Pioneering Practical AI in Libraries: Five Lessons from Building ChatGPT Tools
As libraries evolve to meet the needs of digital-age patrons, AI technology offers unprecedented potential to enhance services. At the Palo Alto City Library, I recently shared insights at BiblioCon ‘24 from our journey building ChatGPT-powered tools for library workflows. Here, we’ll unpack the practical lessons learned and how they’re shaping our approach to integrating AI in our library.
Lesson 1: Building vs. Deploying—Start Small and Stay Flexible
Our initial AI experiments focused on building pilot tools rather than rushing into full deployment. ChatGPT’s evolving landscape means new features frequently emerge, offering novel ways to refine workflows, solve problems, or improve efficiency. Each new feature shifts our perspective on deployment, underscoring the value of starting small, experimenting, and remaining adaptable. As these tools develop, balancing flexibility with caution ensures we can pivot as necessary, harnessing new features that align with our library’s needs.
Lesson 2: The Importance of Collaboration—“Invite AI to the Table”
In library tech, blending human insight with AI guidance unlocks new possibilities. ChatGPT’s role in solving complex problems becomes powerful when treated as an active collaborator rather than a mere assistant. During our experiments, we found that presenting ChatGPT with clear problem statements led to better solutions and new use-case insights. For example, combining ChatGPT’s retrieval capabilities with our unique data requirements allowed us to envision AI-enhanced workflows, creating a dynamic partnership where AI truly amplifies our capabilities.
Lesson 3: Streamlining Content Creation and Summarization
One of the most practical applications of ChatGPT in our library has been content creation. The ability to generate concise, audience-specific summaries saves substantial time and effort. ChatGPT’s proficiency in rephrasing text to target diverse audiences has made it invaluable, from drafting blog snippets to summarizing lengthy documents. This AI-assisted approach enables us to communicate more effectively, tailoring content to resonate with various patron demographics while maintaining clarity and engagement.
Lesson 4: Leveraging AI for Visual Content Creation
Image generation with ChatGPT’s partner tools, like DALL-E, has opened doors to fresh and creative ways to enhance our library’s visual media. In the past, we relied heavily on stock photos, but now we can craft visuals tailored to our brand and themes. AI-generated images offer flexibility—whether creating thematic displays, customizing blog headers, or enriching social media content. These tools allow us to build a robust, unique media library that reflects our library’s values and story in a meaningful way.
Lesson 5: Retrieval-Augmented Generation (RAG)—Fast, but Verify
RAG enables ChatGPT to access and cite knowledge bases, potentially turning it into a responsive, citation-ready information source for staff and patrons alike. However, we’ve discovered that while RAG’s setup is straightforward, maintaining it requires a commitment to quality control. As with any AI tool, results need consistent vetting, particularly in areas like accuracy and relevance. We’re still evaluating whether RAG or emerging options, like advanced search features, provide the most reliable and user-friendly AI solution for our library.
Looking Ahead: Local Language Models and Privacy Considerations
For libraries, data privacy is paramount. While ChatGPT and similar tools continue to revolutionize digital services, we’re exploring the potential of in-house AI models, which offer enhanced control over data and privacy. As more libraries adopt AI, decentralized models—where data never leaves the library—could help address security concerns, ensuring patrons’ information remains confidential.
In Summary
Integrating AI into library services is both challenging and rewarding. At the Palo Alto City Library, we’re embracing this journey one step at a time, balancing innovation with ethical considerations, and prioritizing tools that align with our mission. Each experiment reveals new insights, helping us refine a strategy that’s uniquely suited to our library and the patrons we serve.
As we continue to navigate the AI landscape, the lessons we’ve learned provide a solid foundation for future endeavors. We hope that by sharing these insights, we inspire other libraries to embark on their own AI journey, harnessing the power of technology to support our shared mission of organizing knowledge and enhancing community access.
