The focus of the seminar series is to call for experts related to academia and research in the areas related to biomechanics, variability, motor disorders, physical therapy, and related studies.

Presentation Title: From Experimentation to Infrastructure: How Universities Should Rebuild Research, Teaching, and Academic Culture in the Age of AI

Presentation Abstract:

This seminar offers an institution-level case discussion of how a university can navigate the rapid transition catalyzed by contemporary artificial intelligence, including generative systems and other automated reasoning tools. The talk synthesizes lessons from building AI-integrated programs, coordinating faculty and staff upskilling, and developing governance practices that address privacy, academic integrity, equity, and long-term sustainability. Rather than treating AI adoption as a set of isolated classroom experiments, the presentation frames the transition as a coordinated change-management problem spanning research workflows, curriculum architecture, assessment norms, and the culture of scholarly collaboration. The seminar also addresses tensions now appearing across campuses: uneven tool access, disciplinary differences in evidentiary standards, uncertainty around intellectual property, and the need to train students for hybrid human–AI work without eroding foundational literacies. The session concludes with a pragmatic framework for departments seeking to move from reactive experimentation to intentional strategy, emphasizing governance, faculty development, and research-centered evaluation of impact.

About the speaker:

James Hutson, PhD, PhD is a multidisciplinary scholar and academic leader specializing in artificial intelligence, higher education strategy, and interdisciplinary research transformation. He holds a PhD in Artificial Intelligence, alongside advanced training in the humanities, and serves as Department Head of Art History, AI, and Visual Culture at Lindenwood University, where he leads institution-wide initiatives integrating AI across research, teaching, and academic governance. His work focuses on how generative and decision-support systems reshape scholarly workflows, curriculum design, faculty development, and institutional policy, with particular attention to ethical deployment, transparency, and long-term sustainability. Hutson is the author and editor of multiple books and peer-reviewed publications on artificial intelligence in education, research, and culture, and he regularly advises universities, public agencies, and industry partners on navigating the organizational and cultural transitions associated with AI adoption.