January 5, 2018

CLTC Grantee Rena Coen Pens Slate Piece on “Inference”

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CLTC Research

“Web of Assumptions,” an article authored by CLTC Grantee Rena Coen for Slate’s Future Tense, focuses on digital marketers’ use of “inference”—connecting data from multiple sources to make probabilistic guesses about consumers’ race, age, gender, and other factors—to personalize prices, search results, and other marketing messages.

“If a company asks you online to provide detailed information about yourself, you might be reluctant to share it,” Coen writes. “So digital marketers have found a workaround: They vacuum up troves of data about internet users to improve their use of inference, the practice of using available information—like behavioral, mobile, and publicly available data—to make informed guesses about consumers. By deducing your race, income, gender, interests, and more, companies can personalize search results, ads, pricing, and other content.”

As Coen explains in the article, marketers benefit from using inference because consumers respond more frequently to personalized ads. Yet such practices can lead to discrimination. As an example, Coen notes how Facebook’s “ethnic affinity” targeting (which used inference to guess users’ ethnicity) was found to be in violation of the Fair Housing Act.

The article is based on a 2016 research study by Coen and colleagues Emily Paul and Pavel Venegas, a survey-based study focused on understanding attitudes about inference and personalization. The research—which was funded by CLTC and the Center for Technology, Society, and Policy—demonstrated that Internet users are largely unaware that companies use inference for personalization, and when they learn about it, they generally disapprove of the practice.

“Out of 748 U.S. internet users surveyed, 58 percent had never or rarely thought about ads targeting them based on their inferred race, and 65 percent found the idea to be unacceptable or somewhat unacceptable,” Coen writes. “Respondents particularly disliked the use of race for personalizing the prices of products, with only 8 percent saying that using their inferred race would be somewhat acceptable or acceptable…. Most web users surveyed don’t like marketing based on their household income level, either, with 67 percent finding this type of targeted ad to be somewhat unacceptable or unacceptable.”

In her piece on Slate, Coen argues that better standards are necessary to curtail the use of customer data for personalization: “Our study suggests that the industry needs new standards to better inform and empower people to protect their personal information. This requires not only allowing users control over what data are collected about them but also what is inferred about them, how those inferences are used, and by whom….If industry can’t find a path to respecting users on its own, users deserve a regulatory hook that can help it to find the way.”

Read the full article on Slate.

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