Ivar Björnsson
Lund University
Responses
Sometimes it feels as if AI arriving has sucked all the joy out of being a teacher.
I feel you and I will keep this short as I think many important points have already been raised in previous responses. For me, teaching is a very personal activity, and I realize I have more of an emotional connection with my teaching than I do with my research. I genuinely believe that this has helped my become a better teacher although it can be quite draining at times. When this happens, I usually talk with my close colleagues and family. These exchanges don't always end with a clear answer to whatever problem I'm facing, but it still helped me to deal with it internally, finding new perspectives and giving me added energy to continue working towards some solution (or at least acceptance so I can focus on other tasks). Have you brough up this issue with any teaching colleagues? It may be that some of them share your reaction or at least sympathize with it. What made teaching enjoyable before - try to remember specific memories and examine these? I would suggest that you, together with close and trusted colleagues, try to isolate what it is specifically that has become less fun - and then try to find ways of mitigating this. If nothing else, maybe the process of talking about it will help (that's been my experience at least).
Can we "force" students to use AI?
I think you bring up a very relevant and interesting issue which I don't think we as teachers or the institutions we teach at currently consider enough - the sustainability impacts of using genAI. These issues are also relevant for other aspects of modern living which is very much reliant on digital infrastructures and systems. These require rare metals and energy to create and run, are often designed for obsolescence so they have to be replaced within certain time spans, and can have negative impact to environment as well as to our society. But I'm getting a bit off track here... When it comes to 'forcing' students to use generative AI (or any digital tool for that matter), I think it is important that the question should asked: what is the underlying learning outcome in this situation or simply, what do I want the students to learn? In my experience from teaching courses within structural engineering I've found it difficult to answer that question with 'to learn how to use a certain tool'. It may, of course, be that this is not the case in other fields. However, I dare say that it is common within many disciplines that the specific tools that professionals use likely change over time - so a necessary learning outcome may be to learn to adapt to this change and get a deeper understanding for what it is that these tools actually help with doing and, more importantly, where the human element factors into this equation (i.e., why do we need the human operator if we are only interested in the output from the tool?). As a researcher, I've previously delved into this issue (pre-genAI) in relation to my discipline. Over multiple decades, the paradigm within professional structural engineering practice has shifted towards a greater reliance on advance computational software. This software, as with genAI, was (and is) becoming more sophisticated and user friendly, meaning that the threshold for being able to use them (in terms of disciplinary knowledge, judgment and competences) was decreasing over time (while the complexity of what they could help create increased). As a teacher, I noticed that students using these tools would often ask questions like, 'how do I get the program to work', rather than, 'is this a good solution'. My approach was to put more emphasis on improving students conceptual understanding of structural behaviour and analysis, giving them the opportunity to develop, appreciate and apply sound engineering judgment, as well as generally adopt a holistic, critical and inquisitive approach. This provided them with the knowledge, competence and judgment to be able to evaluate whether the output from these software was good enough, if there were any errors (e.g., due to poor assumptions, boundary conditions, or input errors), and what could be done to improve the overall design. I've often wondered whether there is a parallel with generative AI - i.e., something that allows students to be able to effectively and with confidence assess the output of generative AI to know when it is good or not, whether it was the right question(s) to ask, knowing what to do with the result(s), etc? In any case, I don't think we should ban genAI (as this is a bit naive) and I am sceptical to 'forcing' students to use it (at least in my field). If, however, I were to 'force' this onto the student, I would need to be able to clearly and confidently communicate with the students why this is the case (and be myself convinced of this) and also think carefully if there are any other ways to fulfil the expected learning outcomes in the course? As with a lot of other issues in teaching and learning, you can go a far way by talking with your students.
How can I teach ethics of AI use?
I think it's good to be transparent with the student in letting them know that there is no easy answer to 'what is ethical use of AI'. I recently had a focussed seminar on ethics in engineering for first year students and started off by having students actively discuss in smaller groups ethical dilemmas that they have experienced, heard of, or could imagine to be relevant for them as students. Generative AI use came up in some of the examples mentioned and it was clear from further probing that many of the students were well aware of the ethical conundrums that AI can impose on us. As the rest of the seminar was focused more specifically on preventative ethics in an engineering context, we were only able to scratch the surface of the ethical issue associated with AI (I think next year I will try to direct some more focus on this topic). In any case, I realized that having these types conversations, and normalizing them both inside the classroom (with our students) as well as outside (with colleagues) is an important prerequisite to actively working towards a shared best practice for what is ethical use. In this paradigm, we as teachers maybe also need to let go of the necessity of always being the experts on the topics we bring up with students. I would prefer that students actively come to me with their questions and concerns about what is ethical AI use, us having an open discussion about it - weighing various pros and cons - without providing a definitive answer. Hopefully over time we may come up with clearer answers to what is ethical use of AI. In the meantime, I think it's important that we all talk about it!