Kirsty Dunnett
Responses
Can my student use AI to redraw a copyrighted image to include in their thesis?
For me, at least, the underlying ethical issue is that the (to a non-expert blatant) abuse of copyright in training generative AI is no excuse to disregard it in one's own practices. (See also the recent Amnesty International report.) Open a reference book or a work of fiction published since 1988 and with an author who has been dead for less than 50 years (I use 50 because that's the US copyright limit; in Europe it's 70 years). On one of the first few pages (usually, occasionally it's at the back), you will find something along the lines of: 'No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without prior permission in writing from the publishers'. To me (and I am no expert, but the basics of copyright law are fairly straightforward) it seems clear that copyrighted material, whether from books or research articles that are not published under a creative commons licence, should never be uploaded to an AI without permission from the author or publisher. Even for textbooks that allow for some local or fair use it seems unlikely that this also covers uncontrolled digital distribution - i.e. what happens when an upload is incorporated into a generative AI program's training data. But let's look at it another way: what would the student have done in 2021 (before generative AI was well known and returned at least apparently sensible output)? And what would they (have) learn(t) by doing so? It seems to me that there is an (increasing) addiction to 'pretty pictures', and generative AI images look pretty until one notices the flaws (which might be a lack of floors). Has academic work become nothing more than a fashion show, where 'attractive' has replaced any sort of useful, practical, meaningful, or accurate? Perhaps you can ask the student to sketch (by hand) what they envision a generative AI image to contain. Then there are three options: 1. scan in and include the sketch; 2. create a digital version of the sketch without genAI; 3. scan in the sketch and upload to genAI, asking for a 'pretty' version. Note: with the exception of the students' time, the third will almost certainly use considerably more resources than either of the other two options (https://what-uses-more.com/). And, of course, readers can simply be directed to the original image in its proper place of the original paper.
AI detection tools and even ChatGPT confirm that AI wrote my student’s text, but the student denies it!
Let me start by giving your student the benefit of the doubt: how might such 'AI characteristics' have arisen? Words such as 'thus' and 'leverage' are not exactly common in formal and academic writing - which is often far from 'plain English'. A combination of formal phrasing (including passive voice) and 'jargon' may be what students understand to be 'appropriate academic style'. The student may simply be trying to achieve a 'proper academic style' (or 'voice'), perhaps based on (outdated) formal style guidelines or information about the proper connectives in arguments from school (this could well explain 'thus'). Mimicking what one read last is typical for inexperienced writers 'finding their voice' (see, e.g., King, 2010), so it seems reasonable that a student still learning to write 'academically' will mimic one or more of the papers they refer to most. I also know from my own writing that I go through phases where I use a few words or phrases a lot more than I do at other times, so words used unusually often in one text is not necessarily about generative AI use. It takes more than a few 'characteristic words' to be able to suspect 'this was not written by a human'. Indeed, that students can try too hard, and produce worse work as a result is not new: Kitching (2008) reported students trying too hard to be properly academic and making their work worse as a result — in this case it was about including a confused theoretical discussion, instead of presenting projects as straightforward empirical work, but I think the point of trying too hard to mimic what is perceived as 'correct' and ending up with something that doesn't 'ring true' as it were remains. But there are questions you, as a teacher, have to ask yourself. It's clear now that at least some students will use generative AI for written assignments, but there are a number of ways in which they may use it, all with different implications. I saw a presentation (by André Mathe of the University of Bergen) a few months ago where some lecturers in Norway were interviewed about appropriate uses of generative AI. If I remember correctly, it was typically considered entirely acceptable to use genAI for text editing, and even for idea generation, though the lecturers were pretty much in agreement the the first full draft of the assignment should be the students' own work. So for those lecturers, a student drafting an assignment in everyday, informal language, and then uploading to genAI with a prompt along the lines of 'make more academic' would have been acceptable — and an over abundance of words such as 'thus' and 'leverage' (I'm guessing more common in academic texts than anywhere else) could appear. There are also many things to consider when it comes to exactly why you're inclined to raise the issue to what you suspect may be an AI generated text: a) whether it matters, b) why it matters, c) how it matters, and d) whether (and why and how) it should matter. But the damage you have done your student and their trust in you and perhaps even other academics, however accurate or inaccurate your questioning of them may have been, should not be underestimated. After all, you have the power. Kitching, G. (2008). The trouble with theory: the educational costs of postmodernism. Pennsylvania state university press. King, S. (2010). On writing, a memoir of the craft. 10th anniversary edition. Scribner. André Mathe's talk announcement: https://www4.uib.no/en/research/research-groups/teaching-and-learning-in-higher-education-teled-research-group/events/this-is-not-mine-exploring-the-challenges-metaphors-and-affordances-of-generative-ai-in-design-education; a publication with the same title is somewhere in preparation, so hopefully his observations will soon be available to all.