AI & Philosophy Readings for Undergraduate Courses
Artificial intelligence is relevant to so many philosophical subfields, and its increased presence in our lives makes it a ripe topic to cover in philosophy courses.
Philosophical writing on AI is at that stage where there has been an explosion of it, yet not enough time for the kind of assessment and filtering of it that could result in the establishment of a canon (or subdisciplinary canons).So I thought it would be useful to solicit your suggestions about good readings, focusing on works it might be reasonable to assign undergraduates.
The readings need not be academic works. It may be that some pieces published in popular media are especially pedagogically valuable. Nor must the pieces be written by philosophers to be appropriate for philosophy courses.
In sharing your suggestion, please provide the title and author, and let us know what kind of course you think the reading would be appropriate for (e.g., “contemporary moral problems,” or “for a unit on mind in an intro course”). If you have a link to the piece handy, please include it. Thanks!
(And yes, I acknowledge there is an irony in soliciting readings about a technology that tempts students to not do the reading.)
In Chinese, I recommend a book called A Brief History of Artificial Intelligence (Rengong Zhineng Jianshi), which was written by Nick. I have read it and found it very clear. It can help you learn some basic concepts of AI and the history of AI. It also has a discussion about AI and Philosophy. If you can read Chinese, you should read this book.
The syllabus is now 3 years out of date, but I last taught AI ethics in 2023 and you can find the syllabus with all of its readings here: https://danielweltman.com/teaching.html
In the third year Ethics of AI course I teach I spend the first lecture exploring the nature of AI, since without having some grasp on how AI works and what it is, engaging with normative and applied ethics for it is fruitless.
Milliere and Buckner have a two part paper (A Philosophical Introduction to Language Models) and I use the second part for a 3rd year or senior course, but it’s quite long and some of the writing is a bit disappointing for a philosophy paper (their polysemantic, overloaded use of the term ‘subspace’, for example.) Part II investigates both the multiple realisability thesis and the epistemic opacity dilemma (although it does not use those specific terms). Apart from the terminological issue, it’s very good and the field they take on is very complex and conceptually dense.
The authors refer to the metaphysics of mechanism (Woodward) to investigate the interventionist and interpretation strategies being deployed of late to try to penetrate the black box of LLMs and transformers. Overall they suggest that Putnam’s multiple realisability thesis has been shown to be true, or very close.
A less technical alternative which is nicely balanced in terms of philosophical coverage is VINCENT C. MÜLLER’s “Philosophy of AI: A Structured Overview” in A Companion to Applied Philosophy of AI, First Edition. Edited by Martin Hähnel and Regina Müller.
© 2025 John Wiley & Sons, Inc. Published 2025 by John Wiley & Sons, Inc.
The field is moving so fast that I have to update lectures fortnightly to monthly. In the last introductory lecture I made sure to present Anthropic’s J-Space video when discussing multiple realisability and global workspace theory.
( https://www.youtube.com/watch?v=rKV5JcALQoQ )
This semester, in an intro course where we sample a bunch of different debates, I assigned a reading on the ethics of AI which I knew I could vouch for — because I wrote it:
“Needle in a needle stack: How AI causes semiotic inflation, which causes experiential devaluation”
https://philpapers.org/archive/CHANIA-6.pdf
The two standard form arguments that are compared in the middle ensured that the stance was not a moving target (and as a bonus helped students get acquainted with arguments generally).
good thread from BSky comments from David Marx: https://bsky.app/profile/digthatdata.bsky.social/post/3mrpjrteoyc2o
“Why We’re Not Using AI in This Course, Despite Its Obvious Benefits”
By Patrick Lin (me), 2025
This long-read is basically an open letter to my students. It explains my AI ban, capturing just about all the major issues around LLM use; so I start my tech-ethics classes with this as the very first reading.
The goal is to persuade and get students’ buy-in (so that I don’t need to be an AI cop and rely only on deterrence and penalties), so this reading can work in any class. For tech ethics courses, it also provides a springboard for discussion about LLM ethics.
This Substack article has made the rounds in academia, e.g., here and here.