AI Week
The Office of the Provost and the School of Engineering and Computer Science proudly present a series of presentations on the possibilities, limitations, and responsible approaches to emergent AI technologies from October 14-16, 2024, at Baylor's Paul L. Foster Campus for Business and Innovation
ETHICAL AI
Non-Computable You: What You Do AI Never Will
Dr. Robert Marks, Distinguished Professor of Electrical & Computer Engineering, Baylor University
Paul L. Foster Campus for Business and Innovation, Room 250
Monday, October 14 • 3:00 p.m.
Will machines eventually replace attorneys, physicians, computer programmers, and world leaders? What about composers, painters, and novelists? Will future supercomputers replicate and surpass human abilities? The answer is no. Just as math has its limitations—such as the impossibility of trisecting an angle with only a compass and straightedge—and physics has its boundaries—like the impossibility of perpetual motion—computers also face fundamental constraints. AI, both now and in the future, will never possess emotions, creativity, or understanding. These powers belong to another—to noncomputable you.
FUTURE OF AI
Convergence: Our Co-Evolution with Artificial Intelligence
Dr. David Copps, CEO/Co-founder of Worlds
Paul L. Foster Campus for Business and Innovation, Room 250
Tuesday, October 15 • 10:00 a.m.
Humanity stands at the brink of one of the most transformative periods in history, driven by the rapid advancement of artificial intelligence. This revolution has the potential to fundamentally reshape society, redefine industries, and challenge our understanding of human potential. In this talk, we will explore our future with AI, focusing on how the world might evolve as we develop and adapt alongside non-biological intelligence. From education to healthcare, energy to logistics, aerospace to agriculture, no sector will remain untouched by this technological upheaval, and no prior revolution has progressed at such a rapid pace. The moment to prepare for this change is now. If we navigate this integration thoughtfully, we could unlock unprecedented opportunities for innovation, progress, and human well-being.
Exploring the Future of AI in Higher Education
Panel discussion featuring our four AI Week speakers:
Dr. David Copps, Dr. Robert Marks, Dr. James Pitarresi and Dr. Collin Stultz
Moderated by Dr. Daniel Pack, Dean of the School of Engineering and Computer Science, Baylor University
Paul L. Foster Campus for Business and Innovation, Room 250
Tuesday, October 15 • 3:00 p.m.
Join the four speakers from AI Week as they share their insights on the evolving role of artificial intelligence in higher education. The panel discussion will illustrate the potential benefits, challenges, and ethical considerations that lie ahead. Following the panelist presentations, the session will transition into an interactive Q&A segment. Attendees are encouraged to engage with the panelists by asking questions related to their areas of expertise.
AI IN HEALTHCARE
Clinically Useful Machine Learning: How Close Are We?
Dr. Collin Stultz, Nina T. and Robert H. Rubin Professor, Electrical Engineering & Computer Science and Institute for Medical Engineering & Science, Massachusetts Institute of Technology; Director, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology; and Associate Director, Institute for Medical Engineering and Science, Massachusetts Institute of Technology
Paul L. Foster Campus for Business and Innovation, Room 250
Wednesday, October 16 • 10:00 a.m.
A necessary condition for the success of any machine learning model is that it achieves an accuracy that is superior to preexisting methods. In the healthcare sphere, however, accuracy alone does not, nor should it, ensure that a model will gain clinical acceptance. So, what constitutes a good machine learning model for clinical applications? Unlike problems outside of the medical domain, poor performance for clinical models can have deleterious consequences for patients. In view of the fact that no model, in practice, has 100% accuracy, attempts to understand when a given model is likely to fail should form an important part of the evaluation of any machine learning model that will be used clinically. In this talk we will expand upon the challenges that make the creation of clinically useful machine learning tools particularly difficult, and discuss ways in which they can be overcome.
AI FOR EDUCATION
Leveraging Generative AI for Course Development and Improved Student Learning: Enhance Quality and Efficiency
Dr. James Pitarresi, Distinguished Teaching Professor and Vice Provost for Online and Innovation Education
Paul L. Foster Campus for Business and Innovation, Room 250
Wednesday, October 16 • 1:00 p.m.
Generative AI offers us a powerful tool to enhance teaching and learning. In this session, we’ll discuss how to effectively use generative AI as an expert assistant to design courses that engage students while reducing the time and effort needed to develop course content. We’ll explore how to refresh course descriptions, develop learning outcomes, and build activities and assessments that align with those outcomes. Finally, we’ll address ethical concerns, including bias and academic integrity, to ensure the responsible use of AI in our academic environment.
For additional information about AI Week, contact Lauren Muhl, Assistant Dean of Operation in the School of Engineering and Computer Science, at (254) 710-7304.