Transforming Library Assessment through AI: Opportunities, Challenges, and Ethical Considerations

The integration of Artificial Intelligence (AI) in libraries and library assessment is transforming how institutions assess services, allocate resources, and engage with users. As AI technologies evolve, libraries are exploring both AI-assisted and AI-driven approaches to streamline operations, improve service delivery, and better respond to user needs. This blog post delves into how AI is reshaping library assessment, the potential benefits, and the ethical considerations libraries must address to navigate these innovations effectively.

This blog post is a summary of the paper written and presented by Leo Lo and Martha Kyrillidou for the 2025 Library Assessment Conference that took place in November in Portland, Oregon.

The AI Revolution in Libraries

       

AI is rapidly transforming industries across the globe, and libraries are no exception. From automating repetitive tasks to uncovering insights from vast datasets, AI presents libraries with the opportunity to modernize and adapt in an increasingly digital world. While AI is still being explored and tested in library settings, it has already been helping librarians optimize resource management and enhance operational efficiency. However, as libraries implement AI, it is crucial to proceed cautiously, ensuring that technology complements human expertise, instead of replacing it, while addressing ethical concerns such as bias, accountability, and transparency.

Rethinking Library Assessment

Traditionally, libraries have relied on qualitative and quantitative assessment methods to measure service impact and user satisfaction. These methods, while effective, often struggle to capture the complexities of today’s digital library environments. AI opens up new possibilities for library assessment by providing tools to analyze vast amounts of data, predict trends, and uncover hidden patterns. However, this shift also raises critical questions about ethics, data privacy, and human oversight.

AI-assisted assessment methods enhance human capabilities, offering predictive analytics and natural language processing to streamline decision-making. AI-driven systems, on the other hand, take on a more autonomous role, making decisions with minimal human input. This evolution challenges traditional assessment paradigms, as libraries must strike a balance between AI’s efficiencies and the core values of trust, equity, and community engagement.

AI-Assisted vs. AI-Driven Assessment

     

AI-assisted systems act as tools that augment human decision-making. These systems help librarians analyze large datasets, forecast trends, and provide actionable insights while retaining human oversight. For instance, predictive analytics can forecast library usage, allowing staff to allocate resources efficiently, while natural language processing helps identify patterns in user feedback for service improvements.

On the other hand, AI-driven systems operate autonomously, making decisions and adapting to real-time data with minimal human intervention. For example, AI-driven tools could automatically reallocate resources or adjust library hours based on real-time user behavior. While these systems offer greater scalability and efficiency, they introduce new challenges related to accountability and governance, requiring libraries to ensure that decisions align with their mission and values.

       

Ethical and Practical Challenges

Both AI-assisted and AI-driven approaches share ethical concerns that libraries must address to ensure successful implementation. These include:

  • Transparency and Explainability: AI systems can often operate as “black boxes,” making it difficult for users to understand how decisions are made. Libraries must prioritize tools that offer interpretable outputs and communicate how decisions are derived.
  • Bias and Fairness: AI systems are vulnerable to biases embedded in their training data. Regular audits and diverse datasets are essential to mitigate the impact of bias and ensure equitable outcomes.
  • Data Privacy and Security: Libraries must protect user data, complying with privacy regulations while ensuring transparency about how data is used in AI-driven assessments.
  • Accountability and Oversight: In AI-assisted systems, human oversight ensures accountability. However, AI-driven systems require robust governance frameworks to define responsibility and ensure alignment with institutional values.

The Future of AI in Library Assessment

The future of library assessment lies in the careful integration of AI technologies. Starting with AI-assisted tools and gradually transitioning to more autonomous AI-driven systems allows libraries to explore AI’s capabilities without sacrificing oversight and control. As AI technologies continue to evolve, libraries must remain adaptable, ensuring that ethical considerations guide their implementation.

The rise of AI agents—autonomous systems that can make decisions and adapt to changing data—holds promise for the future of library services. These systems can optimize operations in real-time, making dynamic adjustments to staffing, resource allocation, and user engagement. However, the increased autonomy of these systems requires careful planning and governance to maintain user trust and ensure that decisions align with library values.

Conclusion

The integration of AI in library assessment represents a pivotal moment in the evolution of library services. AI offers transformative opportunities to enhance efficiency, scalability, and precision, but it also introduces significant challenges that libraries must address. By starting with AI-assisted tools and transitioning to AI-driven systems gradually, libraries can unlock the full potential of AI while maintaining ethical oversight, transparency, and community engagement.

As libraries embrace AI technologies, they must balance the efficiency and scalability AI offers with the core values that have always defined the library mission: equity, accessibility, and trust. By thoughtfully integrating AI into their operations, libraries can continue to serve their communities in innovative ways, ensuring that technology supports rather than replaces the human expertise that lies at the heart of library work.

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