Companies like Netflix and Hulu compete for subscribers to make sure their businesses thrive. But there’s another type of competition at work that receives far less attention – the competition among the machine learning algorithms used by these kinds of competitor companies.
James Zou, Stanford assistant professor of biomedical data science and an affiliated faculty member of the Stanford Institute for Human-Centered Artificial Intelligence, says that as algorithms compete for clicks and the associated user data, they become more specialized for subpopulations that gravitate to their sites. And that, he finds in a new paper with graduate student Antonio Ginart and undergraduate Eva Zhang, can have serious implications for both companies and consumers.
The study co-author, Antonio Ginart, is a 2017 EDGE fellow and 2019 Stanford Interdisciplinary Graduate Fellow.