Michael McLaughlin is a research analyst at the Information Technology and Innovation Foundation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.
A close look at data from a new NIST report reveals that the best facial recognition algorithms in the world are highly accurate and have vanishingly small differences in their rates of false-positive or false-negative readings across demographic groups.