Integrating AI in Libraries: A Guide for Librarians and Educators

Summary: Integrating AI in Library Practices and Education

This session, led by Julie Erikson, a professional learning specialist and librarian, explores how school librarians can integrate AI tools effectively into their educational practices while addressing concerns about ethics, information literacy, and evolving search methods. Julie emphasizes collaboration with educators, AI literacy, and practical resources for navigating this rapidly changing landscape.

Key Themes

1. Librarians as AI Leaders:
   • Librarians play a critical role in teaching AI literacy, promoting ethical use, and supporting digital citizenship.
   • Building connections between curriculum and library resources enhances relevance and engagement.
2. Bridging Gaps in AI Knowledge:
   • Many educators and librarians are still unfamiliar with AI or lack professional development opportunities.
   • Developing a comfort level with AI requires hands-on practice, experimentation, and exploration of available tools.
3. Ethics and Privacy in AI Use:
   • Importance of understanding AI terms of use and data-sharing practices.
   • Avoiding the inclusion of personally identifiable information (PII) in queries.

Practical Applications and Resources

Teaching AI Literacy:

• Digital Citizenship and Media Literacy:
  • Helping students differentiate between information and disinformation.
  • Engaging in discussions about vetting sources and promoting critical thinking.
• AI in Everyday Life:
  • Highlighting how AI integrates into daily tools such as Google Translate, Gmail, and Amazon recommendations.

Exploring AI Tools:

• Prompts and Search Strategies:
  • Teaching iterative prompting for AI tools, similar to advanced search techniques.
  • Utilizing resources like Microsoft's colorful prompt guide to structure effective queries.
• AI-Driven Resource Guides:
  • Using AI tools to create timelines, resource guides, and starter projects for educators and students.

Collaboration with Educators:

• Classroom Integration:
  • Joining Google Classrooms to share resources and maintain alignment with curriculum.
  • Tracking teacher homework calendars to prepare relevant library materials proactively.

Ethical Considerations and Policy Development

1. Privacy and Data Security:
   • Discussing data-sharing policies of popular AI tools with students and teachers.
   • Advocating for transparency and ethical use of AI in schools.
2. School and State Policies:
   • Developing clear guidelines for AI use in schools.
   • Balancing accessibility with security, ensuring equity for students without home access to AI tools.
3. Citations and Academic Honesty:
   • Educating students on how to cite AI-generated content properly.
   • Encouraging lateral reading and source verification for AI-generated outputs.

Takeaways for Librarians

1. Lead by Example:
   • Use AI tools to demonstrate ethical, creative, and collaborative practices.
2. Stay Informed:
   • Follow blogs, podcasts, and AI thought leaders to remain updated on emerging tools and trends.
3. Support Equity:
   • Advocate for balanced AI access in schools to ensure all students benefit from the technology.

The Evolving Role of AI in Research and Education: Ethical and Practical Considerations

Summary of Ethical and Practical Considerations for Generative AI in Research and Education

This session, presented by an associate teaching professor from Rutgers University with over 40 years of library experience, explores the evolving role of AI in research and education. The focus includes ethical concerns, practical applications, and strategies for using generative AI tools effectively and responsibly.

Key Themes and Objectives

1. Generative AI as a Research Partner:
   • We are integrating AI into research processes using trusted content and modern strategies.
   • Encouraging AI literacy as a foundational skill within broader information literacy frameworks.
2. Ethical Considerations:
   • Transparency in AI use.
   • Academic honesty and guidelines for student research.
   • She was addressing equity and privacy concerns.
3. AI and Leadership in Libraries:
   • Librarians as leaders in adopting AI tools.
   • Modeling ethical AI use for students and educators.

The Changing Landscape of Research

Traditional vs. Semantic Search:

• Traditional search relies on keywords and controlled vocabularies.
• Semantic search uses natural language processing (NLP) to interpret queries more contextually, enabling more prosperous, more relevant results.

Future of Research Tools:

• Natural Language and Multimodal Search:
  • AI now supports searches across text, video, and images.
  • Example: Searching for "best restaurants in NYC" semantically includes synonyms like "top" or "fine dining."
• Control F for Concepts:
  • Extends traditional keyword search to identify related concepts across datasets.

Practical Applications of AI in Education

Student-Facing AI Tools:

• Brainstorming and Generating Research Ideas:
  • Example: Identifying Latina poets and their notable works.
• Building LibGuides and Research Portals:
  • AI can generate starter content for academic resources, such as libguides or timelines.

Educator-Facing Tools:

• AI-Enhanced Cataloging:
  • Tools can generate MARC records and catalog outputs automatically.
• Simplifying Complex Texts:
  • AI can reduce reading levels or translate texts for ESL learners.

Emerging Database Integrations:

• RAG (Retrieval-Augmented Generation):
  • AI integrates with trusted databases, ensuring students access vetted, high-quality sources.
  • Examples: Perplexity AI and beta programs from ProQuest, Gale, and JStor.
• Personalized Content Recommendations:
  • AI can offer recommendations based on context, akin to a "Spotify for research."

Ethical Considerations in Using Generative AI

Key Issues:

1. Transparency:
   • Require students to reflect on the origin and role of AI in their work.
   • Highlight the importance of sourcing and accuracy.
2. Bias and Equity:
   • Recognize biases in AI models stemming from imbalanced training data.
   • Ensure inclusivity and diverse perspectives in AI-generated content.
3. Copyright and Fair Use:
   • Discuss challenges with using copyrighted materials for AI training.
   • Clarify policies for responsible AI use in schools.
4. Privacy and Security:
   • Highlight the importance of protecting student data in AI tools.

Strategies for Addressing Academic Honesty:

• Reflection and Transparency:
  • Require students to document AI's role in their research process.
• Interrogating AI Output:
  • Teach students to verify AI-generated information using critical thinking models like SIFT.

AI Tools and Resources

Safe AI for Schools:

• Perplexity AI (13+): Academic-focused AI tool offering contextualized answers and citations.
• JStor Beta and Gale Products: AI-powered academic tools integrate semantic search and controlled vocabulary.
• Microsoft Search Coach and Search Progress: Designed for safe and effective research skill development.

AI for Debate and Research:

• Tools like Consensus provide pro-con summaries on controversial topics.
• AI can identify primary sources and suggest case studies tailored to classroom needs.

Best Practices for Librarians and Educators

1. Encourage Ethical AI Use:
   • Develop clear policies for using AI in research.
   • Promote transparency and creativity in student projects.
2. Embrace Evolving Search Technologies:
   • Stay informed about AI advancements in academic databases.
3. Lead Conversations on Academic Integrity:
   • Use AI to enhance, not replace, traditional research skills.