Houston, TX

Researchers Propose an AI System That Strikes a Balance Between Privacy Protection and Personalization

Jackson Cutler

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HOUSTON, TX —Frequently, when people encounter "click here" on a web page to verify that they have read, understood, and agreed to the company's privacy and policy statements, it is impossible to determine whether they have actually read, understood, and agreed to the company's privacy and policy statements in their entirety.

Regarding this matter, Paul A. Pavlou, Cullen Distinguished Chair Professor and Dean of the University of Houston C.T. Bauer College of Business acknowledged that most people don't read the policies because there isn't a real choice. "If you decline, you are automatically blocked from going further into the website or app and you cannot conduct the business you need," he continued.

Therefore, Pavlou co-authored an article entitled "Achieving a Balance Between Privacy Protection and Data Collection," recently published in the top journal Information Systems Research.

Pavlou partnered with Bailing Liu and Cheng Xiufeng, two computer scientists with Central China Normal University. They propose an alternative that offers meaningful options for both sides of the transaction.

Initially, this initiative is inspired by the justice theory proposed in 1965 by psychologist John Stacey Adams. They wanted to privacy policy agreements by enabling an artificial intelligence system that links tiers of customer information with levels of personalization offered by providers of products or services.

In the proposed system, customers can have the opportunity to choose which data they want to share. If they decide to share only basic personal details, they can have limited access to a company's website.

On the other hand, personalized products and services offerings await customers who decide to give more information, perhaps including marketing-friendly data such as income, family size, residence type, or lifestyle.

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