In Summer 2023, Teaching and Learning Innovations (TLi) launched our AI Residency, an experimental opportunity for a CSU Channel Islands staff member and a faculty member to join the TLi team in a summer of exploring, tinkering, learning, and critically analyzing AI diffusion in higher education. Through weekly meetings with demonstrations, a shared commitment to exploration between meetings, and an asynchronous channel for AI chit-chat, we became a community of inquiry. By summer’s end, we knew that this model needed to expand because of the dizzying pace of AI diffusion and the space that the Residency gave us to learn something new and timely together.

So, for 2024, we expanded the Residency to seven faculty (who volunteered their time) and four staff-in-residence, in addition to six members of the TLi team. We had representation from several corners of campus, including Research & Sponsored Programs, Information Technology Services, Library & Learning Resources, MVS School of Business; Arts & Sciences; Extended University, Center for International Affairs, School of Education, Institutional Research, and Teaching & Learning Innovations. To me, this wide-ranging participation highlights the varying possibilities for AI applications across academic, professional, and operational spaces. That observation was reinforced by the wide range of demonstrations that were brought to the sessions, from image generation to document development, to coding, and more.

Demos and Exploration

Our sessions were organized around two demonstrations and an open discussion. The demos were brief: In 15 minutes, the Resident offered a quick overview of a tool or a case study from personal experience. One Faculty-in-Residence shared how she used ChatGPT to develop an escape room for her students to apply their content learning in a gamified way, while another shared how she was trying to see if she could use ChatGPT’s coding features to develop an automated early alert and communication tool. A Staff-in-Residence shared how she developed support guides for grant development, astutely noting the boundaries between where the usefulness of AI ended and where her human expertise and relationships in that process were essential. We also used our time together in Zoom to test out Zoom’s AI Companion features, including the meeting summary and in-meeting chat feature.

Between sessions, it was time for exploration. That’s how we came across SUNO, an AI song generator that will create a song in any genre and with custom lyrics that users can either input or allow the platform to generate. It was fun to begin each session with a catchy song about the AI Residency and introducing the presenters for that day. We also shared news, resources, and critical reflections on the cases we encountered, both during in-session discussions and asynchronously through a Padlet and Teams group. 

Purpose and Principles

With all of the hype and panic about AI diffusion and the fast pace with which new tools and their applications have and continue to emerge, Teaching and Learning Innovations wanted to make time and space to learn together with and from our colleagues. We wanted to explore pragmatic use cases and consider both the potential and the limitations—the possibilities and the constraints—present in AI tools and applications. 

To that end, we shared the following values:

• Learning: Every one of us is learning, regardless of previous experience (or lack thereof) with AI. We gathered in the spirit of continuous learning and development, starting with the assumption that we have expertise in our respective fields but that we are all new to the types of AI applications we would encounter in the Residency.
• Inquiry & Diverse Expertise: Related to learning, we made space to explore questions like, “Can I ask the Zoom AI Companion a question that is limited to the Zoom chat only, or does it only answer questions about the meeting discussion?” We asked how things worked, and we were fortunate to have colleagues present with diverse professional expertise and experiences related to AI, so our curiosity led to some great insights during our discussions.
• Inclusion: We wanted the Residency to function like a sandbox where people felt welcome and willing to play with something relevant to their personal or professional interests.

Personal Takeaways

Put simply, the AI Residency has been a highlight of my summer for the past two summers. Last year, we began our sessions with AI-themed music (mostly involving robots) and some kind of AI-related icebreaker (e.g., indicating the probability of doom on a digital gauge) before heading into the demos and critical discussions. This year, the tools evolved so that we could begin with AI-generated music with lyrics introducing the presenters for that session (thank you to Michael McGarry for compiling our final session songs into a playlist). 

One takeaway is that the Residency is a good model for learning new technologies. Every demo was fascinating because each person brought their own use case and personal applications to their AI explorations. Keeping the sessions to 60 minutes was challenging, and we could have filled multiple hours, but it was also the right amount of time so that it was not burdensome. The session format was also intended to reduce the feeling of burden and overwhelm that can come with learning new technologies (especially rapidly evolving AI tech). Together, and with a manageable structure and time commitment, the staff and faculty-in-residence created a positive, exploration-oriented community. 

A final takeaway is that all of us are still learning and that our familiarity with generative AI is still developing and widely varied. One Resident showed a sophisticated application of ChatGPT that has promise for transforming the way she communicates with students at key points in the semester. For another, this was the first time that they had tried any AI tools for work purposes. Many campuses are offering training and certification that are quickly becoming outdated as AI tools continue to evolve. We have done our part to curate and share those opportunities (e.g., SDSU’s AI Microcredential remains a good option for those new to AI and wanting micro-credentialed training). Still, I feel validated in making time and space for inquiry, vulnerability, encouragement, and community with our Residents. I’m also excited for what is still to come!

Heartfelt thank you to the talented members of the Teaching and Learning Innovations team who made the Residency possible: Michael McGarry, Kristi O’Neil-Gonzalez, Georgia Van Tyne, Ben Hytrek, and Megan Eberhardt-Alstot.

And, most special thanks to our TLi AI Residents: 

2023 – Dan Lenz; Jerilee Petralba

2024 – Annie White, Asha Ramachandra, Breeann Austin, Cindy Sherman, Courtney Gross, Fable Mangold, Kristen Linton, Kristin Jordan, LaSonya Davis, Nicole Amato, and Yeawon Yoo