This section covers ethical considerations when using or encountering AI. Being AI literate means not only knowing what AI can do, but also thinking about what should (or shouldn’t) be done with AI.
Using AI in an academic setting raises questions of plagiarism and honesty. At Fort Lewis College (and any institution), AI use must be acknowledged. If an AI helped you write something, failing to mention that amounts to unacknowledged assistance. On the other hand, thoughtful use of AI (with permission) – such as brainstorming ideas or getting feedback on a draft – can be done ethically if you credit the AI’s role and still produce original work. Never misrepresent AI-generated work as solely your own. Remember that AI can generate false or mis-cited information; passing that along without verification can lead to academic misconduct.
Faculty decide whether any type of AI tool is allowed in a course or on an assignment. If you don't know whether or not a specific tool or use of a tool is allowed for a particular assignment, please check with your instructor.
AI tools can introduce legal risks, particularly in areas where intellectual property, liability, and regulatory compliance intersect. AI tools may generate content replicating copyrighted material without permission. Users and institutions could face legal liability if this content is distributed or used without proper attribution or licensing.
Case law regarding AI is still developing. As of the time of writing, in the USA, AI produced content is not covered by copyright.
The Library licenses content from publishers and database vendors. Our contracts with these vendors restrict how content may be used.
You cannot use content from licensed Library e-resources in conjunction with AI technologies, including copy and pasting content into GenAI tools, like ChatGPT, unless the vendor expressly permits it.
For more information, please see our FAQ on this topic.
Major style guides have published guidelines on citing AI tools. Remember to check with your instructor to see if there are any instructions related to citing AI specific to that course/assignment.
There are no formal IEEE style guidelines for citing content produced using generative AI. You may thus try citing this content following the "Unpublished" content type style guidelines (page 16).
IEEE requires content generated by AI to be "disclosed in the acknowledgments section of any article submitted to an IEEE publication." (link)
AI systems can unintentionally perpetuate biases present in their training data. For example, a facial recognition AI was found to perform worse on darker-skinned faces than lighter-skinned, reflecting biases in the data used​. Similarly, generative AI image tools have been shown to amplify racial and gender stereotypes if not carefully managed​ (MIT Sloan Teaching & Learning Technologies, 2024). It’s important to understand that AI outputs are only as “fair” as the data and algorithms behind them. Ethical AI use involves recognizing these biases and working to mitigate them. As AI users, we should question whether an AI’s result might be skewed or if certain groups are underrepresented in its data.
Dr. Joy Buolamwini discusses her research on how AI trained to recognize human faces is better at recognizing some than others. She highlights the importance of training AI on datasets that represent diverse populations accurately.
AI tools often require inputting user data or prompts, but think before you share. Treat AI platforms as public spaces. Do NOT input personal, confidential, or sensitive information into an AI tool unless you’re sure of how that data will be used. Many AI services save user inputs for model improvement. There may be language in the Terms of Use that would surprise you. Use AI with the assumption that others might eventually see what you’ve entered. Paid versions of specific software might offer more protection in terms of privacy, but these are dependent on specific language in specific plans. Read Terms of Use to be sure of what's happening with your inputs!
MIT Sloan Teaching & Learning Technologies. (2024, November 12). When AI Gets It Wrong: Addressing AI Hallucinations and Bias - MIT Sloan Teaching & Learning Technologies. https://mitsloanedtech.mit.edu/ai/basics/addressing-ai-hallucinations-and-bias/
This work by Fort Lewis College Reed Library is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Portions of this guide were modified and reused from MIT Libraries' Citing AI guide.