“Reasoning” models, philosophy of inference, and artificial epistemic agency

The frontier of AI is being pushed forward now by “Large Reasoning Models” (LRMs) that self-generate long textual “Chains-of-Thought” (CoTs) before answering user queries. While there is already a cottage industry investigating whether these chains of thought are “faithful” to underlying computations producing answers, existing faithfulness research has largely analyzed faithfulness in purely behavioral terms, as a particular input-output profile on reasoning problems. More broadly, there has been little attempt in this literature to define reasoning or to distinguish rational inference from other forms of decision-making. By contrast, philosophical work on rational inference has tended to focus on internal psychological connections between evidence and conclusions—in the philosophical tradition, rational inference involves the exercise of a distinctive form of epistemic agency to construe evidence in particular ways and to draw conclusions because of these construals. In this talk, I will contrast the behavioral and philosophical approaches to rational inference. I will argue that while the philosophical tradition runs the risk of overintellectualizing inference, there are some pragmatic reasons for engineers to review the richer philosophical notion of reasoning when designing the next generation of artificial agents with more powerful forms of epistemic self-calibration and agency.