AI@ACC Panel 1: Talking to your Students about AI Ethics
AI@ACC Panel 1 brought together Alex Watkins, Toño Ramírez, Andy Kim, and Mavis Klemcke for a candid, laugh-a-little conversation about syllabus policies, student fears, and what transparency really means. Mentimeter results showed big love for openness and process over policing.
AI@ACC Panel 1 Recap: Talking to Your Students About AI Ethics
The first AI@ACC panel opened with a big question many faculty and staff are asking right now: How do we talk to students about AI in ways that are thoughtful, ethical, and practical? The conversation brought together Alex Watkins (Technical Communications and AI Committee), Tono Ramírez (Philosophy and AI Committee), Andy Kim (Energy and Sustainability), and Mavis Klemcke (Faculty Librarian), with moderation focused on creating space for open conversation and shared learning around AI at ACC.
One thing became clear quickly. People across the college are in very different places with AI. Mentimeter responses showed that most attendees described themselves as experimenting or actively engaging with AI conversations, with only a small number avoiding or observing from the sidelines.
The discussion centered on a message that came up repeatedly: students need guidance, not silence. Participants strongly agreed that ignoring AI risks leaving students unprepared for civic and professional life. They also strongly agreed that ethical reasoning about AI is a skill students will carry into careers beyond college.
Transparency matters
One of the strongest themes from both the panel and Mentimeter responses was the importance of transparency.
Participants overwhelmingly agreed that:
- Students benefit when faculty explain the reasoning behind AI boundaries
- Open conversations about AI can reduce student anxiety
- Students deserve transparency about how instructors use AI
- Students need guidance about why to use AI responsibly, not just rules about whether they can use it
Faculty concerns also surfaced clearly. When asked what student situations felt hardest to navigate, the top challenge by far was determining what to do when it seems obvious a student did not write their own paper. Other challenges included inconsistent expectations across courses and questions from students about where the line between support tools and cheating exists.
Process matters more than detection
A powerful thread throughout the discussion focused on moving beyond trying to “catch AI” and instead designing learning experiences that make thinking visible.
Faculty shared strategies like:
- Breaking writing into smaller stages with drafts and revisions
- Using peer review and process feedback
- Looking at revision histories
- Building reflective components into assignments
- Focusing on how students arrived at answers, not only final products
Mentimeter responses reinforced this idea. Participants strongly agreed that teaching with AI requires rethinking assignments, not simply policing behavior.
AI literacy belongs across disciplines
Another interesting finding involved AI literacy itself.
Participants leaned strongly toward the idea that AI-generated content should be treated as something to interrogate and think critically about rather than automatically trust. AI literacy was framed not as a technology issue alone, but as a cross-disciplinary skill involving critical thinking, ethics, information literacy, and judgment.
The panel also highlighted practical concerns faculty and staff face every day:
- Which AI tools are institutionally supported
- Privacy considerations
- Responsible use of third-party tools
- Understanding policies around data sharing and approved technologies
Panelists encouraged caution, thoughtful experimentation, and attention to institutional guidance while recognizing that AI technologies are evolving rapidly.
What stood out most
Perhaps the strongest takeaway from Panel 1 was that faculty and staff do not need perfect answers before beginning conversations.
The goal is not to become an AI expert overnight.
The goal is to create classrooms and workplaces where students can ask questions, think critically, wrestle with ethical challenges, and learn how to navigate technologies they will encounter long after leaving ACC.
As one theme surfaced repeatedly throughout the session: AI conversations are no longer optional. They are becoming part of helping students prepare for the future.
View the session summary or watch the session recording to dive in deeper!
AI@ACC Panel Series is a four-part, cross-disciplinary, dialog-based conversation series developed through Austin Community College’s (ACC) participation in the AAC&U Institute on AI, Pedagogy, and the Curriculum. Grounded in national research, the series explores how artificial intelligence is shaping teaching, learning, assessment, and the future of work in higher education across teaching, support, and workforce roles.
Designed as a low-pressure entry point, this series centers real questions, lived experience, and diverse perspectives rather than tools, mandates, or hype. Ethical concerns, including bias, labor, environmental impact, and academic integrity, are acknowledged and respected throughout. No prior AI experience is expected. Questions and uncertainty are welcomed.
AI@ACC is a space for inquiry, not compliance. The series is exploratory and reflective rather than directive. While AI raises serious concerns, disengagement does not ultimately protect students. These conversations focus on helping educators and staff thoughtfully support students as they navigate evolving academic and workplace norms.