Generative Artificial Intelligence

Considerations for Using AI Tools in Library Research

When using AI tools for library research, it is essential to approach them critically, recognizing both their capabilities and limitations. Generative AI, including chatbots powered by Large Language Models (LLMs), can summarize text, generate ideas, and respond to queries in a way that mimics natural conversation. These tools generate responses based on statistical patterns in vast pre-trained datasets rather than true comprehension. While useful for exploring topics, their accuracy depends on the quality of their training data, which may contain biases, outdated information, or undisclosed sources. Because AI-generated content is based on probabilistic predictions rather than verified facts, its outputs are not guaranteed to be accurate or ethically sound. Researchers should critically evaluate AI-generated information, cross-check sources, and ensure academic integrity in their work.

AI tools can be powerful allies in academic research, offering new ways to gather, analyze, and synthesize information. However, it's essential to approach their use thoughtfully. Below are key considerations to keep in mind:

Understand the Tool’s Purpose: AI tools are best used for support tasks—like brainstorming or summarizing—not as definitive sources. They should supplement, not replace, traditional research strategies.

Evaluate Credibility: AI outputs may not reference peer-reviewed sources. Always verify claims against scholarly materials available through your library.

Maintain Academic Integrity: Use AI ethically. Cite its contributions appropriately, and follow institutional guidelines to avoid plagiarism or misuse.

Protect Your Privacy: Avoid inputting sensitive or personal information. Many tools store data externally, raising security concerns.

Generative AI Product Tracker

Generative AI can help and supplement the research process, but it should not replace the entire process. Generative AI tools can be used to help: 

• Brainstorm and explain complex concepts

• Discover trends or sources and visualize relationships between ideas

• Summarize texts

• Draft or revise writing

• Edit content for clarity or consistency

• Organize and manage data

• Generate images, code, and multimedia materials

• Translate or convert written materials into audio to enhance accessibility

AI can be a valuable productivity aid when paired with human judgment and scholarly practices.

While generative AI can be used as a tool in the research process, there are limitations and considerations including: 

• Despite its benefits, AI presents several limitations that researchers must acknowledge:

• Bias: Reflects systemic biases in training data

• Inaccuracy: May produce outdated, incorrect, or unverifiable content

• Citation Gaps: Often lacks transparent or scholarly sourcing

• Limited Access: Cannot retrieve paywalled or subscription-only academic content

• Reproducibility: Outputs are often unique and cannot be exactly replicated

• Ethical & Legal Concerns: Raises questions around plagiarism and intellectual property

• Privacy & Security Risks: Potential exposure of personal data

• Environmental Costs: High computational energy use

• Outdated Information: AI may not reflect the most recent developments or research

Additional resources: 

• The Alan Turing Institute - Understanding artificial intelligence ethics and safety (PDF)

• The Ethical Framework for AI in Education (PDF)

• Ethical data and AI groups

TLS, UT Libraries. LibGuides: Artificial Intelligence (AI): Benefits and Limitations. https://guides.lib.utexas.edu/c.php?g=1363366&p=10085246. Accessed 11 Mar. 2025. 

ChatGPT. “Response to a Query about the Benefits and Limitations of Generative AI.” ChatGPT, OpenAI, 11 Mar. 2025, https://chat.openai.com.