What Machine Learning Can’t Learn | Angie Beasley | TEDxUTAustin

We live in the age of the algorithm, where increasingly more decisions are being handed over to machine learning. And the results of these decisions made by machine learning are affecting both individuals and society. Professor of machine learning Angie Beasley warns us that these automated decisions can increase unfairness and inequity in society when we are not careful about how we use this technology. Angie Beasley is an Assistant Professor of Instruction in the Computer Science department at The University of Texas at Austin, where she teaches both introductory programming and machine learning. She is passionate about getting others interested in and excited about computer science and believes that in today's digital world, every undergraduate degree should include at least one computer science course. Angie enjoys demystifying complex topics like machine learning, as well as discussing both the harmful and the beneficial social impacts of the increasing use of this technology.

Prior to teaching, Angie worked as a software engineer on projects for the US Navy, including submarine and surface ship sonar systems, periscope systems, and unmanned underwater vehicles. Angie received her MS in Computer Science with a concentration in machine learning from The George Washington University and her BS in Computer Science from The University of Texas at Austin. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx