From AI Resources to Thoughtful Practice: What We’re Learning (and Trying) at Furman

In December, we shared an overview of the growing set of AI resources Furman has access to through the Council of Independent Colleges’ (CIC) AI Ready: All Campus Essentials program. If you missed that update, you can catch up here: AI Ready at Furman: All-Campus Essentials Resources. 

Since then, the AI Ready program has continued with two additional focus areas that speak directly to common questions and concerns we hear from Furman faculty and staff: Administrative Use of AI (January) and Hyper-Personalized Learning (February). 

January: Administrative Use of AI (Reducing Drudgery, Not Replacing People) 

The January sessions focused on AI as a collaborative partner in administrative work, helping to reduce routine tasks so that staff can spend more time on high-impact, human-centered work. A key theme was that effective AI use starts small and personal (e.g., targeting workflow pain points) and can scale thoughtfully to departmental and institutional contexts. Importantly, the framing throughout emphasized augmentation rather than automation: AI can support human judgment, communication, and care, but it should not displace them. 

For faculty, even if administrative workflows aren’t your primary concern, this framing offers a useful lens for thinking about AI more broadly: Where might tools responsibly reduce drudgery without hollowing out the meaningful, relational work that defines higher education? 

You can find all of the January resources on Box. 

February: Hyper-Personalized Learning (Tempering Hype with Care) 

February’s sessions took on a topic many of us approach with both curiosity and caution: AI-driven personalization in teaching and learning. The webinars offered a grounded perspective. Rather than leaning into “super-tutor” hype, the presenters highlighted the limits and risks of personalization such as uneven access, thin evidence of learning gains, privacy concerns, and the danger of replacing mentorship with automation. 

One particularly generative thread reframed personalization as community-centered rather than purely individualized: AI might help map options, but learning still happens in human relationships, disciplinary communities, and local contexts. The sessions emphasized privacy-first tools, transparency, and an intentional shift from “policing” student use of AI toward an apprenticeship model that foregrounds process, inquiry, and ethical engagement. 

You can find all of the February resources on Box. 

A Resource Worth Your Time: Slow AI and the Integrity Debt Audit 

For those feeling wary of speed, hype, or pressure to “adopt AI” wholesale, we especially want to highlight the work of Sam Illingworth, who writes the Slow AI Substack. His framework invites educators to pause, reflect, and ask harder questions about what we gain, and what we risk losing, when we integrate AI into our work. 

One concrete tool you might find useful is the Integrity Debt Audit, an interactive resource that helps faculty identify where an assignment can be automated by AI. Illingworth notes, “Many traditional assignments (essays, reports, literature reviews) are now vulnerable to being completed by AI in minutes rather than through genuine student learning. This creates what I call Integrity Debt: the gap between what you think you’re assessing and what students can now automate. This diagnostic evaluates your assessment brief across 10 evidence-based categories that distinguish human learning from AI automation. Each category is scored from 1 (easily automated) to 5 (resilient to AI), giving you a total integrity score out of 50.” 

Try It Out: AI Play Sessions in March 

If reading about AI feels abstract, or if you’d prefer to explore these questions hands-on in a low-stakes environment, we invite you to join one of our AI Play sessions in March. 

Curious about how AI might support your teaching or streamline your daily work?
Join us for a two-hour, drop-in “AI Play” session—offered on both Wednesday and Thursday—with space for up to 20 participants per session. These sessions provide a supportive environment for faculty and staff who want guided practice using AI tools for course design, feedback, writing tasks, data organization, and other workflow improvements. Several experienced colleagues will be on hand to answer questions, demonstrate possibilities, and help you experiment at your own pace. Come with a task in mind—or simply come curious. 

Whether you’re enthusiastic, skeptical, or somewhere in between, AI Play is designed as a space for thoughtful experimentation, not evangelism. We hope you’ll join us to explore what these tools can—and can’t—do in ways that align with your values and your work at Furman. Register for this opportunity online.