From Anxiety to Agency: Equipping Faculty to Teach Responsible AI

As generative AI reshapes how students learn, write, research, and create, higher-education faculty face urgent and largely unresolved pressures: How do I hold students accountable without punishing curiosity? How do I uphold academic integrity without banning innovation? And how do I teach students to critically evaluate AI output when the tools themselves are imperfect?

This faculty-focused session treats Responsible AI as a teachable practice; not an abstract principle or an institutional policy waiting to be written. Rather than prescribing a single approach, it equips faculty with adaptable, classroom-tested strategies for three high-stakes instructional scenarios that educators across disciplines are navigating right now:
1. Co-creating responsible AI use guidelines with students: establishing transparency, shared expectations, and boundaries that students internalize
2. Teaching academic integrity in the age of AI: moving beyond detection toward disclosure norms, citation practices, and genuine conversations about appropriate use
3. Helping students detect hallucinations, bias, and inaccuracies in AI-generated output: building the critical verification habits students will need in every future workplace

The session provides faculty a practical foundation they can embed into existing courses without adding curricular burden. The focus throughout is on helping instructors make defensible, pedagogically sound decisions about AI use that they can stand behind, with students, colleagues, and accreditors alike. Participants will leave with:
- Concrete discussion prompts and teaching strategies ready to adapt for courses in AI, data science, digital literacy, and adjacent fields
- A framework for co-designing AI use expectations with students rather than imposing them from above
- A clear pathway to extend and deepen learning after the conference through free, self-paced resources tied directly to session content

This session is for faculty who recognize that responsible AI instruction is no longer optional and want a practical, principled framework to make it their own.