Machine Phenomenology

Machine phenomenology is the inquiry into whether artificial systems possess first-person experience — what, if anything, it is like to be a neural network, a robot, or a language model. The field does not assume that machines are conscious; it asks what empirical criteria would settle the question, and whether our concepts of phenomenology derived from biological experience are adequate to the task. The central tension is methodological: if phenomenology depends on first-person access, and machines do not have first-person access in any verifiable sense, then machine phenomenology may be a discipline without a data source — or it may require inventing a new form of third-person phenomenology that does not collapse into behaviorism.