A Place for AI in Higher Ed

During our EDUCAUSE pre-conference workshop Co-Creating AI Strategies: A Design Thinking Approach, my co-facilitators and I faced a dilemma. The clock was ticking. Our participants had generated hundreds of ideas on sticky notes. It was a rainbow of distinct thoughts on 2-inch squares covering every surface of the room. The task was to synthesize these thoughts into themes to move to the next exercise, and we were already behind schedule.

Technologically speaking, the solution was obvious. We could have digitized the notes, fed them into an LLM, and received a categorized summary in seconds. It would have been automatic, easy, and efficient. It would have kept us on pace.

Instead, we chose the "inefficient" route. We asked the humans to do the work. We asked them to sit with the ambiguity, wrestle with the connections, and find the patterns themselves.

This choice highlights the tension for artificial intelligence adoption in higher education. We need to recognize the bifurcation of objectives. If the goal is a product like a report or a schedule, AI is often the superior tool. However, if the goal is a process like critical thinking or deep learning, the friction of doing the work manually is not a bug. It is the feature.

True AI strategy requires "objective-aligned augmentation." We must teach our community to value efficiency for outputs, but to value the intentional pause where learning happens.

The workshop was a success, demonstrating how we can leverage AI to build robust strategies. However, for me, the biggest takeaway was the reminder that while AI can solve many challenges, we must always keep the human at the center as we move forward.