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Artificial Intelligence (AI) Library Guide

Rethinking Research with AI

Generative AI tools can support researchers by helping to visualize source connections, generate keywords, and assist with literature reviews. While these tools can enhance the research process, they are meant to supplement, not replace, traditional research methods. AI tools don’t search all scholarly literature and may produce inaccurate or repetitive results. Therefore, it remains essential to verify all AI-generated content using library databases and apply critical evaluation. If permitted by your instructor, AI use must always be cited appropriately.

Using AI Tools in the Research Process

Generating ideas for a research paper topic can often be challenging, and it is common to feel uncertain about where to begin. Engaging with generative AI can stimulate the development of ideas and reveal specific perspectives or subtopics related to the issue that might not have previously been considered or recognized.

Although generative AI can effectively map out potential ideas and concepts, it is important to note that these tools are generally not well-suited for locating reliable academic sources. Use AI as a starting point to inspire your thinking, and then turn to scholarly databases and reputable search engines (such as Google Scholar or your institution’s library resources) to locate credible sources once you have selected a researchable topic.

Key Considerations Prior to Beginning

Generative AI tools are trained on vast datasets, some of which may include inaccurate or biased information. As a result, the responses you receive—whether text, images, or video—may contain errors or misrepresentations. These tools can also "hallucinate," meaning they may provide false information or fabricate sources entirely. Always verify the accuracy of any topic or claim presented by AI using trustworthy academic sources.

If something in the AI-generated response seems questionable, trust your instincts and investigate further using credible tools. The research you conduct afterward will help ensure that the topic you pursue is both factual and viable.

Finally, remember to acknowledge and cite your use of generative AI in your academic work, according to the recommendations of the Cyprus University of Technology for the Use of Artificial Intelligence in Education and Research.

Effective Techniques for AI-Assisted Brainstorming

To make the most of AI tools during the brainstorming phase, follow these recommended steps:

  1. Define your general topic area: Start with a broad subject you're interested in, such as "social media" or "environmental issues.
  2. Select an appropriate AI tool..
  3. Formulate a clear and specific prompt: For example:

“How is the use of AI and adaptive learning platforms affecting student performance in universities?”

“What are the implications of automation and AI on job displacement in the manufacturing industry?”

  1. Review and refine the prompt based on the usefulness of the AI's initial response. This is a dialogue—ask follow-up questions to explore or narrow down the ideas provided.
  2. Repeat the process. Starting over with a slightly different prompt or trying another AI tool can yield new results, as responses vary with each interaction.
  3. Critically evaluate and verify the output. Use your own judgment and reliable sources to confirm the accuracy and relevance of any ideas generated.
  4. Be mindful of ethical concerns, including the potential for bias, issues of privacy, and proper citation of AI assistance in your final work.

Identifying strong keywords is essential for effective library research. In addition to consulting librarians, thesauri, and academic sources, AI tools like ChatGPT can assist in generating relevant terms.

  1. Introduce Your Topic

Briefly describe your research focus. Example:
“I am a master's student researching the ethical implications of artificial intelligence in healthcare.”

  1. Request Keyword Suggestions

Use prompts such as:
“Can you suggest relevant keywords for this topic?”
or
“What are some search terms related to AI and healthcare ethics?

  1. Review and Refine

Evaluate the suggestions for relevance and precision. Add or revise terms based on your understanding of the subject.

  1. Follow Up for Specific Areas

Request more targeted keywords as needed (e.g., “Can you suggest additional terms related to data privacy or algorithmic bias in medical AI?”).

  1. Validate and Expand

Cross-check the list with scholarly literature or database thesauri to ensure accuracy and consistency. Continue refining the list as your research evolves.

Evaluating AI-Generated Sources: A Condensed Guide (Based on ACRL FRAMEWORK)

 

  1. Authority is Constructed and Contextual

AI tools are not authoritative sources. Always verify the authorship and expertise of individuals cited.

  • Verify author credentials (Google search, institutional affiliations).
  • Search author in databases (e.g., EBSCOhost, ProQuest) to locate additional publications and assess scholarly relevance.
  1. Information Creation as a Process

AI-generated content lacks peer review and may include fabricated citations.

  • Check citation validity: Confirm that each reference is real and appropriately cited.
  • Locate full texts: Use databases like JSTOR, ProQuest, or publisher websites to verify and access content.
  1. Information Has Value

AI outputs must be used ethically and with proper attribution.

  • Cite AI tools clearly in your work.
  • Avoid using AI content as a substitute for original thought or scholarship.
  1. Research as Inquiry

Use AI as a starting point, not a conclusion.

  • Find relevant literature: Identify 4 peer-reviewed articles on your topic and compare them to AI citations.
  • Refine your research questions through deeper engagement with scholarly sources.
  1. Scholarship as Conversation

AI mimics but does not participate in academic dialogue.

  • Ensure your work reflects real scholarly perspectives and engages with current academic discourse.

  1. Searching as Strategic Exploration 

Effective research goes beyond AI.

  • Use advanced search strategies and academic databases to verify information and locate quality sources.
  • Supplement AI with library resources and expert assistance.

 

Association of College & Research Libraries. (2016, January 11). Framework for information literacy for higher education. American Library Association. https://www.ala.org/acrl/standards/ilframework

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