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Human-Centered Artificial Intelligence: How to Combine the Best of Humans and Machines

Instructor
Oge Marques
Category
Science
SPL03181
Video Catch-up
Available

Course Description

The success of artificial intelligence (AI) in recent years has led to concerns about the likelihood of AI-powered solutions replacing humans in a multitude of professions, from truck drivers to radiologists. Every field of human activity will likely experience some help from AI, properly mixed with human intervention, due to job requirements that are difficult to address with AI alone, such as creativity, compassion, and common sense. In short, humans and machines will converge and produce solutions that are better than either could produce alone. This lecture will give an overview of human-centered AI, highlight some of the leading efforts in this field of research, and show how algorithms, sensors, and robots can interact with humans in numerous, meaningful ways.

Course Info

  • Time: 10:00 AM - 11:30 AM
  • Date: Friday, March 18
  • Location: Friedberg Auditorium, Lifelong Learning Building
  • Fees: Member - $30
    $75 for any combination of three events, members only
    No Refunds Will be Given for One-Time Events Purchased Within a Discounted Bundle
    Non-member - $35
    One-time guest pass, Member or Non-member at the door - $35.

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).