Understanding the Impact of Machine Learning on Labor and Education

Joseph Ganem, Ph.D., is a professor of Physics at Loyola University Maryland and the chair of the Loyola Physics Department. He is an author on numerous scientific papers in the fields of optical materials, lasers, and magnetic resonance. He has taught physics in the classroom for more than 25 years and has served on the Maryland State Advisory Council for Gifted and Talented Education. Dr. Ganem is the author of “The Robot Factory: Pseudoscience in Education and Its Threat to American Democracy” and also of the award-winning book “The Two Headed Quarter: How to See Through Deceptive Numbers and Save Money on Everything You Buy.” He speaks and writes frequently on science, consumer, and education issues and has been a contributor of articles on these topics to the Baltimore Sun newspaper. For its 2017 “Best of Baltimore” awards, Baltimore magazine named him one the “Best Baltimoreans” in its people in the media section for the category “Best Defense of Science.” Dr. Ganem earned a Ph.D. from Washington University in Saint Louis, a M.S. from the University of Wisconsin-Madison, and a B.S. from the University of Rochester.

• Introduction: The difference between knowing and learning.- Labor Markets: Comparative learning advantages.- Learning to Work: The two dimensions of job performance.- The Judgment Game: The Turing Test as a general research framework.- The Learning Game: A time-dependent Turing Test.- Implications: Recommendations for future education and labor policies.