In AI-rich classrooms, answers often arrive before questions. This creates a central paradox for liberal arts education: tools that promise intellectual support can also short-circuit the uncertainty and iteration through which thinking develops. This session reframes AI literacy as the ability to structure and sustain inquiry when answers are instantly available. Participants will examine how common assignment designs invite premature closure and will practice redesigning them using three strategies: staging tasks to delay answer-generation, requiring student reasoning before feedback, and separating composing from evaluation. Attendees will leave with adaptable frameworks for designing assignments that preserve critical thinking across disciplines, even when AI systems can generate polished responses on demand.
Benjamin Breyer is Senior Lecturer in English at Barnard College, where he teaches First-Year Writing and directs research on AI-mediated learning and rhetorical scaffolds in the liberal arts. His work focuses on designing writing instruction that reinforces critical reading, interpretive... Read More →
Friday October 16, 2026 1:00pm - 1:30pm EDT Blaustein 210
"Is this AI?" is a question vexing even the most media-savvy users today, as synthetic images and videos grow exponentially more convincing, with widespread circulation. But are there reliable "tells" and transferable frameworks for critical AI media literacy, even in this rapidly shifting landscape? This interactive presentation invites participants to examine a curated selection of images and videos and discuss: Is this AI? How do you know? Rather than offering easy answers, this session will use guided exercises and discussion to consider critical media AI literacy, inviting participants to think about visual artifacts & physics (is the hair texture right?); anatomy & proportions (are the joints strangely elongated?); and context & coherence (what is the file provenance or source?). Along the way, participants will consider deeper questions of authenticity, consent, and responsibility in an era of increasingly convincing synthetic media, and how critical AI media literacy has relevance in a liberal arts curriculum.
This session introduces Colgate University’s Innovation Fellows and their use of AI, and its evolution into a new undergraduate consulting program that pairs human-centered design (Design Thinking) with intentional, responsible AI use to solve real campus problems. Rather than viewing AI as a shortcut, this program trains liberal arts students to leverage it as an active collaborative thought partner for synthesizing research, stress-testing prototypes, and generating ideas.The session highlights their inaugural pilot success: a partnership with Colgate’s ITS Service Desk to rethink and revise intern training. Using empathy-gathering interviews, observations, and surveys, as well as a design sprint, the student team produced a training program that includes AI-generated instructional content, a role-playing simulation game, and a skills progression rubric. The proposal was accepted by ITS for implementation beginning summer 2026. Presenters will detail the program's design, AI learning outcomes, and pilot results, while examining why liberal arts institutions are uniquely positioned to model this work.
Director of creative technologies, engagement and support, Colgate University
Ahmad is currently the director of creative Technologies, Engagement and Support. With previous roles in student support, instructional support, and desktop administration he is able to leverage a variety of perspectives when approaching new problems.
Friday October 16, 2026 3:25pm - 3:55pm EDT Blaustein 210
This session proposes how to define and teach “AI literacy” in liberal arts classrooms for the increasingly AI-integrated world. Unguided AI use does not automatically produce literacy; instructions focused solely on a technical capacity will become outdated at every major model change. Instead, AI literacy must be captured as a disposition, or a durable habit of the mind, that emphasizes the value of human judgment in ever-changing technological landscape. The pedagogical task is to cultivate this disposition through intentional hands-on engagement that turns AI use into an object of guided critical inquiry: observing, iterating, and evaluating human-AI interaction and developing sound judgment for responsible human-AI collaboration. Participants will experience a short AI literacy activity that reveals a commonly held misconception about AI and debrief how guided encounters can help students examine AI behavior, their own assumptions, and the ethical choices involved in learning with AI.
From the ancient Greeks forward, liberal arts education has never been only about storing information. It has been about forming judgment through practice: rhetoric in the agora, philosophical dialogue, ethical deliberation, and the disciplined use of language in public life. Oratory, dialectic, and disputation were not simply ways of displaying knowledge, but of testing whether a person could think, respond, persuade, and act wisely in context. As generative AI unsettles traditional assessments, this older tradition becomes newly relevant. This presentation argues that AI-powered simulations can recover something essential to liberal arts learning by shifting assessment from static recall to situated performance. Using GENESIS as a case example, this talk will explore how conversational, competency-based simulations can make visible the capacities the liberal arts have long aimed to cultivate: judgment, communication, ethical reasoning, interpretive agility, and the ability to use language as action. Rather than abandoning the humanistic tradition, simulations may help us reclaim it in a new form.
Vibe coding — building working software through natural-language conversation with AI rather than traditional programming — has quietly removed the technical barrier that once kept faculty and students from creating their own interactive learning tools. This session embodies the symposium's central paradox: the same capability that lets a student generate code without understanding it can let a humanities professor build a simulation that finally makes an abstract concept click. In thirty minutes, participants watch a fully playable classroom simulation emerge live from a plain-language prompt, then interrogate what that means for learning. When a literature, economics, or government instructor can prototype a simulation in minutes, who is doing the thinking — and is that a problem or a breakthrough? Participants leave with a shared, honest framework for deciding when vibe-coded simulations deepen understanding and when they short-circuit it.
What is a faculty learning community (FLC)? Why is this model so relevant for the topic of AI and the Liberal Arts? This session proposes to answer these questions by introducing the FLC model, which brings together faculty and staff in a community of practice, and to argue for its relevance as a means of fostering interdisciplinary and collaborative connections, debates, and discussions, as well as practical outputs, in relation to the role of AI in higher education and more specifically in the Liberal Arts. Through a demonstration of how to form an AI-focused FLC, interactive activities, and shared resources, this session will leave the audience with the means of forming their own AI-focused FLCs at their home institutions, as well as giving audience members the opportunity to connect with colleagues from a variety of institutions who plan to undertake this same goal.
Visiting Assistant Professor - Francophone Studies, Trinity College
Elisabeth Herbst Buzay is a Visiting Assistant Professor of Francophone Studies at Trinity College. Her research focuses on topics including multimedia medievalism and extraordinary communication, in works ranging from French Medieval literature to contemporary French fantasy works... Read More →
Saturday October 17, 2026 3:30pm - 4:00pm EDT Blaustein 210
When AI arrived on campus, most institutions responded the same way: individual faculty experimenting in isolation, policy committees deliberating, and a general sense of productive chaos. At Hobart and William Smith Colleges, the Digital Learning Center took a different path: restructuring one role to make AI integration its central focus, then building outward from there. In this interactive session, participants will explore how a single department can catalyze institution-wide AI culture change without a massive budget or a dedicated AI office. Drawing on initiatives including a faculty Community of Practice, a BoodleBox pilot, and intentional strategies for amplifying student voice, this session offers a replicable framework for moving from scattered experimentation to coordinated community effort. Participants will leave with concrete strategies they can adapt to their own institutional contexts and the conviction that meaningful, human-centered AI integration is within reach, regardless of institutional size or resources.
