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)

This paper explores some ways in which artificial intelligence (AI) could be used to improve human moral judgments in bioethics by avoiding some of the most common sources of error in moral judgment, including ignorance, confusion, and bias. It surveys three existing proposals for building human morality into AI: Top-down, bottom-up, and hybrid approaches. Then it proposes a multi-step, hybrid method, using the example of kidney allocations for transplants as a test case. The paper concludes with brief remarks about how (...) to handle several complications, respond to some objections, and extend this novel method to other important moral issues in bioethics and beyond. (shrink)

Brauchen Roboter moralische Kompetenz? Die Antwort lautet ja. Einerseits benötigen Roboter moralische Kompetenz, um unsere Welt aus Regeln, Vorschriften und Werten zu begreifen, andererseits um von ihrem Umfeld akzeptiert zu werden. Wie aber lässt sich moralische Kompetenz in Roboter implementieren? Welche philosophischen Herausforderungen sind zu erwarten? Und wie können wir uns und unsere Kinder auf Roboter vorbereiten, die irgendwann über moralische Kompetenz verfügen werden? André und Iga Maria Schmiljun skizzieren aus einer humanistisch-philosophischen Perspektive erste Antworten auf diese Fragen und entwickeln (...) einen didaktischen Einstieg in das Thema für die Grundschule. (shrink)

Herein we make a plea to machine ethicists for the inclusion of constraints on their theories consistent with empirical data on human moral cognition. As philosophers, we clearly lack widely accepted solutions to issues regarding the existence of free will, the nature of persons and firm conditions on moral agency/patienthood; all of which are indispensable concepts to be deployed by any machine able to make moral judgments. No agreement seems forthcoming on these matters, and we don’t hold out hope for (...) machines that can both always do the right thing (on some general ethic) and produce explanations for its behavior that would be understandable to a human confederate. Our tentative solution involves understanding the folk concepts associated with our moral intuitions regarding these matters, and how they might be dependent upon the nature of human cognitive architecture. It is in this spirit that we begin to explore the complexities inherent in human moral judgment via computational theories of the human cognitive architecture, rather than under the extreme constraints imposed by rational-actor models assumed throughout much of the literature on philosophical ethics. After discussing the various advantages and challenges of taking this particular perspective on the development of artificial moral agents, we computationally explore a case study of human intuitions about the self and causal responsibility. We hypothesize that a significant portion of the variance in reported intuitions for this case might be explained by appeal to an interplay between the human ability to mindread and to the way that knowledge is organized conceptually in the cognitive system. In the present paper, we build on a pre-existing computational model of mindreading (Bello et al. 2007) by adding constraints related to psychological distance (Trope and Liberman 2010), a well-established psychological theory of conceptual organization. Our initial results suggest that studies of folk concepts involved in moral intuitions lead us to an enriched understanding of cognitive architecture and a more systematic method for interpreting the data generated by such studies. (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)

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)