FTC Keeps Pressure on Data Privacy Issues with Thursday Event

Researchers Will Discuss Mobile Ads, Ad Targeting Discrimination and More

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The Federal Trade Commission is examining whether online data collection and ad targeting can inadvertently lead to discrimination.
The Federal Trade Commission is examining whether online data collection and ad targeting can inadvertently lead to discrimination. Credit: FTC

If the last two weeks are any indication, data analytics and related privacy issues will take center stage at the Federal Trade Commission this year. On Thursday the agency will make it second move of 2016 that's focused on the use of data and privacy.

The all-day PrivacyCon in Washington, D.C., will feature a range of speakers, many from the world of academia, presenting their latest research on topics including extensive storage of web user data, mobile advertising data, standards for consumer control over data and how Google privacy settings affect ad targeting and could result in discrimination.

FTC Chairwoman Edith Ramirez, Commissioner Julie Brill and Chief Technologist Lorrie Cranor will all speak at the event, which will be livestreamed. The event follows the release of the "Big Data: A Tool for Inclusion or Exclusion?" report last week.

Annenberg School for Communication Professor of Communication Joseph Turow, a longtime critic of digital data collection and ad targeting, will share recent research showing that "marketers are misrepresenting a large majority of Americans by claiming that Americans give out information about themselves as a tradeoff for benefits they receive," according to a paper submitted to the FTC for the event.

Researchers from University of California, Berkeley and Carnegie Mellon University will present a study exploring how user settings and interactions with websites affect ad content and targeting. In one example, they found evidence suggesting that changes made to Google's Ad Settings resulted in different ads being presented based on gender. The research paper says, for example:

The interesting result was how the ads differed between the groups: during this experiment, Google showed the simulated males ads from a certain career coaching agency that promised large salaries more frequently than the simulated females, a finding suggestive of discrimination.

The agency has already devoted significant resources to the potential for discrimination resulting from data analysis. Its "Big Data: A Tool for Inclusion or Exclusion?" report last week, which followed a workshop on the subject last year, warned companies that algorithms may require specific human supervision to avoid discrimination affecting areas such as health, credit, and employment. With examples such as the ones that will be presented during the event tomorrow, don't expect the issue to go away.

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