Just the principles ...
Three principles for AI in the academy.
This letter is about three principles that apply to AI contributions in an era of digital thought.1
An AI cannot pass a course.
AI contributions must be attributed and true.
AI use should be open, and documented.
(A) We must define that an entirely AI generated contribution can at best only achieve a grade just below a pass. You might object that that makes our courses significantly more difficult than they used to be, and you would be right, but also perhaps not. First: you are right – but we have no choice. Either we learn to surpass the AI, or the AI becomes a competitor. Second: you may not be right – the requirements will be higher, but the AI can help to make it less difficult to achieve them. That will depend on how we put this into practice.
(B) Whatever contribution the AI makes, the final product must attribute the source of the ideas, and the contribution must be factually correct. That sounds trivially true in scholarship, but here it is not: the source of the AI’s ideas may be challenging to identify, and sometimes the AI is absolutely and confidently incorrect. That’s not even rare.2
(C) Whether students or educators, we are in this together. If we assume everything is AI produced, cheating becomes impossible – and once that is out of the way, we can focus on what matters: education.
The consequences are straightforward: use the AI to be better, do so with integrity, gather experience and learn. It will be fun.
For ideas and resources to put this into practice, you can look at the files linked above, or visit the Sentient Syllabus website linked from the image below.
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Cite: Steipe, Boris (2022) “Just the Principles …”. Sentient Syllabus 2022-12-29 https://sentientsyllabus.substack.com/p/just-the-basics .
Though, when you point out the error, you will usually get a remorseful apology, and a long-winded explanation why you are right. The AI had the “knowledge”, it just did not know.