I argue that John Dewey’s analysis of imagination enables an account of learning from imaginary cases consistent with Jonathan Dancy’s moral particularism. Moreover, this account provides a more robust account of learning from cases than Dancy’s own. Particularism is the position that there are no, or at most few, true moral principles, and that competent reasoning and judgment do not require them. On a particularist framework, one cannot infer from an imaginary case that because a feature has a particular moral (...) importance there, that it must have that import in an actual case. Instead, for Dancy, cases can yield “reminders,” and a person with a lot of experience (real or imagined) brings a “checklist” of features that can matter to a situation. Using the Nathan-David exchange from 2 Samuel and Martha Nussbaum’s “Steerforth’s Arm” from Love’s Knowledge, I show that this account does not explain all instances of learning from cases. Drawing on recent work on cases, I argue that cases can be educative by serving an exploratory function, probing what one takes to be known and provoking change in the background one uses in evaluating a situation. I then argue that Dewey’s work on imagination in his comments on sympathy and in A Common Faith and Art as Experience enables such a role for cases on a particularist framework. Mark Johnson’s recent work on metaphor further illuminates how Dewey’s account of art can be exploratory. I contend that this account affords an exploratory role for cases consistent with Dancy’s particularism. (shrink)

This paper compares two theories and their two corresponding computational models of human moral judgment. In order to better address psychological realism and generality of theories of moral judgment, more detailed and more psychologically nuanced models are needed. In particular, a motivationally based theory of moral judgment is developed in this paper that provides a more accurate account of human moral judgment than an existing emotion-reason conflict theory. Simulations based on the theory capture and explain a range of relevant human (...) data. They account not only for the original data that were used to support the emotion–reason conflict theory, but also for a wider range of data and phenomena. (shrink)

This paper presents the results of training an artificial neural network (ANN) to classify moral situations. The ANN produces a similarity space in the process of solving its classification problem. The state space is subjected to analysis that suggests that holistic approaches to interpreting its functioning are problematic. The idea of a contributory or pro tanto standard, as discussed in debates between moral particularists and generalists, is used to understand the structure of the similarity space generated by the ANN. A (...) spectrum of possibilities for reasons, from atomistic to holistic, is discussed. Reasons are understood as increasing in nonlocality as they move away from atomism. It is argued that contributory standards could be used to understand forms of nonlocality that need not go all the way to holism. It is also argued that contributory standards may help us to understand the kind of similarity at work in analogical reasoning and argument in ethics. Some objections to using state space approaches to similarity are dealt with, as are objections to using empirical and computational work in philosophy. (shrink)

The growing field of machine morality has becoming increasingly concerned with how to develop artificial moral agents. However, there is little consensus on what constitutes an ideal moral agent let alone an artificial one. Leveraging a recent account of heroism in humans, the aim of this paper is to provide a prospective framework for conceptualizing, and in turn designing ideal artificial moral agents, namely those that would be considered heroic robots. First, an overview of what it means to be an (...) artificial moral agent is provided. Then, an overview of a recent account of heroism that seeks to define the construct as the dynamic and interactive integration of character strengths and situational constraints that afford the opportunity for moral behavior . With this as a foundation, a discussion is provided for what it might mean for a robot to be an ideal moral agent by proposing a dynamic and interactive connectionist model of robotic heroism. Given the limited accounts of robots engaging in moral behavior, a case for extending robotic moral capacities beyond just being a moral agent to the level of heroism is supported by drawing from exemplar situations where robots demonstrate heroism in popular film and fiction. (shrink)

This work is an investigation into philosophical method and rational argument in moral philosophy. It makes an original contribution to human understanding, by taking some of the tools and techniques that Gordon Baker identifies in the later work of Wittgenstein, and using them as a way of fending for oneself in an area of philosophy that neither Baker, nor Wittgenstein, wrote on. More specifically, a discussion of some different aspects of the contemporary literature on Dancy’s moral particularism is used as (...) a vehicle for illustrating how Baker’s therapeutic conception of philosophy offers alternative possibilities for how we can do philosophy, and what counts as rational argument in moral philosophy. I maintain that, by considering some indicative ways in which Baker’s therapeutic approach to philosophy can dissolve, rather than solve, the kinds of perplexities found in the existing literature on Dancy’s moral particularism, we can liberate ourselves from the traditional/theoretical view of how we ought to do philosophy, and an understanding of rational argument in moral philosophy, to which we need not be committed. (shrink)

Accounts of analogical inference are usually categorized into four broad groups: abductive, deductive, inductive and sui generis. The purpose of this paper is to defend a sui generis model of analogical inference. It focuses on the sui generis account, as developed by Juthe [2005, 2009, 2015, 2016] and Botting’s [2017] criticism of it. This paper uses the pragmadialectical theory of argumentation as the methodological framework for analyzing and reconstructing argumentation. The paper has two main points. First, that Juthe’s arguments against (...) a deductive interpretation of prima facie analogy argumentation remain unaffected by Botting’s criticism, which means that many of the reasons against deductive reformulation of analogy argumentation still stand. The additional argument, which Botting himself brings up, that a deductive interpretation cannot account for the cumulative effect of analogies, just provides further reason to reject deductivism. The second main point of this paper is that an inductive interpretation of analogical inference also fails. There are constitutional differences between inductive and analogical inference that cannot be bridged. The result is a firm defense of the sui generis view of analogical inference. (shrink)

This paper will add to the discourse on analogical arguments by showing that they need not be deductively reconstructed in common contexts of persuasion. Analogical arguments have varying degrees of similarity, which helps us to understand their varying degrees of strength. Pace Shecaira it will be argued that this is a common and useful way of examining analogical arguments. It will be shown that deductive reconstruction does not adequately capture the needed degrees of strength. Let us start with two-wise similarity (...) claims. Subject S1 says that the disputed case C1 is similar to C2 and should be treated as x, just as C2 is. S2 says that C1 is similar to C3 and should be treated as y, just as C3 is. S1 may counter with a three-wise similarity claim: C1 is more similar to C2 than it is to C3, because…, so C1 should be treated as x. Think of lawyers in court. It will be shown that the evaluation of analogical arguments in these contexts turns in a central way on similarity, and that deductive reconstructions get in the way of a proper understanding of the preceding. (shrink)

I argue that John Dewey’s analysis of imagination enables an account of learning from imaginary cases consistent with Jonathan Dancy’s moral particularism. Moreover, this account provides a more robust account of learning from cases than Dancy’s own. Particularism is the position that there are no, or at most few, true moral principles, and that competent reasoning and judgment do not require them. On a particularist framework, one cannot infer from an imaginary case that because a feature has a particular moral (...) importance there, that it must have that import in an actual case. Instead, for Dancy, cases can yield “reminders,” and a person with a lot of experience (real or imagined) brings a “checklist” of features that can matter to a situation. Using the Nathan-David exchange from 2 Samuel and Martha Nussbaum’s “Steerforth’s Arm” from Love’s Knowledge, I show that this account does not explain all instances of learning from cases. Drawing on recent work on cases, I argue that cases can be educative by serving an exploratory function, probing what one takes to be known and provoking change in the background one uses in evaluating a situation. I then argue that Dewey’s work on imagination in his comments on sympathy and in A Common Faith and Art as Experience enables such a role for cases on a particularist framework. Mark Johnson’s recent work on metaphor further illuminates how Dewey’s account of art can be exploratory. I contend that this account affords an exploratory role for cases consistent with Dancy’s particularism. (shrink)

A simple recurrent artificial neural network is used to classify situations as permissible or impermissible. The trained ANN can be understood as having set up a similarity space of cases at the level of its internal or hidden units. An analysis of the network’s internal representations is undertaken using a new visualization technique for state space approaches to understanding similarity. Insights from the literature on moral philosophy pertaining to contributory standards will be used to interpret the state space set up (...) by the ANN as being structured by implicit reasons. The ANN, on its own, is not capable of explicitly representing or offering reasons to itself or others. That said, the low level similarity space set up by the network could be made available to higher order processes that exploit it for case-based reasoning. It is argued that for normative purposes, similarity could be seen as a contributor to procedural coherence in case-based reasoning and local forms of substantive coherence, but not to global forms of coherence given the computational complexity of managing those more ambitious forms of coherence. (shrink)

“Deductivism” is a broad label for various theories that emphasize the importance of deductive argument in contexts of rational discussion. This paper makes a case for a very specific form of deductivism. The paper highlights the dialectical importance of advancing deductively valid arguments in natural-language reasoning. Sections 2 and 3 explain the various forms that deductivism has taken. Section 4 makes a case for a particular form of deductivism. Section 5 discusses the value of deductive argument in law. Section 6 (...) concludes and acknowledges critical questions that need to be addressed more fully in future work. (shrink)