Hosted by the AI Literacy Center at Oregon State University.
Join us for the second presentation in a three-part summer speaker series, "Critical AI Literacy for Information Work: Agentic AI"
Registration required.
Speaker: Ranjit Singh, director, AI on the Ground Program, Data & Society
Title: The Oversight Fallacy: Why Humans-in-the-Loop Aren't Enough for AI Agents?
AI agents are moving generative AI from response to action. Unlike chatbots that primarily answer questions, agents can take a high-level goal, translate it into a plan, and act across tools, files, browsers, databases, code, and other digital environments. This shift creates new challenges for universities, libraries, and research settings, where people are increasingly being asked to evaluate, support, and govern systems that can act at machine pace across institutional workflows. This talk examines why "human-in-the-loop" is an insufficient answer to the risks posed by agentic AI. Drawing on fieldwork on the use of AI agents in scientific workflows, I introduce the "goal-plan-execution gap" to describe the space between what users ask agents to do and how agents actually pursue those goals. I then walk through three oversight practices: post-hoc auditing, real-time monitoring, and steering. Together, these examples show why oversight cannot mean simply reviewing an output or approving the next step. Effective oversight depends on whether users can understand what an agent is doing, observe the right parts of its work, meaningfully constrain its actions, and intervene before small mistakes become consequential failures. I conclude by arguing that oversight should not be treated as an individual user burden. It has to be designed into agentic systems and organized through institutional practices, including audit rights, clear accountability structures, appropriate training, and meaningful authority to pause, redirect, or contest agentic work.
------------------------------
Laurie Bridges
Director, AI Literacy Center / Humanities Librarian
Oregon State University
She/Her/Hers
------------------------------