The organizers of the fourth Philosophy of Machine Learning conference (PhilML‘26), taking place on October 7-9, 2026 at LMU Munich, would like to invite the submission of extended abstracts.
Since 2021, PhilML has brought together scientifically-engaged philosophers with machine learners to address foundational issues raised by developments in ML research. Submissions are invited from all philosophical subfields, including philosophy of science, mind, ethics, epistemology, and political philosophy, as well as foundational and philosophical submissions from machine learners.
Submissions, due ..., should consist of an anonymised extended abstract (750 words, not including references), along with a cover sheet with your name, email address, and institutional affiliation. It should be sent as an attachment to philml2026@gmail.com. Please indicate in the email subject line that this is a: Submission to the PhilML Conference.
Reflections on key topics such as learning, benchmarking, robustness, explanation, causality, trust, transparency, reliability, and fairness.
Implications of machine learning for the sciences or their methodology, e.g. physics, cognitive science, biology, social science, or medicine.
Issues arising at the intersection of machine learning and public policy, e.g. public services, resource allocation, or climate policy.
Novel considerations raised by foundation models e.g., authorship, mechanistic interpretability, or homogenization
Each abstract will be reviewed by multiple of the conference organizers and LMU faculty members. Selection criteria are research quality, novelty, and topical diversity. Decisions will be announced by ....
There will be no participation fee!
If you have questions, please email: philml2026@gmail.com.