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.