Demystifying Artificial Intelligence, Machine Learning and Deep Learning

Whether we know it or not, artificial intelligence, or AI, in its various forms and sub-domains, is radically transforming almost everything we do, from automated decisions on loan and job applications to facial recognition and autonomous, self-driving vehicles, to student use of ChatGPT in classrooms and assignments. While supervised and unsupervised machine learning, deep learning and neural networks are influencing our entire society in phenomenal ways and providing instant gratification and efficiency to our society, they are simultaneously presenting enormous challenges. Potential bias in the underlying data on which the models are based, the algorithms themselves and the ethical application of AI creates enormous tension. And for many in our society, what does all of this mean anyway? In this talk, Professor Cogburn will attempt to demystify, explain and illustrate the concepts of AI, machine learning and deep learning. He will then discuss the broader implications of these developments for academic librarians and the humanities, and how we confront the present challenges while harnessing the opportunities they portend.

Presented by:

Dr. Derrick L. Cogburn, Full Professor of Information Technology and Analytics and International Communication and Development, American University

Dr. Derrick L. Cogburn is Full Professor of Information Technology and Analytics and International Communication and Development at American University. He holds a joint appointment in the School of International Service and in the Kogod School of Business. He serves as the founding Executive Director of the AU Institute on Disability and Public Policy (IDPP) and founding Faculty Co-Director of the Internet Governance Lab (IGL). He also directs COTELCO the Collaboration Laboratory. Dr. Cogburn edits the book series on Information Technology and Global Governance at Palgrave Macmillan. His multifaceted research interests are located at the intersection of information technology, global governance and socio-economic development. He uses a variety of computational text mining and data analytics approaches including unsupervised and supervised machine learning and artificial intelligence methodologies to better understand large-scale, text-based datasets in the areas of cybersecurity, disability policy and distributed collaboration in knowledge work. He holds a PhD in political science from Howard University where he was a W.K. Kellogg doctoral fellow at the Ralph J. Bunche International Affairs Center. Read more.

Registrations are closed

Demystifying Artificial Intelligence, Machine Learning and Deep Learning