Research Assistance

Use AI to clarify concepts, generate new ideas, narrow or expand a topic, suggest outlines that you can then edit and expand upon. Ask questions for clarification and greater understanding. Explore diverse perspectives. Get feedback on ideas.

Academic Honesty and Plagiarism

The use of AI in academic research requires honesty and accountability. Most writing and citation styles ( e.g., APA, MLA, Turabian) require disclosure of AI assistance for transparency and to avoid plagiarism. For style recommendations and guidelines see the following

APA Style - opens new windowHow to cite ChatGPT
MLA Style - opens new windowHow do I cite generative AI in MLA style?
CSE Style - The Council of Science Editors recommends treating AI-generated content as personal communication. See the Citations page for citation details.

Always follow your professor's instructions on the scope of using AI in your course.

Within academia, artificial intelligence (AI) introduces both opportunities and challenges, including concerns of bias, accountability, integrity, and transparency. Students must critically evaluate and approach AI information with a critical eye to ensure the validity, reliability, and trustworthiness of their findings rather than just accept AI information without evaluation. AI is a tool that does not replace your thinking, research, or writing.

The challenges outlined below are connected to the Association of College & Research Libraries' (ACRL) Framework for Information Literacy for Higher Education. They highlight essential aspects of information literacy, including responsible, ethical, and effective use of AI in academic research.

Bias Awareness

AI and research are not neutral. Bias can appear in:

• Researchers and authors influence outcomes by choices about what gets published, framing, funding bias, or what is studied
• Articles and sources reflect editorial decisions, funding interests, and audience expectations
• Data and algorithms may contain biases from how data is collected, labeled, and analyzed.
• AI outputs may be unethical, inaccurate, or misleading, often unintentionally reinforced through skewed or incomplete training data, question interpretation, or design choices.

Framework Connection: Authority is Constructed and Contextual - Expertise and credibility vary by situation. Authority should always be examined in context. (Information resources reflect their creators' expertise and credibility, and authority is a type of influence recognized in various forms and contexts. Information possesses several dimensions of value, including as a commodity, as a means of education, as a means to influence, and as a means of negotiating and understanding the world.)

Accountability

Responsible research is clear, honest, and ethical. Students must recognize that information has value and must be handled responsibly to ensure transparency, honesty, and integrity in scholarly inquiry and reporting methods and findings.

• Include methods and findings transparently.
• Acknowledge the limits of AI tools in your research process.
• Consider authorship and originality. AI tools (like ChatGPT) are not authors.

Accountability prevents unethical use and creates and fosters responsible knowledge creation and dissemination.

Framework Connection: Information Has Value - Information possesses several dimensions of value, including as a commodity, as a means of education, as a means to influence, and as a means of negotiating and understanding the world.

Data Integrity

Accuracy matters. AI can "hallucinate" or generate false information. Critical evaluation of information sources is important and crucial when using AI tools. Students must:

• Evaluate all sources for credibility and reliability.
• Cross-check AI information against scholarly sources.
• Maintain high ethical standards by citing only verifiable information.

Framework Connection: Information Creation as a Process - Information in any format is produced to convey a message and is shared via a selected delivery method. Research involves recognizing that it is a process, as well as understanding the various ways information is created and shared..

Transparency and Openness

• Recognize the limitations and biases of AI-generated content.
• Evaluate AI sources within their context (e.g., inputs, training data, algorithms).
• Compare AI outputs with scholarly authority and established research.

Framework Connections:

• Authority Is Constructed and Contextual - Information resources reflect their creators' expertise and credibility, and authority is a type of influence recognized in various forms and contexts.
• Information Creation as a Process - Knowing how AI systems produce information helps student awareness of limitations and potential biases.

Publisher submission policies and academic publishing standards vary on whether or not to allow AI-generated images, videos, and/or text. As AI tools and use evolve, policies and standards are likely to be revised.

Some publishers strictly prohibit AI-generated text and images that are not pre-approved by the editor, while other publishers may allow AI-generated text, but not AI-generated images or videos. Or, publishers that allow AI-generated text may require disclosure of the AI text and models used.