"...librarians already have a significant set of competencies that are essential in the successful, responsible, and ethical development of AI..." — Harper & Groth, 2025
Describes AI specialists as professionals who design and build software systems that can simulate human-like decision making. These systems collect and process information and then use that information to make informed actions or predictions.
Key points
Roles: AI specialists understand, critique and develop intelligent software and decision-making systems;
Collaboration: with machine learning engineers, data scientists, and analytics teams;
Core activities: understanding and applying algorithms, data, and testing systems that automate or support decision-making;
Education: advanced degree(s) in computer science or cognitive science; library and information science;
Skills: programming skills (e.g., C#, Java); experience in programming or systems analysis.
The presentation by Raymond Uzwyshyn discusses the emerging role of AI research librarians and how academic libraries are developing infrastructure and expertise to support artificial intelligence in research and teaching. It argues that libraries are becoming interdisciplinary hubs where data services, digital scholarship, and AI tools converge to support faculty, students, and research workflows.
Artificial Intelligence (AI) Librarian, Association of Research Libraries to lead and shape how faculty, students, and research teams engage with artificial intelligence (AI) in research and scholarly communication. This position is designed to help researchers not only use AI, but use it responsibly, ethically, and effectively.
Reporting to the Manager of Digital Scholarship and Data Services, the AI Specialist will lead the development of AI research support services at the libraries. As the Libraries’ go-to expert on AI tools, methods, and responsible use, they will empower the Hopkins community to integrate AI into research and learning in ways that are technically sound, ethically grounded, and aligned with institutional values.
This role is ideal for someone who thrives at the intersection of computation, scholarly inquiry, and public responsibility. The successful candidate will bring experience with machine learning or natural language processing, a deep knowledge of the evolving AI landscape, and a strong interest in helping researchers and scholars navigate the rapidly changing terrain of responsible AI use.
Specific Duties and Responsibilities
Design and deliver workshops, guides, and training that promote AI literacy and support responsible integration of AI tools into research;
Create user-facing resources (e.g., research guides, tutorials, and code notebooks) that help researchers learn and apply AI;
Develop and promote guidance on ethical and responsible use of AI, including best practices for attribution, transparency, and compliance;
Collaborate with campus partners (e.g., academic departments, data science or AI institutes, teaching and learning centres, and campus IT);
Work across library departments to develop internal training programs that equip librarians to respond to AI, questions, tools, and ethics;
Conduct outreach and build relationships with faculty, researchers, and students to understand evolving AI research needs;
Contribute to library initiatives related to digital scholarship, research support, and emerging technologies.
Special Knowledge, Skills, and Abilities
Knowledge of artificial intelligence technologies such as generative AI, natural language processing, and machine learning.
Ability to design and deliver instructional materials on AI tools and concepts, including workshops, tutorials, and course-integrated instruction.
Understanding of current discussions surrounding responsible and ethical AI use, particularly in research and scholarly communication.
Familiarity with the ethical, legal, and social implications of AI in academic and public contexts.
Strong communication skills and the ability to explain technical topics to interdisciplinary audiences.
Ability to work both independently and collaboratively with colleagues and library users.
Capacity to learn and apply new technologies, with evidence of ongoing professional development.
Commitment to inclusive and supportive learning environments for individuals exploring AI technologies.
Technical Qualifications or Specialized Certifications
Proficiency in relevant programming languages (e.g., Python, R) and experience with machine learning or AI frameworks (e.g., scikit-learn, Hugging Face, TensorFlow).
Minimum Qualifications
Bachelor’s degree in a relevant discipline.
Five years of related professional experience.
Additional education may substitute for required experience, and additional experience may substitute for education, according to institutional equivalency guidelines.
Preferred Qualifications
Degree in library or data science, computer science, information science, or a related field.
Experience applying AI or machine learning methods in research or applied settings.
Experience supporting researchers or students in the use of AI tools in academic, laboratory, or library environments.
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