I am a Lecturer in Philosophy at the University of Otago. Previously I was a Postdoc in the EMRG Lab in the Rotman Institute of Philosophy, and before that I finished my PhD at Columbia University.

I work in philosophy of science, studying how cognitive science and AI make complex systems, like brains and neural networks, intelligible. I also have research projects in philosophy of mind and philosophical methodology. And I am increasingly involved in research and outreach concerning the role of AI in public (especially social) life.

You can reach me at andrew.richmond[at]otago[dot]ac[dot]nz. My CV is here, and further down the page you can find information about my research, teaching, and postgraduate supervision.

Research

I study scientific reasoning as a psychological process. Currently, I spend most of my time thinking about how philosophy, cognitive science, and machine learning can make complex cognitive systems intelligible to human beings.

I mainly focus on how specialized concepts shape scientific reasoning, and I take a pragmatic approach to that question. That is: I spend less time asking about the kind or category a concept might name, and more time asking how the concept helps scientists think, how it guides their research, and how it serves science as a result.

My main project (1) elaborates and defends the pragmatic approach, (2) applies it in philosophy of cognitive science and AI, and (3) traces its implications for the philosophy and psychology of concepts. And I have related projects in philosophy of mind, AI ethics, and philosophical methodology.

Publications
(* = first/co-first author)​​

• Experimental philosophy of science: Beyond categories. Forthcoming, ​Philosophy of Science.
• What really lives in the swamp? Kinds and the illustration of scientific reasoning. ​2026, Philosophy of Science.
• Use and usability: concepts of representation in philosophy, neuroscience, cognitive science, and computer science.​ 2026, Neurons, Behavior, Data Analysis, and Theory​. With Baker, B.,* Lange, R.,* Richmond, A.,* Kriegeskorte, N., Cao, R., Pitkow, X., & Schwartz, O.
• What is a theory of neural representation for? 2025, Synthese, 205(14).
• How Computation Explains.​ 2025, Mind & Language, 40(1).
• Imposing vs finding unity. 2024, Cognitive Neuroscience, 15(3–4), 122-123. With Richmond, A.,* Bowen, J. G., Kayssi, L. F., Küçük, K., Ravikumar, V., Şahin, Y., Anderson, M.L.​
• Commentary: Investigating the concept of representation in the neural and psychological sciences. 2023, Frontiers in Psychology, 14.​

In preparation/
​under review

• Pragmatism in philosophy of cognitive science (under commission, Philosophy Compass)
• Computational externalism ​(under review)
• Chatbot attachment: Relational artefacts and the personal stance (in preparation, see the policy brief here)
• How concepts travel: Representation in philosophy, neuroscience, and explainable AI​​ (in preparation)

​Teaching

Most of my teaching is organized around the attempt to individualize my courses to make them accessible and engaging for all students. To do that, I lean especially on the principles of Universal Design for Learning.

Teaching Materials​

• AI and the Pedagogical Relationship [link]
  A short article for Western University's Center for Teaching and Learning, on the use of AI tools and how they affect the social dimension of learning.
• The Next Generation of Ethical AI ​[advertisement, details]
  A summer school I ran in 2025, for high school students. It covered the technical basics of deep learning, the way AI is applied in areas like healthcare and education, and the ethical challenges it poses. The goal was to help the next generation of AI users, developers, and policy-makers become philosophically informed and ethically sensitive to the risks of AI.
• Philosophy and Artificial Intelligence [syllabus]
  An upper-level course I taught at Columbia, as a Teaching Scholar, on philosophy of AI. The course gives students lots of latitude in the kind of work they do, especially on their final projects, while still thoroughly scaffolding those projects.
• Ethics [syllabus]
  An intermediate-level course I taught at Columbia. It introduces traditional ethical theories in the context of current ethical dilemmas. The course's main distinguishing feature is that it is ungraded — an experiment that went very well, but that I probably won't do again. (Ungrading served pedagogical goals that I can achieve in other ways. Grades serve pedagogical goals that are hard for me to achieve in other ways.)
• Metaphysics [syllabus]
  An intermediate-level course I taught at Columbia. It introduces metaphysics through some traditional topics, and then turns to broader questions about realism, naturalism, and the place of metaphysics in inquiry.
• Philosophical Monsters [syllabus in progress]
  An introductory- or intermediate-level course I plan to teach. The first part introduces a range of philosophical topics through the bestiaries they have created: philosophy of mind has P-zombies and swampmen; ethics has the utility monster; etc. The second part interrogates the methodology that gives such weight to these monsters (and thought experiments more generally).
• Other
  ​I have drafts of syllabi on philosophy of cognitive science, the philosophy and psychology of humor, the epistemology of conspiracy theories, and some other subjects, which I can provide on request.

​Postgraduate Supervision

If you're interested doing an MA or PhD in one of my areas, please get in touch. I'm happy to supervise work in philosophy of science, cognitive science, mind, and AI. I'm also happy to talk more broadly about whether/why/where you might want to undertake postgraduate study. (In case it needs to be said: please don't send research proposals or other materials that have been written or revised by AI.)