Deflationism About Logic

Abstract

Logical consequence is typically construed as a metalinguistic relation between (sets of) sentences. Deflationism is an account of logic that challenges this orthodoxy. In Williamson's recent presentation of deflationism, logic's primary concern is with universal generalizations over absolutely everything. As well as an interesting account of logic in its own right, deflationism has also been recruited to decide between competing logics in resolving semantic paradoxes. This paper defends deflationism from its most important challenge to date, due to Ole Hjortland. It then presents two new problems for the view. Hjortland's objection is that deflationism cannot discriminate between distinct logics. I show that his example of classical logic and supervaluationism depends on equivocating about whether the language includes a "definitely" operator. Moreover, I prove a result that blocks this line of objection no matter the choice of logics. I end by criticizing deflationism on two fronts. First, it cannot do the work it has been recruited to perform. That is, it cannot help adjudicate between competing logics. This is because a theory of logic cannot be as easily separated from a theory of truth as its proponents claim. Second, deflationism currently has no adequate answer to the following challenge: what does a sentence's universal generalization have to do with its logical truth? I argue that the most promising, stipulative response on behalf of the deflationist amounts to an unwarranted change of subject.

Diversity Training With Robots: Perspective-Taking Backfires, While Sterotype-Suppression Decreases Negative Attitudes Towards Robots

“…Even though robots offer a vast potential to support people in the workplace by, for example, increasing productivity and flexibility ( Fragapane et al, 2020 ), or by reducing the strain on workers in the care sector ( Blake, 2019 ), attitudes towards robots are not as positive as one would think (e.g., Bernotat and Eyssel, 2018 ). Relatedly, stereotypes pose a problem for successful hybrid human-robot teams: It has been shown that stereotypes that apply within the human-human context are also readily transferred to robots (e.g., Eyssel and Hegel, 2012 ; Bernotat et al, 2019 ), biasing judgments about them.…”