Over the past several months, the ZSR AI Engagement Task Force has been working through a question that almost every academic library is sitting with right now: how do we want to engage with artificial intelligence in a way that is honest about what these tools are, faithful to our values, and useful to the people we serve? I’m really glad to share the result of that work with you today. Three new pages are now live on our site:

• The ZSR AI Engagement Framework, a principles-based guide for how we engage with AI in our work.
• The ZSR AI Values Statement, which articulates how our enduring commitments as a library shape our approach to AI specifically.
• The ZSR Guide to Using AI, which offers ZSR faculty and staff practical decision-making questions, current areas of use, areas where we proceed with care, and areas where we do not use AI at this time.

Together these three documents form a layered resource. The Values Statement names the foundation. The Framework translates that foundation into eight engagement principles. The Guide takes those principles into the texture of everyday decisions. They are designed to be read together but to stand on their own when that’s what you need in the moment.

A few things about how this work came together.

First, this was a genuinely collaborative effort, and that collaboration shows in every page. The taskforce gathered input through ongoing dialog with their departments as each document took shape, surfaced the range of perspectives honestly (from enthusiastic adoption to cautious curiosity to principled concern), and then built documents that hold space for that range rather than smoothing it over. The appendix of the Framework captures a summary of the staff perspectives that shaped the work, and you can see that variation reflected throughout. We treated disagreement as a resource, not an obstacle, and I think the documents are stronger for it.

Second, the documents are honest about the process. The taskforce used Claude to produce a baseline draft of each document, and then substantially revised those drafts through iterative review across departments. We thought it was important to say so plainly, both because transparency is one of our stated values and because the question of how to acknowledge AI assistance in our own work is one we are still collectively figuring out. Modeling that acknowledgment in the work itself felt like the right place to start.

Third, these are living documents. The Framework names this explicitly, and the Guide includes a section on what the framework deliberately does not do. We are not trying to resolve every question or anticipate every edge case. We are trying to build shared language and shared principles that support good decision-making together, with the expectation that we will keep learning and revising as the landscape changes and as our own understanding deepens.

I am grateful to the members of the AI Engagement Task Force for the care, rigor, and patience they brought to this work: Thomas Dowling, Amanda Kaufman, Denice Lewis, Joddy Marchesoni, Laura Milcarzyk, Morgan Ritchie-Baum, Sam Sfirri, Kate Silton, Meg Sturdevant, and Beth Tedford (and Claude!). The work reflects their collective wisdom and the wisdom of the many colleagues who joined the conversation and offered feedback along the way. Thank you, all of you.

If you have questions, reactions, or examples from your own work that the framework should be in conversation with, please bring them to your supervisor, to a taskforce member, or to me directly. That kind of ongoing conversation is how these documents stay alive.

There is more to come. We are continuing to develop a learning plan so we can explore together how AI is reshaping our work, but we wanted to share these live pages with you now.