I’m Michael Rowe. I’m an academic and researcher working on technology-enhanced scholarship and artificial intelligence in health professions education. I’m also the Director of Digital Innovation in the School of Health and Care Sciences at the University of Lincoln.
This site is where I write and think about scholarship — how we learn, how we teach, how we create and share knowledge. I’ve spent my career exploring these questions, first in health professions education, now increasingly at the intersection of AI and academic practice.
Emergent scholarship is both the name of this site and an ongoing inquiry: what does it mean to do scholarly work when the tools, contexts, and expectations keep shifting? I don’t have answers so much as working notes, arguments in progress, and the occasional conviction.
What I’m working on
Right now I’m exploring how AI changes the nature of academic work — not just the tools we use, but what counts as expertise, how we assess learning, and what “scholarship” even means when content generation is trivial.
I’m also developing an AI literacy course for academics, and writing about the alignment problem in education.
Featured
Post - A bitter lesson in education: Rich Sutton’s “Bitter Lesson” showed that general computation beats human-crafted expertise in AI. Higher education faces a parallel lesson - our complex assessment frameworks, built on the difficulty of artifact generation, are collapsing now that AI makes content production trivial.
Essay - Taste and judgement in human-AI systems: This essay introduces taste as a framework for cultivating contextual judgement through iterative experimentation and reflection that enables discernment about when, how, and why to engage AI capabilities in service of personally meaningful purposes.
Course: AI literacy for academics. This course develops comprehensive AI literacy across six interconnected dimensions, using a developmental framework that moves from basic competence through adaptation to transformation.
Explore
Browse by format (essays, posts, notes, courses) or by topic.
The graph view in the top right section shows how ideas connect across the site. The local graph updates depending on what you’re currently looking at. Click any node to navigate there, or use the global view (small graph icon in the top right) to see the full network. It’s a way to discover related ideas you might not find through linear browsing.
This site works a bit like an open source project: I work in public, ideas develop through iteration, and the process is part of the output. If something here is useful, use it. If you want to respond, get in touch.