AI and the Librarian: Reconciling Personal Ethics with AI as a Professional Necessity

What does ethical AI interaction look like in a role where you can’t ignore or cut it out altogether?

Posted on April 6, 2026 in Blog Posts

In a field shaped by strong values, many librarians cite ethical concerns with labor, copyright, privacy, and the environmental impact of AI. Some professionals are shirking it altogether. AI in warfare has recently joined the growing list of user concerns, with some swapping platforms or swearing off the technology. However, as vendors continue to integrate AI into library platforms, patrons increasingly rely on these tools for everyday tasks, and institutions commit to AI-forward strategies, complete disengagement is not an option for today’s librarian.

So, what does ethical AI interaction look like in a role where you can’t ignore or cut it out altogether? Balance is key.

Recognize patron use of AI and validate it.

Balancing patron support with personal ethics is perhaps the most challenging part of ethical AI use. Patrons are likely engaging with AI somewhere in their lives, and in a world where expertise is a valuable social commodity, it promises to be a great equalizer. Our patrons will soon have a wide range of comfort and expertise with AI, and many reference questions already reflect ChatGPT-influenced queries. In other words, AI is becoming more ubiquitous in libraries with each passing day. As with all other trends, librarians need to have their fingers on the pulse to best understand how this technology impacts patron information-seeking needs and behaviors.

Despite the proliferation of AI, admitting to its use does seem to have something of a social taboo. Combine that with an intimidating reference interview where the librarian has a clear disdain for AI usage, and we risk pushing patrons further out of the library.

The solution: normalize asking patrons as part of your reference interview if they’ve used generative AI during their research process and, if so, how they utilized it, so you can learn more about the research project at hand. When communicating with patrons, destigmatize AI use by acknowledging that many patrons use it and it can be a helpful resource. Then, pivot to ask for more information about the research at hand and/or a copy of the patron’s chat prompt, so the reference interview can pick up at a place that we’re better equipped to support. Doing so maintains our professional role as a nonjudgmental guide to information while subtly signaling that regardless of our personal feelings about AI, we understand how widespread it is.

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Familiarize yourself with AI and AI library tools, but don’t forget tried-and-true librarian skills along the way.

Even if you’ve mostly been able to avoid AI in your personal life, it is still inescapable in libraries, and there is no “right” amount of AI engagement. Like it or not, library staff will need some exposure to AI to best understand how it can be used by patrons. This should include frequent test searches in freely available generative AI platforms and in library resources, so librarians have some sense of how AI can support patron research and how these tools are changing over time. It will also make sense for some staffers to incorporate AI into their workflows and find frequent applications for these tools.

With that said, don’t forget to exercise your librarian skills along the way. It may be tempting to outsource complex reference questions to AI, but don’t forget that it is okay for librarians as the experts to not have all the answers. Don’t hesitate to go back to your patron to clarify their ask, lean on your colleagues for their expertise, and employ traditional search strategies when you need to bolster your understanding. For project work, incorporate AI where it makes the most sense, like lower-risk projects without any personally identifiable data, but omit AI where it does not add value.

Library ethics still apply.

While the AI ethical guardrails are still being built, our professional ethics and our institutional ethics must continue to guide our work. There are numerous guiding principles, resource guides, agency guides, and blog posts on the topic of ethical AI use or the ethics of AI itself. Many of these resources discuss the murky ethics behind the creation of Large Language Models (LLMs), but few prescribe a path forward for libraries.

When all else fails, extend existing ethical guidelines to AI in libraries. The technology may have changed, but we should still strive for professional excellence, protect the interests of our patrons, and distinguish between our professional duties and personal convictions. You can limit your personal AI use, but full exclusion is no longer realistic.

Call out low-quality AI outputs when you see them.

As AI becomes more embedded in the library tools and the research landscape, it remains our professional responsibility to ensure that these resources are accurate, reliable, and aligned with the standards of our field. AI can streamline repetitive tasks and support brainstorming, but overreliance on these tools can introduce errors and undermine the quality of our work.

By actively experimenting with AI, library staff can better understand how patrons engage with these tools while also assessing their reliability. A hands-on approach allows us to identify inaccuracies, biased outputs, or problematic search behaviors and to then communicate our findings with colleagues, patrons, and vendors. Not every resource benefits from AI integration, and libraries still have a responsibility to advocate for quality when these tools fall short. Similarly, we have an ethical duty in the library landscape to call out sloppy use of AI. AI has a role to play in research, but overreliance can also devalue the scientific process. As researchers and information professionals, we should follow publisher guidelines, transparently disclose AI use, and hold ourselves and our peers to a high standard when integrating AI into research practices.

Don’t over-rely on AI for basic tasks.

There are compelling reasons to both limit and expand AI use in libraries. In a field plagued by attrition, AI can offer meaningful support by assisting with tasks like image generation, editing, and marketing. However, these applications and their outputs must be carefully evaluated for accuracy and real benefit. Libraries should intentionally decide which projects are well-suited for AI, the extent to which AI should be employed overall, and whether it truly saves time or improves outcomes. As individuals, we can model this critical approach for colleagues and patrons alike by encouraging human-first communication while reinforcing the library’s timeless role in guiding users to accurate, reliable information.

For those reevaluating their own AI use, scaling back to a more intentional, exploratory approach can help maintain tool familiarity while avoiding overreliance on it for routine tasks. As an early adopter of generative AI, I found myself increasingly using it for routine tasks, like emails and outlining ideas. Over time, I realized that these applications did not save me much time and did little to improve my work outputs. I still engage with AI where it adds value and to remain current with emerging tools, but I’m now aiming for more deliberate applications that ensure that it supports, rather than replaces, my own thinking and workflows.

Don’t lean on AI for the parts of your job that you enjoy.

There’s an AI solution for every problem, but as with all other uses, carefully consider whether it is going to bring something to the table, including emotionally. You can also evaluate your AI usage to determine if AI is going to reduce or remove something that brings you joy or added value in your role. You could employ AI for a myriad of job-related tasks, but if you enjoy doing those tasks yourself, you don’t have to incorporate AI into them. For some librarians, responding to reference messages is emotionally draining, while other librarians find that they are reenergized by carefully crafting each word of a response to their patrons. Incorporating AI to make a template or help craft a response will make sense for some library staffers but will be a poor application for others. The good news is that you can choose to use AI to aid with the tasks you don’t enjoy, not the ones you do. To paraphrase my colleague Austin Haley, “I don’t want AI to make art so I have time to fold my laundry; I want AI to fold my laundry so I have time to make art.”

The bottom line is that librarians must navigate a careful balance when engaging with AI through an ethical lens: maintaining enough familiarity with AI to support patrons and meet institutional expectations while resisting overreliance that conflicts with professional values or personal convictions. Ethical AI use will not look the same across roles or individuals, but it can be guided by a shared set of principles centered on patron behaviors, core library ethics, and intentional decision-making about when and how to engage with these tools. Doing so allows ethical AI use to become less about rigid rules and more about sustained, critical engagement with a technology that is already embedded in our professional landscape.

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