A weekly letter at the intersection of artificial intelligence and education — gathered, threaded, made short.
Each issue gathers a selection of recent papers around a single theme, for example assessment, simulation, faculty attitudes, student wellbeing, and threads them into one short essay. The aim is coherence, not coverage.
Occasional features explore the tools and methods of the trade; for example, the best AI assistants for medical educators, how to write a better MCQ, what we still get wrong about feedback.
Who it’s for
Medical educators — faculty, residents, and PDs who teach. Curriculum leads, simulation directors, assessment people. Anyone in higher ed curious about how clinical training is evolving.
What you’ll get
Free subscribers get the weekly essay.
Paid subscribers receive permanent archive access and career intelligence: curated alerts on jobs, funding grants, conferences, and target journals.
If you are reading as part of your academic or clinical work, this subscription is usually reclaimable through your institution’s expenses process, so it need not come from your own pocket, and a receipt is available for your records. Depending on your country and employment status it may also count as a deductible professional expense.
Lab Licenses are available for research groups of 5+ members at a 25% discount, allowing Principal Investigators to equip their team via a single invoice.
About Me
I am Dr Andrew O’Malley, Senior Lecturer at the University of St Andrews Medical School. My research focuses on the impact of generative artificial intelligence (AI) on medical education, with a specific emphasis on AI safety, bias, assessment, and real-world implementation.
Research and Publications
My academic research investigates how generative AI transforms medical education, technology-enhanced learning, and digital assessment. I am interested in the adoption of emerging technologies by students and faculty, alongside the pedagogical, ethical, and practical implications of AI integration.
As Deputy Director of the Scottish Graduate Entry Medicine (ScotGEM) programme, I evaluate how distributed medical models and technologies support workforce development in remote and rural communities.
Consultancy and Speaking
I collaborate with organisations across higher education, healthcare, and industry to support the ethical and effective use of AI in teaching and clinical training.
Advisory and Consultancy: I advise academic institutions and international bodies on AI strategy, curriculum innovation, and policy development.
Academic Quality: I contribute to external quality assurance, including programme reviews and external examining, and deliver faculty development workshops.
Speaking: I present regularly at international conferences on generative AI and the future of medical education.
For inquiries regarding projects or speaking engagements, please get in touch.
