Matthieu Queloz
Matthieu Queloz

Concepts 6

Evolving Minds, Evolving Language: Metaphor as a Process of Conceptual Adaptation to Artificial Intelligence

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Argues that cognitively loaded terms such as “understanding” and “reasoning,” when applied to large language models, are best understood neither literally nor as merely loose talk, but as metaphors that adapt our conceptual repertoire to new circumstances under pressure of conceptual needs. Drawing on the Strawson-Kant tradition on imagination and concept-application, inferentialist semantics, Bermudez’s theory of rational framing, and Gentner’s structure-mapping account of analogy, it develops a four-part framework: inferential transfer rather than referential transfer, the aptic normativity of conceptual needs, the empirical evaluation of transferred inferences through mechanistic interpretability, and the career of AI metaphors from novelty toward possible conventionalization. The result is a shift away from all-or-nothing disputes about the literal applicability of cognitive terms to AI toward graded and empirically tractable questions about which inferential transfers are apt, revealing why our cognitive vocabulary for AI is evaluatively and practically consequential.

philosophy of AI, concepts, evolution of language, inference, large language models, metaphor

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Explication or Amelioration? Carnapian Clarification as the Normative Basis for Conceptual Engineering

The Monist. Special issue on Explication and Conceptual Engineering.

As conceptual engineering fractures into explication pursuing exactness and amelioration pursuing justice, the field risks losing its focus. I argue that unifying these projects requires retrieving a crucial insight from Rudolf Carnap: that attempts to improve concepts must start with the preliminary stage of practical clarification. However, Carnap’s account of clarification in terms of predictive proficiency remains normatively inert and biased towards exactness. I expand it into a normative diagnosis of the needs underpinning a concept’s inferential structure. This reveals whether properties like vagueness are flaws that need fixing or features worth preserving.

Carnap, clarification, normativity, explication, amelioration, conceptual engineering

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Reasons of Love and Conceptual Good-for-Nothings

In Themes from Susan Wolf. Michael Frauchiger and Markus Stepanians (eds.). Berlin: De Gruyter. In Press.

Appealing to the instrumentality of concepts raises the worry of yielding the “wrong kind of reasons.” Drawing on Susan Wolf’s work on “reasons of love,” I argue this worry is misplaced. I further explore Wolf’s notion of “valuable good-for-nothings” to demonstrate how non-instrumental values ultimately reinforce the importance of reasons of love in concept use.

concepts, conceptual ethics, conceptual engineering, motivation, reasons of love, normativity

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The Points of Concepts: Their Types, Tensions, and Connections

Canadian Journal of Philosophy 49 (8): 1122–1145. 2019. doi:10.1080/00455091.2019.1584940

By distinguishing four senses in which concepts might be said to have a “point,” this paper resolves the tension between the ambition of point-based explanations to be informative and the claim—central to Dummett’s philosophy of language, but also to the literature on thick concepts—that mastering concepts already requires grasping their point.

concepts, conceptual ethics, conceptual functions, conceptual engineering, metaphilosophy, normativity

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