AAP 2026 CONFERENCE

Does philosophy make progress? Although it may seem obvious that it does, there are sceptics—both within the discipline and beyond it—who question this. In response to such doubts, Stoljar (2017) argues that we are entitled to a “reasonable optimism” about philosophy’s capacity to advance. Stoljar notes that there are recurring patterns or types of philosophical problems that we have solved—such as boundary problems and constitutive problems—that indicate progress. Moreover, as philosophical subfields evolve, new questions and positions emerge—and that, in itself, can be seen as a form of progress. Philosophers may progress their fields by extending earlier arguments, refining existing views, or make what Kelley (2024) calls “philosophical moves.” For example, one might adopt a pluralist position in one field after observing it in another. Given that these moves, or styles of inquiry, could plausibly be learned and applied through pattern recognition, a question arises: could Large Language Models (LLMs), which excel at such tasks, contribute to philosophical progress? In this paper, I argue they may be able to, by looking at issues from the self-knowledge literature. I also consider some of the ethical implications of LLM use in philosophy, including questions around authorship, privacy, and their environmental impact.