AI Info Sessions

From 300 Papers to Key Insights: AI-Powered Literature Discovery, presented by Carlos Lizárraga, explores how artificial intelligence can help researchers quickly analyze large collections of academic papers and extract the most important insights. The session focuses on using AI tools to efficiently navigate extensive literature and identify key research findings.

An AI Insights session with ORAI featuring Michele Cosi highlights the University of Arizona’s GenAI Platform and explores responsible AI governance, cross-sector collaboration, and community-centered strategies to advance public benefit across Arizona.

This session provides an overview of responsible AI practices and tools for small businesses and non-profits, highlighting how AI can be applied ethically and effectively in real-world work environments.

Jeff Gillan, Geospatial Data Scientist with the Arizona Institute for AI and Society (AI2S) will present Agents in Academia: The Promise & Peril of Autonomous AI Systems.

This AI Insights session, presented with the Office of Responsible AI, features Carlos Lizárraga presenting From Frustration to Precision: Mastering the CRAFT of AI Prompting, sharing practical strategies and the CRAFT framework to improve clarity, structure, and the quality of AI-generated responses.

This AI Insights session, presented with the Office of Responsible AI, features Michele Cosi and Jeff Gillan discussing The AI Ecosystem at U of A: Tools, Programs, and Resources that Support Research, highlighting campus AI tools, programs, and support for responsible, collaborative research.

This AI Insights session, presented with the Office of Responsible AI, features Carlos Lizárraga reviewing Responsible AI Use and Academic Integrity, focusing on ethical practices and institutional expectations for responsible AI use.

This AI Insights session, presented with the Office of Responsible AI, features Enrique Noriega-Atala presenting From Next-Word Prediction to Hallucinations: How Large Language Models Really Work, demystifying how LLMs generate text, why hallucinations occur, and what that reveals about their capabilities and limits.