8,196 research outputs found

    Commentary on “Eliminating Gender-, Racial- and Age-Biases in Medical Diagnostic Reasoning”

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    Computer Decision-Support Systems for Public Argumentation: Criteria for Assessment

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    Informal fallacies as cognitive heuristics in public health reasoning

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    The public must make assessments of a range of health-related issues. However, these assessments require scientific knowledge which is often lacking or ineffectively utilized by the public. Lay people must use whatever cognitive resources are at their disposal to come to judgement on these issues. It will be contended that a group of arguments - so-called informal fallacies - are a valuable cognitive resource in this regard. These arguments serve as cognitive heuristics which facilitate reasoning when knowledge is limited or beyond the grasp of reasoners. The results of an investigation into the use of these arguments by the public are reported

    A literature review. Introduction to the special issue

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    UIDB/00183/2020 UIDP/00183/2020 PTDC/FER-FIL/28278/2017 CHIST-ERA/0002/2019Argumentation schemes [35, 80, 91] are a relatively recent notion that continues an extremely ancient debate on one of the foundations of human reasoning, human comprehension, and obviously human argumentation, i.e., the topics. To understand the revolutionary nature of Walton’s work on this subject matter, it is necessary to place it in the debate that it continues and contributes to, namely a view of logic that is much broader than the formalistic perspective that has been adopted from the 20th century until nowadays. With his book Argumentation schemes for presumptive reasoning, Walton attempted to start a dialogue between three different fields or views on human reasoning – one (argumentation theory) very recent, one (dialectics) very ancient and with a very long tradition, and one (formal logic) relatively recent, but dominating in philosophy. Argumentation schemes were proposed as dialectical instruments, in the sense that they represented arguments not only as formal relations, but also as pragmatic inferences, as they at the same time depend on what the interlocutors share and accept in a given dialogical circumstance, and affect their dialogical relation. In this introduction, the notion of argumentation scheme will be analyzed in detail, showing its different dimensions and its defining features which make them an extremely useful instrument in Artificial Intelligence. This theoretical background will be followed by a literature review on the uses of the schemes in computing, aimed at identifying the most important areas and trends, the most promising proposals, and the directions of future research.publishersversionpublishe

    Towards an authentic argumentation literacy test

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    A central goal of education is to improve argumentation literacy. How do we know how well this goal is achieved? Can we measure argumentation literacy? The present study is a preliminary step towards measuring the efficacy of education with regards to argumentation literacy. Tests currently in use to determine critical thinking skills are often similar to IQ-tests in that they predominantly measure logical and mathematical abilities. Thus, they may not measure the various other skills required in understanding authentic argumentation. To identify the elements of argumentation literacy, this exploratory study begins by surveying introductory textbooks within argumentation theory, critical thinking, and rhetoric. Eight main abilities have been identified. Then, the study outlines an Argumentation Literacy Test that would comprise these abilities suggested by the literature. Finally, the study presents results from a pilot of a version of such a test and discusses needs for further development

    Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

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    Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future
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