Program Details

Can We Trust Artificial Intelligence? Understanding FATE in AI

Instructor
Oge Marques
Category
Science / Current Events
FPL12081
Video Catch-up
Available

Course Description

Advancements in artificial intelligence (AI) have impacted every aspect of human life, such as medical diagnosis, credit analysis, and movie recommendations, to name just a few. Along with the speed and intensity at which the technical advancements reach the headlines, there are growing concerns about the social, ethical, economic, and philosophical facets of AI. This program will discuss several crucial non-technical dimensions of AI, which are often grouped in the FATE (Fairness, Accountability, Transparency, and Ethics) acronym. After providing a brief introduction to AI, we will cover some of the most important aspects of FATE in AI and address some of the most frequently asked questions, such as, how can we minimize bias in AI-based decision systems? Who should be held accountable when an AI makes mistakes? Should we adopt AI solutions that produce decisions without explaining them? Adopting a balanced approach and using a rich set of examples, Marques will broaden your view of the field of AI and allow a better understanding of its implications for many aspects of our lives.
 


About the Instructor

  • Oge Marques, Ph.D. is a professor of computer science and engineering at Florida Atlantic University. He is a world-renowned expert in the fields of image processing, computer vision, human vision, artificial intelligence (AI), and machine learning. His current research focuses on applying AI to healthcare. He is the author of 11 technical books, one patent, and more than 150 scientific articles in his fields of expertise. Marques is a Sigma Xi Distinguished Lecturer and a fellow of the AAAS Leshner Leadership Institute. He has won several awards, including the Engineers’ Council John J. Guarrera Engineering Educator of the Year Award, (2019) and the FAU Excellence and Innovation in Undergraduate Teaching Award, (2018, 2011, 2004).