reasoningas

Reasoningas is a term used in cognitive science and philosophy of mind to describe an approach to modeling reasoning that foregrounds the construction and evaluation of reasons from multiple perspectives. It treats reasoning as the articulation of justifications agents can defend, rather than as a purely linear deduction from fixed premises. In reasoningas, justification is distributed across speakers, evidence sources, and contextual factors, with an emphasis on transparency and the auditability of inferential steps.

The theoretical framework of reasoningas posits a cyclical process: gather relevant evidence from diverse sources, compare competing explanations, weight reasons by their relevance and reliability, revise beliefs in light of new information, and clearly articulate the justificatory chain. It contrasts with formal deduction by integrating pragmatics, epistemic virtues, and the acknowledgment of fallibility.

Origin and usage: the term has appeared in contemporary discussions on explainable artificial intelligence, rationality, and theory change, though its exact definition varies by author. Some interpret reasoningas as a normative ideal for intelligent agents, while others view it as a descriptive account of everyday inference and conversation.

Applications: in AI alignment and interpretability research, reasoningas-inspired models emphasize justification traces for decisions. In education, the concept informs curricula that emphasize argumentation, evidence evaluation, and critical reflection. In epistemology, reasoningas contributes to analyses of rational justification, theory change, and the social dimensions of belief formation.

Criticisms and defenses: critics argue that reasoningas can be overly context-dependent or difficult to formalize for computational systems. Proponents counter that it captures essential features of real-world reasoning, communication, and accountability that purely formal approaches may miss.