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I'm a Postdoc in the EMRG Lab in the Rotman Institute of Philosophy, at Western University.
I work in philosophy of science, studying the way that cognitive science and AI make complex systems, like brains and neural networks, intelligible. I also have projects on philosophy of mind, philosophical methodology, and pedagogy. You can reach me at arichmo8[at]uwo[dot]ca. My CV is here, and further down you can find descriptions of my research and teaching. |
Research
I work in philosophy of science, blending methods from philosophy and psychology to study scientific reasoning. Currently I spend most of my time thinking about how philosophy, neuroscience, and AI can work together to make complex systems, like brains and neural networks, intelligible. I take a pragmatic approach, and one of my main projects is to elaborate and defend that approach by showing how our methodology as philosophers of science should be sensitive to lessons from the psychology of scientific explanation.
I work in philosophy of science, blending methods from philosophy and psychology to study scientific reasoning. Currently I spend most of my time thinking about how philosophy, neuroscience, and AI can work together to make complex systems, like brains and neural networks, intelligible. I take a pragmatic approach, and one of my main projects is to elaborate and defend that approach by showing how our methodology as philosophers of science should be sensitive to lessons from the psychology of scientific explanation.
Publications (* = first/co-first author)
Forthcoming
Forthcoming
- Richmond, A. What really lives in the swamp? Kinds and the illustration of scientific reasoning. Philosophy of Science.
- Baker, B.,* Lange, R.,* Richmond, A.,* Kriegeskorte, N., Cao, R., Pitkow, X., Schwartz, O., & Achille, A. Use and usability: Three levels of neural representation. Neurons, Behavior, Data, and Theory.
- Richmond, A. What is a theory of neural representation for? Synthese, 205(14).
- Richmond, A. How Computation Explains. Mind & Language, 40(1).
- Richmond, A.,* Bowen, J. G., Kayssi, L. F., Küçük, K., Ravikumar, V., Şahin, Y., Anderson, M.L. Imposing vs finding unity. Cognitive Neuroscience, 15(3–4), 122-123.
- Richmond, A. Commentary: Investigating the concept of representation in the neural and psychological sciences. Frontiers in Psychology, 14.
- Richmond, A. Pragmatism in philosophy of cognitive science (under commission, Philosophy Compass)
- Richmond, A. Computational externalism (under review)
- Richmond, A. Social AI: Mechanisms and consequences (in preparation, see the policy brief here)
- Richmond, A. Experimental philosophy of science: Beyond categories (in preparation)
- Richmond, A. How theories travel: Representation in explainable AI (in preparation)
Teaching
Most of my teaching is organized around the attempt to make courses accessible and engaging by individualizing them, primarily through the principles of Universal Design for Learning.
Most of my teaching is organized around the attempt to make courses accessible and engaging by individualizing them, primarily through 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 in education and the way they change the social dimension of learning.
The Next Generation of Ethical AI [poster, 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 posed by AI technology. 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 the relationship of AI to philosophy of mind, science, and ethics. The course gives students lots of latitude in the kind of work they do, especially on their final projects, while still ensuring that those projects are scaffolded.
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 try again any time soon. (Ungrading mostly served pedagogical goals that I can achieve in other ways. Grades serve pedagogical goals that I have difficulty achieving 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 of the course introduces a range of philosophical topics through the bestiary 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 evidential weight to these monsters and thought experiments more generally.
Other
I have drafts of syllabi on the 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.
AI and the Pedagogical Relationship [link]
A short article, for Western University's Center for Teaching and learning, on the use of AI tools in education and the way they change the social dimension of learning.
The Next Generation of Ethical AI [poster, 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 posed by AI technology. 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 the relationship of AI to philosophy of mind, science, and ethics. The course gives students lots of latitude in the kind of work they do, especially on their final projects, while still ensuring that those projects are scaffolded.
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 try again any time soon. (Ungrading mostly served pedagogical goals that I can achieve in other ways. Grades serve pedagogical goals that I have difficulty achieving 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 of the course introduces a range of philosophical topics through the bestiary 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 evidential weight to these monsters and thought experiments more generally.
Other
I have drafts of syllabi on the 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.
