I'm a lecturer in philosophy at the University of Cambridge. 


My core areas of research are philosophy of mind, epistemology, and philosophy of psychology. I also enjoy thinking and writing about philosophy of psychiatry.  

Some of my research is in philosophy of perception. I'm currently thinking about the ways in which visual experience extends through and develops over time. I'm also interested in perceptual uncertainty. I'd like to find ways of modeling perceptual experience that can accommodate the dynamism and uncertainty of our perceptual experience.  

I also work on bias: when is something a bias, and when is it just a case of legitimately learning from experience? Must problematic biases always involve false or unjustified beliefs? What can we learn from bias about the limits of epistemic evaluation? I'm particularly interested at the moment in figuring out how we can epistemically evaluate the ways in which we order information in terms of relevance. Related to that bigger question, I'm currently working on a paper about salience and prejudice, and thinking about the epistemology of search engines.

I like to do philosophy by talking to other people, so if you're working on any of those questions and want to discuss them, get in touch! 

Before coming to Cambridge in 2018 as a Junior Research Fellow at St John's College, I was a Bersoff  Faculty Fellow at NYU in for the 2017-2018 academic year. Before that, I completed my PhD at Yale University, and a BPhil in philosophy and a BA in classics and philosophy, both at Oxford University. I have also spent time undertaking legal training, and legal research focusing on capital punishment in Sub-Saharan Africa. 

email: jm2200[at]cam[dot]ac[dot]uk

New and Upcoming Things...

I reviewed Philippa Perry's "The Book You Wish Your Parents Had Read" and Emily Oster's "Cribsheet" for the TLS, here.

My paper "Visual Indeterminacy and the Puzzle of the Speckled Hen" is now forthcoming in Mind and Language. You can read a penultimate version here.


And here's the Abstract: I identify three aspects to the puzzle of the speckled hen: a general puzzle, an epistemic puzzle, and a puzzle for the representationalist. These puzzles rely on an underlying ‘pictorialist’ assumption, that we visually perceive general, determinable properties only in virtue of determinate properties or more specific, local features of our visual experience. This assumption is mistaken: visual perception starts from a position of uncertainty, and is routinely able to acquire information about general properties in the absence of more specific information. Acknowledging that visual indeterminacy is structured this way resolves all three puzzles of the speckled hen.


My paper "Beyond Accuracy: Epistemic Flaws with Statistical Generalizations" is now out in Philosophical Issues. You can read the final on-line version here: https://onlinelibrary.wiley.com/doi/full/10.1111/phis.12150  and a penultimate version is available here.

Here's an Abstract: What, if anything, is epistemically wrong with beliefs involving accurate statistical generalizations about demographic groups? This paper argues that there is a perfectly general, underappreciated epistemic flaw which affects both ethically charged and uncharged statistical generalizations. Though common to both, this flaw can also explain why demographic statistical generalizations give rise to the concerns they do. To identify this flaw, we need to distinguish between the accuracy and the projectability of statistical beliefs. Statistical beliefs are accompanied by an implicit representation of the statistic's modal profile. Their modal profile determines the circumstances in which they can legitimately be projected to unobserved instances. Errors in that implicit content can be compatible with the accuracy of the “bare” statistic, whilst systematically leading to downstream errors in reasoning, in a manner which reveals an epistemic flaw with an important aspect of the belief state itself.

© 2023 by Scientist Personal. Proudly created with Wix.com

  • Facebook Clean Grey
  • Twitter Clean Grey
  • LinkedIn Clean Grey
This site was designed with the
website builder. Create your website today.
Start Now