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Congress’ Anti-Tech Bills Will Not Prevent Algorithmic Harm to Consumers

  • February 7, 2022

A new report from the Progressive Policy Institute (PPI) explains how the ubiquity of algorithms and their ever-expanding sophistication often come at a cost to consumers and the public at large. And Congressional proposals to break up Big Tech companies, rather than address the root causes of “algorithmic harm,” represent a solution in search of a problem — not a sober assessment of this highly problematic phenomenon. The report, “Breaking Up Big Tech Will Not Prevent Algorithmic Harm to Society,” is authored by Dr. Kalinda Ukanwa, Assistant Professor of Marketing at the University of Southern California’s Marshall School of Business.

“This paper argues that forcing Big Tech companies to sell parts of their businesses will not prevent algorithms at large from circulating extremist, incendiary, and other harmful content,” writes Dr. Ukanwa. “Algorithms are everywhere, and they all operate on the same two guiding principles. To attack the algorithm problem at its roots, society must implement policy that applies to all algorithms.”

Although the way in which algorithms circulate content may not appear problematic at first glance, as Dr. Ukanwa explains, the patterns of recycling and amplifying content categories that typify them are what create echo chambers, often to harmful effect. In service of their main objective — increased engagement and greater profits for developers — algorithms can promote everything from biased understandings of societal concepts to blatantly harmful content.

The report concludes that current bills proposed in Congress are ill-equipped to protect consumers from algorithmic harm because they fail to take into account algorithmic design principles and the wide-ranging nature of algorithmic activity.

Read the full paper and expanded conclusion here:

 

Dr. Kalinda Ukanwa is an Assistant Professor of Marketing at the University of Southern California’s Marshall School of Business. A quantitative modeler, Professor Ukanwa researches how algorithmic bias, algorithmic decision-making, and consumer reputations impact firms. She is the winner of the 2018 Eli Jones Promising Young Scholar Award and a finalist for the 2018 INFORMS Service Science Best Student Paper Award, 2019 Howard/ AMA Doctoral Dissertation Award, and the 2020 AMS Mary Kay Doctoral Dissertation Award.

The Progressive Policy Institute (PPI) is a catalyst for policy innovation and political reform based in Washington, D.C. Its mission is to create radically pragmatic ideas for moving America beyond ideological and partisan deadlock. Learn more about PPI by visiting progressivepolicy.org.

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