Emergence of Deep Learning & New AI: The Technology Revolution and Roadblocks

Dr. Jacek M. Zurada
University of Louisville, KY USA
IEEE Life Fellow; International Neural Networks Society Fellow
Member of the Polish Academy of Sciences
Professor of Electrical and Computer Engineering

October 22, 2020,
14.30 - Slovak Time,
8.30 Louisville Time,
20.30 - Beijing Time
21.30 Tokyo Time

Summary: As today’s DL systems can so successfully acquire new knowledge from the environment that even exceed human cognitive and perceptual abilities, they can be considered as endowed with AI. This has led to breakthroughs in image recognition, speech recognition, computer vision, robotics, intelligent interfaces which all are revolutionizing today’s homo sapiens environment. The most useful results of DL/AI are the complex decisions they are able to make. However, they have only little, if any transparency. Therefore, the primary challenge for their designers and users is the assignment of responsibility. These systems, moreover, neither know codes of ethical behaviour or legal norms. Other challenges inherent in autonomous systems are related to the protection of privacy, safety or non-discrimination. These are the challenges of our day, which stand not only against the engineers and computer scientists creating these systems, but with entire societies and nations.

Biosketch: Jacek M. Zurada (M’82-SM’83-F’96-LF’14) serves as a Professor of electrical and computer engineering with the University of Louisville, Louisville, KY, USA. He has authored or co-authored several books and over 450 papers in computational intelligence, neural networks, deep learning, logic rule extraction, and bioinformatics and delivered over 125 presentations throughout the world.
Dr. Zurada has been a Board Member of the IEEE, IEEE CIS, IEEE C&S and of INNS. He was a recipient of the 2013 Joe Desch Innovation Award, the 2015 Distinguished Presidential Service Award, and five honorary professorships. He served as the IEEE V-President and the Technical Activities Board (TAB) Chair in 2014. In 2010-13 he was the Chair of the IEEE Periodicals Committee and the Periodicals Review and Advisory Committee. From 2004 to 2005, he was the President of the IEEE Computational Intelligence Society, and served as the Editor-in-Chief of the IEEE Transactions on Neural Networks (1997-2003) He was a nominee for 2018 and 2019 IEEE President-Elect.

His impact to the field is significant - his papers are cited 14 400 time.

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