With the arrival of the holiday season, you’ve likely been bombarded with customized coupons and gift recommendations designed to steer you to products and services you’re most inclined to buy. Retailers and free service providers, like Facebook and Google, reap revenue with these highly curated and targeted advertisements – but at the cost of your private data.
The increase in consumer privacy violations motivated Arizona State University Associate Professor Lalitha Sankar to develop game theoretic models retailers and service providers can use to help them generate accurate recommendations while guaranteeing consumer privacy.
“Recommendation systems are everywhere,” says Sankar, an electrical engineer in the faculty of ASU’s Ira A. Fulton Schools of Engineering. “How can these systems make recommendations without knowing who you are? Should they know your political preferences? I think some of it is inevitable, but where should we draw the line?”