According to explanatory individualism, every action must be explained in terms of an agent's desire. According to explanatory nonindividualism, we sometimes act on our desires, but it is also possible for us to act on others' desires without acting on desires of our own. While explanatory nonindividualism has guided the thinking of many social scientists, it is considered to be incoherent by most philosophers of mind who insist that actions must be explained ultimately in terms of some desire of the (...) agent. In the first part of the paper, I show that some powerful arguments designed to demonstrate the incoherence of explanatory nonindividualism fail. In the second part of the paper, I offer a nonindividualist explanation of the apparent obviousness of belief-desire psychology. I argue that there are two levels of the intelligibility of our actions. On the more fundamental (explanatory) level, the question "Why did the agent do something?" admits a variety of folk-psychological categories. But there is another (formation-of-self) level, at which the same question admits only of answers that ultimately appeal only to the agent's own desires. Explanatory individualism results from the confusion of the two levels. (shrink)

Donald Davidson established causalism, i.e. the view that reasons are causes and that action explanation is causal explanation, as the dominant view within contemporary action theory. According to his “master argument”, we must distinguish between reasons the agent merely has and reasons she has and which actually explain what she did, and the only, or at any rate the best, way to make the distinction is by saying that the reasons for which an agent acts are causes of her action. (...) “Davidson's challenge” to non‐causalists is to come up with an alternative, more convincing, way of drawing the distinction. In this paper, I argue that G.E.M. Anscombe and G.H. von Wright offer such an alternative. Moreover, I argue that Davidson's own account of interpretation makes no use of his causalist claim. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

The paper firstly reconstructs Mario Calderoni’s criticism of the Jamesian version of pragmatism, which corresponds to his philosophical choice in favor of the ethical value assigned by Peirce to the scientific-experimental method. In this light, I propose a reading of some Calderoni’s arguments concerning the link between the construction of beliefs, practical norms and moral or legal responsibility, trying to reassess his criticisms of James and then his conception of philosophy as a practical and therapeutic activity. The latter will be (...) discussed considering Wittgenstein’s analysis of intentional verbs and Calderoni’s approach to the issues of freedom, of the definition of voluntary acts as well as of individual responsibility, both moral and legal. In particular, I will focus on the paradigm shift suggested by Wittgenstein with regard to the problem of human will, which seems useful for enhancing Calderoni’s pragmatist insights. (shrink)