Professor Ali Makhdoumi designed a data acquisition mechanism that maximizes platforms' utility while compensating privacy-sensitive users
As platforms learn details about users’ preferences and characteristics, the risk is that they use those data points to enable price discrimination and other manipulations useful for them and harmful for users
Image: Shutterstock
The rise of artificial intelligence and machine learning is increasing the demand for data from app users, device owners, firms, consumers, and even patients.
As data-hungry technologies are getting more and more efficient, the key question is how to incentivize data-sharing while protecting users’ privacy, said Ali Makhdoumi, an associate professor of decision sciences at Duke University’s Fuqua School of Business.
[This article has been reproduced with permission from Duke University's Fuqua School of Business. This piece originally appeared on Duke Fuqua Insights]