction influences

  • whether the ad shows up on your feed at all. You can get a sense of what Facebook thinks

  • you're interested in on your Ad Preferences page. Or your Ad Interests on instagram.

  • Notice how some of these interests could correlate with your gender, your age, your income level,

  • or your race. And then you wanted to look at race. But it

  • sounds like Facebook does not give you data on the race of people that are seeing an ad.

  • So how do you study that? That was one of the harder things to do. We

  • thought we could use a different custom audience. Instead of random phone numbers. We could

  • take voter records from North Carolina, which are public, and they have the race of the

  • person registered as well. Then they bought ads for Rolling Stone articles

  • that were either about country albums, hip hop albums, or general top 30 albums and targeted

  • an equal number of white and Black users. And it was surprising how much the skew to

  • the Black users was for the hip bag versus the country and the top 30.

  • Facebook's algorithms are trained to not show people ads they won't be interested

  • inBut there may be cases when we're not comfortable

  • with Facebook making those predictions. One study by Ali and his colleagues investigated

  • how this plays out with political ads and found that despite targeting the same audiences,

  • using the same goal, bidding strategy, and budget,

  • an ad pointing to Bernie Sanders' site went to mostly Democrats and an ad for Trump went

  • to mostly RepublicansIt cost 1.5 times more for an ad linking to

  • Sanders' site to reach the same number of conservatives as a Trump ad. Because Facebook

  • subsidizes what they consider to berelevantads.

  • And then we move on to housing and employment ads, and these are considered sort of a different

  • category. Why is that? Because these are legally protected. For example, housing ads are protected by

  • the Fair Housing Act. An advertiser cannot discriminate in those

  • cases. At that point, you're excluding someone from a life opportunity which becomes much

  • more problematic. Because it's actually a legal violation that's

  • at stake? Possibly? Possibly.

  • Facebook allows advertisers to exclude certain ethnic groups from seeing an ad.

  • Dozens of employers placing job ads on Facebook that discriminate against older workers.

  • Facebook is revamping its targeted advertisements after settling lawsuits with civil rights

  • groups. In response to criticism and several lawsuits,

  • Facebook has been removing some of the targeting attributes that an advertiser could use to

  • discriminate against demographic groups, and is paying special attention to ads related

  • to employment, housing, and creditBut the role that the ad delivery system plays

  • remains unsolved. When Ali and his team tested out ads for job

  • openings in different industries, without targeting any demographic groups, facebook

  • generated some skewed audiences. The lumber industry post went to mostly men. The cleaner

  • post went to mostly women. The taxi driver ads that we ran, basically

  • seventy five percent of the audience was black users.

  • These results don't mean that Facebook is directly basing their predictions on our gender

  • or race. Instead it looks for patterns in all of our user data.

  • Maybe people who shop at a men's clothing site and like joe rogan are less likely to

  • click on an ad for a job teaching preschool. Maybe your data is similar to theirs and so

  • they predict you also wont click on that ad either.

  • Instead they show it to someone who likes skincare and feminism. And if that person

  • clicks, the system gets a new data point affirming its prediction.

  • A complaint filed by the US Department of Housing and Urban Development states that

  • this processinevitably recreates groupings defined by their protected class.” They

  • said that Facebook's ad delivery systemprevents advertisers who want to reach

  • a broad audience of users from doing so.” According to a report by ProPublica, a construction

  • workers' union wanted to recruit diverse candidates for its apprenticeship program,

  • so they created ads featuring women, but found that Facebook still showed its them to mostly men.

  • And wouldn't any ad targeting system with

  • sort of sufficiently rich data about people have this kind of effect?

  • Well, we believe so, because a lot of these things, for example, custom audiences on all

  • of these targeting features --they're industry practice. They that also in Google's or Linkedin's or

  • Twitter's advertising platform. So the general ethos of how these systems work is the same.

  • It's a question that the industry as a whole hasn't answered:

  • When exactly is it unacceptable for an algorithm to decide that relevant audiences

  • are segregated ones?

Before the 1970s, people looking for jobs in the US would open up thehelp wanted

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B1 Vox ad facebook advertiser targeting ali

Facebook showed this ad to 95% women. Is that a problem?

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    林宜悉 posted on 2020/07/31
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