Building Human-Centric Machine Learning Solutions

With the increasing advancement of AI and ML technologies comes the understanding that our current relationship with AI is deeply shaped by our society’s historical experience with technology. In this course, AI engineers will gain the skills to design human-centered AI experiences using human-focused science. Learn how to deploy techniques from social science to tackle cognitive gaps and fallacies when building effective computing platforms. Through case studies, practical tips and design anthropology exercises, you observe how anthropology and ML can add a new dimension to AI.

Lead Instructor: Alexander I. Iliev, Ph.D., earned his doctorate from the College of Engineering at the University of Miami (UM) in 2009. He holds two patents in the Digital Audio Watermarking and Data Enhancement fields. Dr. Iliev’s research interests are in the fields of Big Data analytics, signal processing, personalization using speech and image signals, AI, ML and data mining.

Expert Speaker: Ali Rebaie, B.S., is a data anthropologist, industry analyst and global keynote speaker. He is also the president of Rebaie Analytics Group. As a data anthropologist, Ali studies social trends and ideological changes in societies and understands our ancestors’ cognitive and cultural evolution to help stage emotional human experiences and human-centric AI. Ali is excited about helping companies use AI to lantern customer experience while understanding the “why” of human experience.