Artificial Intelligence (AI)

• Do check with your professor about the use of generative AI for assignments
• Do use AI to help write difficult pieces of code
• Do review AI-generated content

• Don't accept all of Grammerly's suggestions without reviewing each one 
• Don't use a generative AI to write your whole paper
• Don't use AI to create a work cited page, often many of the citations are hallucinations. 

This checklist is from the 2025 Student Guide to Artificial Intelligence by Elon University and AAC&U.

Accuracy and source check

• Verify all facts, statistics, and data points with multiple reputable sources (academic journals, government publications, respected news organizations); don't rely on a single source
• If the AI cites sources, check those sources directly; if the AI cannot cite a source, disregard the information
• Watch for outdated information; confirm the publication date of the source material
• Try the same prompts in multiple AI tools and traditional search engines and compare the results

Bias check

• Ensure the content presents multiple perspectives and does not omit certain viewpoints or promote stereotypes
• Check original sources to see if they favor a specific viewpoint, ideology or group
• Use critical thinking to evaluate information that seems slanted to serve business, government or advocacy interests, or influence buying decisions

Logical consistency check

• Ensure the arguments being presented flow logically and make sense
• Watch for broad generalizations from limited evidence
• Look carefully for contradictions or misleading jumps in reasoning
• Assess the depth of reasoning and avoid simplistic analysis

Emotional and manipulative language check

• Look for content that uses neutral, fact-based langague; be ware of language that is overly dramatic or inflammatory
• Watch for loaded words designed to provoke emotions (fear, anger, excitement) or influence opinions or actions

According to the Association of Research Libraries: Artificial intelligence (AI) technologies, and in particular, generative AI, have significant potential to improve access to information and advance openness in research outputs. AI also has the potential to disrupt information landscapes and the communities that research libraries support and serve. The increasing availability of AI models sparks many possibilities and raises several ethical, professional, and legal considerations.

This is a non-exhaustive list of considerations:

• Accuracy
• Bias
• Copyright
  • Unauthorized inclusion of others' works
  • Rights and Attribution
• Equity - available to those who can pay for the premium version
• Sustainability and energy consumption
• Security and privacy
• Unknown data sources

Information in this section was gathered from the sites below: