CfA: Call for Abstracts

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 are due by 1 July and should consist of an anonymised extended abstract of up to 1,000 words (excluding references). Abstracts should be submitted via Oxford Abstracts using the following link: https://app.oxfordabstracts.com/stages/82713/submitter. We welcome submissions from scholars at all career stages, including PhD students.

The workshop’s central topics include

1. Reflections on key topics such as learning, benchmarking, robustness, explanation, causality, trust, transparency, reliability, and fairness.

2. Implications of machine learning for the sciences or their methodology, e.g. physics, cognitive science, biology, social science, or medicine.

3. Issues arising at the intersection of machine learning and public policy, e.g. public services, resource allocation, or climate policy.

4. Novel considerations raised by foundation models e.g., authorship, mechanistic interpretability, or homogenization

Procedure and Questions

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 1 August. 

There will be no participation fee!

If you have questions, please email: philmlconf@protonmail.com.