Generative artificial intelligence is increasingly pervasive in higher education, embedded in everyday applications and already forming part of staff and student workflows. Yet doubts remain manifold. On the teaching side, colleagues are concerned with the technology’s potential to enable plagiarism while also being excited about the prospect of its doing lower-level work, such as expediting basic computer coding, that makes space for more advanced thinking. On the research side, various techno-solutions are being pushed that are meant to speed up crucial processes, such as summarising reading, writing literature reviews, conducting thematic analysis, visualising data, doing referencing and even peer reviewing.
Saving time is all well and good. But efficiency is rarely the core norm driving scholarship. The only way to know if and how to adopt generative AI into our teaching and research is through openly deliberating about its impact on our main values with colleagues and students. Those values must lead and shape the technology we use, not the other way around.
