Johns Hopkins Libraries supports the responsible, ethical, and transparent use of artificial intelligence in research, teaching, and scholarship. As AI tools become increasingly embedded in academic work, we are committed to helping our community navigate both the possibilities and the challenges these technologies present.
We align our approach with the Association of Research Libraries’ (ARL) Guiding Principles for Artificial Intelligence, which emphasize:
- Transparency, accountability, and explainability
- Privacy, security, and data stewardship
- Equity, accessibility, and inclusivity
- Open knowledge and collaboration
- Ongoing evaluation and adaptability
These principles reflect our belief that AI should enhance—not replace—the critical thinking, creativity, and integrity at the heart of scholarly inquiry. We aim to build AI literacy across disciplines, support responsible integration of AI tools in research workflows, and ensure our infrastructure and services uphold these values.
We invite our community to explore these principles and join us in shaping a thoughtful and just approach to AI in academia.
Read the full ARL AI Guiding Principles [pdf]
Responsible AI Workshops
Hopkins Libraries are developing training and workshops for using AI responsibly. As artificial intelligence becomes more embedded in research, teaching, administration, and everyday work, it’s essential that our community is prepared to use these tools thoughtfully, responsibly, and effectively.
Launching in the coming months, this program will include:
- Structured training and workshop offerings
- Hopkins-specific guidance and support for using university-supported AI tools, platforms, and policies
Library Staff Initiatives
AI Interest Group
The AI Interest Group is a staff-led initiative designed to build shared understanding of emerging AI and machine learning technologies across Johns Hopkins Libraries. By exploring the opportunities and challenges of these tools, the group aims to inform library policies, guide experimentation, and support thoughtful implementation.
Operational Workflows
To support innovation across our services, Johns Hopkins Libraries is actively exploring AI tools that can improve operational workflows. We use a shared evaluation process to identify opportunities, assess risk, and determine whether a tool is a good fit for further testing or pilot use. This approach helps us focus on practical applications of AI that align with our values and meet real staff and user needs.
Organizational Learning
In the coming months we will be launching a structured training and education program open to all library staff. Our goal is to ensure everyone—regardless of technical background—has the foundational knowledge needed to engage with AI meaningfully, critically, and creatively.
This learning series is designed to:
- Demystify AI technologies and concepts — Introduce foundational knowledge about how AI works, what it can and can’t do, and how it intersects with the work of academic libraries.
- Build critical awareness of risks and implications — Encourage thoughtful engagement with issues such as privacy, bias, copyright, accessibility, and environmental impact.
- Support practical skill development — Provide hands-on opportunities to explore tools and techniques—like prompt engineering, transcription tools, semantic search, and metadata automation—that may enhance or reshape library services.
- Foster a culture of exploration and continuous learning — Encourage staff to experiment, share insights, and participate in the co-creation of new practices as the technology continues to evolve.
- Lay the foundation for future service design — Build internal capacity to support researchers and students in responsibly using AI tools, while also identifying ways AI might improve library workflows and infrastructure.