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Use of Generative AI
Generative AI presents a range of intrinsic problems for scholars which we have analyzed in our recent papers. (Please read them!) With our CGMap application, we have calibrated the technology to do only those things that it does well. However, if you decide to use Generative AI through publicly available interfaces, as well as being extremely cautious of their deficiencies for scholarly work, also we require you to provide: a) your prompts; b) output text, with before/after highlighted to indicate the impact of the AI on the work (e.g. use “compare documents” in Word); and c) a change note analyzing your experience of advantages and disadvantages in use. Please review for the broad picture the University’s website https://www.vpaa.uillinois.edu/digital_risk_management/generative_ai/. Be sure you are familiar with the basic benefits and deficiencies of these models (bias, temporal limits on content, hallucinations etc.), and have a basic understanding of how they operate.
Illinois Student Code
The Illinois Student Code is considered as a part of our courses’ syllabus. Students should pay particular attention to Article 1, Part 4: Academic Integrity.
Read the Code at the following URL: https://studentcode.illinois.edu/ and complete the student Academic Integrity training course through enrolling at this link: https://canvas.illinois.edu/enroll/PXCHNG.
IMPORTANT!
Academic dishonesty may result in a failing grade. Every student is expected to review and abide by the Academic Integrity Policy: https://studentcode.illinois.edu/article1/part4/1-401/
All the work you do in this course is very visible. Not only is plagiarism a terrible idea; it will be obvious in ways that is not obvious in traditional course formats because your work will be seen by many eyes. Fortunately, for these reasons, we experience very little plagiarism in our courses. However, just in case, here are some rules, additional to the University’s standard rules.
- Citing Peers: This is a collaborative knowledge community. We want you to learn from each other’s work, as much as from the resources that we provide and that you identify. When you have learned something from a course participant, please cite the source. This might be an update they have made, or a peer-reviewed work. Include author, title, and a weblink as your citation.
- Self-Plagiarism: Do not self-plagiarize, or copy work from previous updates or works, or other courses. All work must be new. If you want to refer to earlier work, cite it, including author, title, and a weblink as your reference.
- Generic Evaluations: Do not copy/paste generic review text or annotations (an old teacher’s trick, we know, when faced with the chore of grading). Comments and annotations must be tailored to a specific work.
- Appropriate Use of AI: See above
Responsibility to Report
If you notice any problems with a work or the reviews you receive (for instance, plagiarism or reviews which are cut/pasted or offensive), you must inform the teaching assistant or instructor, no matter how uncomfortable you may feel to do this. This is for the sake of the offender as much as anything else—offending in another place may have even more serious consequences.