I am a philosopher of medicine and AI, working on questions where evidence and ethics meet. I am Associate Professor of Interdisciplinary Education and Co-Director of LSE100 at the London School of Economics.
[This paper has been updated in 2026 from the 2022 preprint] Evidence pyramids are amongst the most recognisable artefacts of the Evidence-Based Medicine movement. Yet no study has established the origins of evidence pyramids, or analysed whether they offer any information beyond simple lists or tables. In this paper, I establish the origins of the first evidence pyramid and argue that the pyramidal turn is a retrograde step in evidence appraisal.
How can AI-generated "Top 10" lists of cultural influencers expose the cultural biases and defaults that are built into our most popular language models? I propose and report an initial test using lists of the Top 10 most influential musicians.
How can the concept of the experimenter's regress help us understand the problems in AI decision systems? I explore two forms of circularity that can underpin AI decision tools through the lens of Collins and Pinch's 'The Golem'.
Google's NotebookLM "deep dive" feature is taking off in popularity. I subject three of my academic papers to the deep dive treatment, and reveal its tendency to subvert content for a happier ending.
I outline four common misconceptions about the use of Generative AI which are widespread in Higher Education debates about the use of these tools: that it is possible and practical to detect the use of AI in writing, that text produced by GenAI is bland, repetitive or predictable, that GenAI tools struggle to cite sources accurately, and that more creative or reflective assessments are harder to complete using AI.
