Transforming Library Collections and Research with AI and Machine Learning
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Transforming Library Collections and Research with AI and Machine Learning
A PRESENTATION BY Greg Ritter
Strategy Lead for Research Data, Scholarly Communications, and Libraries at Amazon Web Services (AWS)
Artificial intelligence and machine learning (AI/ML) have transformative potential for modern research libraries and research processes. This lecture examines how AI/ML technologies, including generative AI, can automate labor-intensive library workflows, enhance collection and data discoverability, and enable new forms of engagement, research, and analytics. Through real-world projects, we'll demonstrate the impact of automated metadata extraction, intelligent document processing, machine transcription and translation, natural language processing, and interactive learning. The presentation also explores emerging applications of generative AI in academic libraries, while addressing critical challenges around accuracy, privacy, and ethics. Discussion includes frameworks for responsible AI development and deployment in educational settings, with emphasis on practical implementation strategies.
Greg Ritter leads AWS Higher Education strategy for Research Data, Scholarly Communications, and Libraries. He holds a BA in English from Virginia Tech (and worked in Newman Library) and an MFA in Creative Writing from the University of Iowa. Greg has taught at Iowa, Virginia Commonwealth University, and the University of Richmond. While teaching, his technology focus began with an Annenberg Foundation grant on incorporating technology into writing classrooms. After serving as Director of Academic Technology at Gallaudet University, he joined Blackboard, Inc., in its early years and held a variety of positions culminating in Sr. Director of Higher Education & Government Strategy. Greg joined AWS in 2019.
If you are an individual with a disability and desire an accommodation, welcome! Please email ylchen@vt.edu at least 10 days prior to the event.
- Date:
- Friday, January 31, 2025
- Time:
- 10:00am - 11:15am
- Audience:
- Advanced Alumni Beginners Faculty/Staff Graduate Students Postdoc Public Undergraduates
- Categories:
- Event > Livestream