In this paper we apply a general account of practical reasoning to arguing about legal cases. In particular, we provide a reconstruction of the reasoning of the majority and dissenting opinions for a particular well-known case from property law. This is done through the use of Belief-Desire-Intention (BDI) agents to replicate the contrasting views involved in the actual decision. This reconstruction suggests that the reasoning involved can be separated into three distinct levels: factual and normative levels (...) and a level connecting the two, with conclusions at one level forming premises at the next. We begin by summarising our general approach, which uses instantiations of an argumentation scheme to provide presumptive justifications for actions, and critical questions to identify arguments which attack these justifications. These arguments and attacks are organised into argumentation frameworks to identify the status of individual arguments. We then discuss the levels of reasoning that occur in this reconstruction and the properties and significance of each of these levels. We illustrate the different levels with short examples and also include a discussion of the role of precedents within these levels of reasoning. (shrink)

(2011). Casuistry: Case-based Reasoning for the Ethical Journalist. Journal of Mass Media Ethics: Vol. 26, Media Accountability Part Two, pp. 88-92. doi: 10.1080/08900523.2011.532386.

In this paper Michael Vazquez and Dustin Webster consider the practice of deliberating about ethical case studies as a means to contribute to the professional development of educators. An ongoing debate is whether or not the study of ethical theory should be included in this practice. Vazquez and Webster argue that a popular strategy, known as the Phronetic Approach, is vulnerable to what they call “epistemic blinders” that arise in the absence of the scaffolding provided by theory. They then (...) sketch an alternative approach to case-based reasoning inspired by Barbara Herman's notion of middle theory. The middle theory approach naturally suggests a balanced method for using case studies in teacher professional development: expose educators to some theory, but only to the degree and at the level appropriate for the specific audience and in light of how frequent interactions with that audience will be. (shrink)

With the deployment of information and communication technologies and the needs of data and information sharing within cities, smart city aims to provide value-added services to improve citizens’ quality of life. But, currently city planners/developers are faced with inadequate contextual information on the dimensions of smart city required to achieve a sustainable society. Therefore, in achieving sustainable society, there is need for stakeholders to make strategic decisions on how to implement smart city initiatives. Besides, it is required to specify the (...) smart city dimensions to be adopted in making cities smarter for sustainability attainment. But, only a few methods such as big data, internet of things, cloud computing, etc. have been employed to support smart city attainment. Thus, this study integrates case-based reasoning as an artificial intelligence technique to develop a recommender system towards promoting smart city planning. CBR provides suggestions on smart city dimensions to be adopted by city planners/decision-makers in making cities smarter and sustainable. Accordingly, survey data were collected from 115 respondents to evaluate the applicability of the implemented CBR recommender system in relation to how the system provides best practice recommendations and retaining of smart city initiatives. Results from descriptive and exploratory factor analyses suggest that the developed system is applicable in supporting smart city adoption. Besides, findings from this study are expected to provide valuable insights for practitioners to develop more practical strategies and for researchers to better understand smart city dimensions. (shrink)

Reasoners compare problems to prior cases to draw conclusions about a problem and guide decision making. All Case-Based Reasoning (CBR) employs some methods for generalizing from cases to support indexing and relevance assessment and evidences two basic inference methods: constraining search by tracing a solution from a past case or evaluating a case by comparing it to past cases. Across domains and tasks, however, humans reason with cases in subtly different ways evidencing different mixes of (...) and mechanisms for these components.In recent CBR research in Artificial Intelligence (AI), five paradigmatic approaches have emerged: statistically-oriented, model-based, planning/design-oriented, exemplar-based, and adversarial or precedent-based. The paradigms differ in the assumptions they make about domain models, the extent to which they support symbolic case comparison, and the kinds of inferences for which they employ cases. (shrink)

This paper takes up Berman and Hafner's (1993) challenge to model legal case-based reasoning not just in terms of factual similarities and differences but also in terms of the values that are at stake. The formal framework of Prakken and Sartor (1998) is applied to examples of case-based reasoning involving values, and a method for formalising such examples is proposed. The method makes it possible to express that a case should be decided in (...) a certain way because that advances certain values. The method also supports the comparison of conflicting precedents in terms of values, and it supports debates on the relevance of distinctions in terms of values. (shrink)

The use of case-based reasoning in teaching professional ethics has come of age. The fields of medicine, engineering, and business all have incorporated ethics case studies into leading textbooks and journal articles, as well as undergraduate and graduate professional ethics courses. The most recent guidelines from the National Institutes of Health recognize case studies and face-to-face discussion as best practices to be included in training programs for the Responsible Conduct of Research. While there is a (...) general consensus that case studies play a central role in the teaching of professional ethics, there is still much to be learned regarding how professionals learn ethics using case-based reasoning. Cases take many forms, and there are a variety of ways to write them and use them in teaching. This paper reports the results of a study designed to investigate one of the issues in teaching case-based ethics: the role of one’s professional knowledge in learning methods of moral reasoning. Using a novel assessment instrument, we compared case studies written and analyzed by three groups of students whom we classified as: Experts in a research domain in bioengineering. Novices in a research domain in bioengineering. The non-research group—students using an engineering domain in which they were interested but had no in-depth knowledge. This study demonstrates that a student’s level of understanding of a professional knowledge domain plays a significant role in learning moral reasoning skills. (shrink)

The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation LCBR. Ontologies for different systems allows comparison and contrast between them. OWL ontologies are standardised, machine-readable formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and to LCBR are (...) discussed. Two LCBR systems (AS-CATO, which is based on CATO, and IBP) are analysed in terms of basic and intermediate concepts. Central components of the OWL ontologies for these systems are presented, pointing out differences and similarities. The main novelty of the paper is the ontological analysis and representation in OWL of LCBR systems. The paper also emphasises the important issues concerning the representation and reasoning of intermediate concepts. (shrink)

This paper discusses a recent turn in the ethics of refugee resettlement which involves taking the interests of refugees themselves into account in the distribution of refugees among potential refugee receiving countries. It argues that there is an important category of interest that does not align with the two commonly held views on what is owed to refugees: ‘safety’ or ‘conditions of a good life’. This category, focussing on the refugees’ interests in not being subjected to a variety of non-asylum-grounding (...) injustices, should, by default, take precedence in the assessment of the refugee-based reasons in refugee resettlement. The normative salience of this category – not being subjected to injustice – is illustrated with the help of the case of LGBTIQ+ refugees, and the kinds of injustices they may be subject to in countries that provide them with asylum. (shrink)

Case-based reasoning is a familiar method of evaluating sentences. But when applied to conditionals, it seems to lead to implausible conclusions. In this paper I argue that the problem arises from equating the probability of a conditional sentence on the evidential supposition of some condition with the conditional probability of the former, given the latter.

This paper proposes a formal top-level model of explaining the outputs of machine-learning-based decision-making applications and evaluates it experimentally with three data sets. The model draws on AI & law research on argumentation with cases, which models how lawyers draw analogies to past cases and discuss their relevant similarities and differences in terms of relevant factors and dimensions in the problem domain. A case-based approach is natural since the input data of machine-learning applications can be seen as (...) cases. While the approach is motivated by legal decision making, it also applies to other kinds of decision making, such as commercial decisions about loan applications or employee hiring, as long as the outcome is binary and the input conforms to this paper’s factor- or dimension format. The model is top-level in that it can be extended with more refined accounts of similarities and differences between cases. It is shown to overcome several limitations of similar argumentation-based explanation models, which only have binary features and do not represent the tendency of features towards particular outcomes. The results of the experimental evaluation studies indicate that the model may be feasible in practice, but that further development and experimentation is needed to confirm its usefulness as an explanation model. Main challenges here are selecting from a large number of possible explanations, reducing the number of features in the explanations and adding more meaningful information to them. It also remains to be investigated how suitable our approach is for explaining non-linear models. (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)

Computational models of relevance in case-based legal reasoning have traditionallybeen based on algorithms for comparing the facts and substantive legal issues of aprior case to those of a new case. In this paper we argue that robust models ofcase-based legal reasoning must also consider the broader social and jurisprudentialcontext in which legal precedents are decided. We analyze three aspects of legalcontext: the teleological relations that connect legal precedents to the socialvalues and policies (...) they serve, the temporal relations between prior andsubsequent cases in a legal domain, and the procedural posture of legal cases,which defines the scope of their precedential relevance. Using real examples drawnfrom appellate courts of New York and Massachusetts, we show with the courts' ownarguments that the doctrine of stare decisis (i.e., similar facts should lead to similar results) is subject to contextual constraints and influences. For each of the three aspects of legal context, we outline an expanded computational framework for case-based legal reasoning that encompasses the reasoning of the examples, and provides a foundation for generating a more robust set of legal arguments. (shrink)

My aim in this paper is to critically assess the idea that reasons for action are provided by desires (the Desire-based Reasons Model or the Model). I start from the claim that the most often employed meta-ethical background for the Model is ethical naturalism; I then consider attempts to argue against the Model through its naturalism. I make use of two objections that are both intended to refute naturalism per se. One is the indirect version of G. E. Moore’s (...) Open Question Argument (OQA), the other is Derek Parfit’s more recent Triviality Objection (TO). I show that naturalists might be able to avoid both objections in case the reduction they propose is tolerable. This, however, means that in order to see if the objections work, we must analyze the particular reductions proposed. Hence, though not knock down arguments as they were intended to be, the indirect OQA and TO may pose threat to the Model. (shrink)

We experimentally investigate the disposition of decision makers to use case-based reasoning as suggested by Hume and formalized by case-based decision theory. Our subjects face a monopoly decision problem about which they have very limited information. Information is presented in a manner which makes similarity judgements according to the feature matching model of Tversky plausible. We provide subjects a “history” of cases. In the 2×2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2\times 2$$\end{document} between-subject (...) design, we vary whether information about the current market is given and whether immediate feedback about obtained profits is provided. The results provide support for the predictions of case-based decision theory, particularly when no immediate feedback is provided. (shrink)

토머스 쿤이 남긴 개념체계와 추론에 대한 개요는 인지과학의 성과에 힘입어 더욱 정교한 이론으로 발전했으며, 이러한 인지적 접근은 그동안 해명하기 어려웠던 과학 활동의 동학을 설명하는 데 매우 유용한 틀을 제공하고 있다. 이러한 접근은 그동안 강조되어 왔던 규칙과 정의 및 정언적 합리성의 역할을 축소시키는 한편, 그 자리에 유사관계에 의거한 개념체계와 사례/모형 기반 추론을 채우고, 과학 활동의 핵심에 과학의 ‘내용’이 아닌 과학을 수행하는 ‘인지적 행위자’를 둠으로써, 과학 활동의 양식과 내용의 변화를 유연하게 설명하는 데 상당한 성과를 내고 있다. 그러나 일반적인 인간의 인지적 능력만으로는 과학 (...) 연구의 방향이 결정되지 않으며, 그렇기에 부각되는 것이 ‘과학자가 어떤 문제를 풀고 있는가’와 ‘그가 동원할 수 있는 자원이 무엇인가’이다. 이 점에서 과학은 경로 의존성을 가지게 되며, 과학의 역사적, 사회적 차원은 과학 활동을 설명하기 위한 중요한 자원이 된다. (shrink)

This paper starts out from the proposition that case-based decision theory is an appropriate tool to explain human decision behavior in situations of structural ignorance. Although the developers of CBDT suggest its reality adequacy, CBDT has not yet been tested empirically very often, especially not in repetitive decision situations. Therefore, our main objective is to analyse the decision behavior of subjects in a repeated-choice experiment by comparing the explanation power of CBDT to reinforcement learning and to classical decision (...) criteria under uncertainty namely maximin, maximax, and pessimism-optimism. Our findings substantiate a predominant significantly higher validity of CBDT compared to the classical criteria and to reinforcement learning. For this reason, the experimental results confirm the suggested reality adequacy of CBDT in repetitive decision situations of structural ignorance. (shrink)

Group-based reasons are reasons to play one’s part in some pattern of action that the members of some group could perform, because of the good features of the pattern. This paper discusses three broad conceptions of such reasons. According to the agency-first conception, there are no group-based reasons in cases where the relevant group is not or would not be itself an agent. According to the behaviour-first conception, what matters is that the other members of the group would (...) play their parts in the relevant pattern, not whether they would have the cooperative intentional states constitutive of group agency in doing so. This paper argues against these conceptions and in favour of the powers-first conception, according to which what matters is that the members of the group have practically relevant powers. (shrink)

Case-based instruction has been regarded by many as a viable alternative to traditional lecture-based education and training. However, little is known about how case-based training techniques impact training effectiveness. This study examined the effects of two such techniques: (a) presentation of alternative outcome scenarios to a case, and (b) conducting a structured outcome evaluation. Consistent with the hypotheses, results indicate that presentation of alternative outcome scenarios reduced knowledge acquisition, reduced sensemaking and ethical decision-making strategy (...) use, and reduced decision ethicality. Conducting a structured outcome evaluation had no impact on these outcomes. Results indicate that those who use case-based instruction should take care to use clear, less complex cases with only a singular outcome if they are seeking these types of outcomes. (shrink)

In a legal expert system based on CBR (Case-Based Reasoning), legal statute rules are interpreted on the basis of precedents. This interpretation, because of its vagueness and uncertainty of the interpretation cannot be handled with the means used for crisp cases. In our legal expert system, on the basis of the facts of precedents, the statute rule is interpreted as a form of case rule, the application of which involves the concepts of membership and vagueness. (...) The case rule is stored in a data base by means of fuzzy frames. The inference based on a case rule is made by fuzzy YES and fuzzy NO, and the degree of similarity of cases. The system proposed here will be used for legal education; its main area of application is contract, especially in relation to the United Nations Convention on Contracts for the International Sale of Goods (CISG). (shrink)

Case-based reasoning has long been used to facilitate instructional effectiveness. Although much remains to be known concerning the most beneficial way to present case material, recent literature suggests that simplifying case material is favorable. Accordingly, the current study manipulated two instructional techniques, incremental case presentation and forecasting outcomes, in a training environment in an attempt to better understand the utility of simplified versus complicated case presentation for learning. Findings suggest that pairing these two (...) cognitively demanding techniques reduces satisfaction and detracts from the effectiveness of the learning approach. Implications regarding the use of instructional techniques in training programs are discussed. (shrink)