Conceptual engineering concerns the assessment and improvement of our concepts. But how can proposals to engineer concepts be implemented in the real world? This is known as the implementation challenge to conceptual engineering. In this paper, I am concerned with the meta-philosophical implications of the implementation challenge. Specifically, must we overcome the implementation challenge prior to undertaking conceptual engineering? Some critics have recently answered this question affirmatively. I intend to show that they are mistaken. I argue as follows. First, successful (...) implementation is not an integral part of conceptual engineering. Second, the idea that the value of conceptual engineering relies on successful implementation is in tension with widespread assumptions about normative theorizing. (shrink)

Should we be worried that the concept of trust is increasingly used when we assess non-human agents and artefacts, say robots and AI systems? Whilst some authors have developed explanations of the concept of trust with a view to accounting for trust in AI systems and other non-agents, others have rejected the idea that we should extend trust in this way. The article advances this debate by bringing insights from conceptual engineering to bear on this issue. After setting up a (...) target concept of trust in terms of four functional desiderata (trust-reliance distinction, explanatory strength, tracking affective responses, and accounting for distrust), I analyze how agential vs. non-agential accounts can satisfy these. A final section investigates how ‘non-ideal’ circumstances—that is, circumstances where the manifest and operative concept use diverge amongst concept users—affect our choice about which rendering of trust is to be preferred. I suggest that some prominent arguments against extending the language of trust to non-agents are not decisive and reflect on an important oversight in the current debate, namely a failure to address how narrower, agent-centred accounts curtail our ability to distrust non-agents. (shrink)

Conceptual engineering is sometimes presented as an alternative to conceptual analysis. But one important objection to conceptual analysis threatens to carry across: that philosophy investigates phenomena—knowledge, truth, freedom, etc.—rather than concepts of those phenomena. This poses a prima facie problem insofar as conceptual engineering targets concepts or terms rather than phenomena. Call it the ‘phenomenon objection’. I begin by examining recent discussions of the phenomenon objection by Cappelen and Scharp, rejecting their responses. I then clarify and strengthen the objection, discussing (...) the challenge that the ‘strong phenomenon objection’ poses to conceptual engineers. Finally, I develop a new response to the strong phenomenon objection. In doing so, I motivate, articulate and defend an account of philosophy and its problems on which conceptual engineering is the appropriate method for tackling many philosophical problems—as well as, perhaps surprisingly, some problems in the sciences. (shrink)

Supporters of conceptual engineering often use Haslanger’s ameliorative project as a key example of their methodology. However, at face value, Haslanger’s project is no cause for optimism about conceptual engineering. If we interpret Haslanger as seeking to revise how people in general use and understand words such as ‘woman’, ‘man’, etc., then her project has been unsuccessful. And if we interpret her as seeking to reveal the meaning of those words, then her project does not involve conceptual engineering. I develop (...) and defend an alternative interpretation of Haslanger’s project and argue that, so interpreted, it is a successful conceptual engineering project after all. In so doing, I develop what I call a particularist account of the success conditions for conceptual engineering. (shrink)

We describe a method, based on Jennifer Nado's definition of classification procedures as targets of conceptual engineering, that implements such procedures using a large language model. We then apply this method using data from the Wikidata knowledge graph to evaluate concept definitions from two paradigmatic conceptual engineering projects: the International Astronomical Union's redefinition of PLANET and Haslanger's ameliorative analysis of WOMAN. We discuss implications of this work for the theory and practice of conceptual engineering. The code and data can be (...) found on GitHub. (shrink)