Logical Methods for Deontic Explanations

道义解释的逻辑方法

• 批准号: 511915728
• 负责人: Professor Dr. Christian Straßer
• 金额: --
• 依托单位: Institut für Philosophie II
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/511915728?language=en
• 关键词: Logical; Methods; Deontic; Explanations

Deontic reasoning, which involves obligation and related notions, is highly important in a variety of fields---from law and ethics to artificial intelligence. The combination of deontic logic and formal argumentation provides a fruitful theoretical basis for modelling this type of reasoning. The three partners of the "Logical methods for Deontic EXplanations" (LoDEx) project represent important developments in the area: Ciabattoni (Vienna University of Technology) addresses practical concerns in mathematics and logic, Straßer (Ruhr University Bochum) uses formal methods in philosophy, and van der Torre (University of Luxembourg) provides legal and ethical reasoners in computer science and artificial intelligence. Now they are joining forces to develop a formal theory of what they call deontic explanations. Deontic explanations provide reasons why some deontic notions hold and others do not. They provide answers to complex questions like "Why should a child be entrusted to its father, rather than its mother, given a specific context?'' or "Should someone who follows the faith of Jehovah's Witnesses be forced to undergo a life-saving blood transfusion? Why (not)?''. By targeting the understanding and transparent presentation of reasoning processes, deontic explanations are a major concern in many fields. Driven by case studies in (bio)ethics and law, LoDEx develops logical methods with tool support to formalise and reason about deontic explanations. By integrating both preference-based and norm-based explanations, LoDEx takes up the challenge raised by Makinson (1998) and Horty (2014) of formulating a unified logical theory combining several disconnected methods from the field of deontic logic. By means of formal argumentation and dialogues, explanations are tailored to ensure explainee comprehension with the generation of fine-tuned explanations relative to the explainee's preconceptions and expectations. LoDEx fills a central gap in formal theories of normative reasoning, which so far have been concerned with justifications rather than personalised explanations. There is an urgent demand for deontic explanations in law and (bio)ethics, two domains where deontic reasoning is particularly involved and which are rich in conflicts. To meet this demand, the formal methods of LoDEx will be applied to and evaluated on key case studies from these areas. Computer-supported tools will be developed in order to experiment with the methods, the formal legal and bioethical theories, and applications of those theories. We will use the LogiKEy methodology for this purpose. The dissemination of the newly created LogiKEY data sets will enable reusability and facilitate implementations for the deontic logic community. LoDEx methods, tools and applications will contribute to the timely interdisciplinary challenge of providing formal foundations to more human-centred logic and reasoning.

道义推理涉及义务和相关概念，在从法律、伦理到人工智能的各个领域都非常重要。道义逻辑和形式论证的结合为此类推理的建模提供了丰富的理论基础。 “道义解释的逻辑方法”（LoDEx）项目的三个合作伙伴代表了该领域的重要发展：Ciabattoni（维也纳科技大学）解决数学和逻辑方面的实际问题，Straßer（波鸿鲁尔大学）在哲学中使用形式方法，van der Torre（卢森堡大学）提供计算机科学和人工智能方面的法律和伦理推理。现在他们正在联手发展一种他们所谓的道义解释的正式理论。道义解释提供了为什么某些道义概念成立而另一些概念不成立的原因。它们为复杂的问题提供了答案，例如“在特定情况下，为什么应该将孩子托付给父亲，而不是母亲？”或“信仰耶和华见证人的人是否应该被迫接受救命输血？为什么（不）？”。通过以推理过程的理解和透明呈现为目标，道义解释成为许多领域的主要关注点。在（生物）伦理学和法律案例研究的推动下，LoDEx 开发了具有工具支持的逻辑方法，以对道义解释进行形式化和推理。通过整合基于偏好和基于规范的解释，LoDEx 接受了 Makinson (1998) 和 Horty (2014) 提出的挑战，即结合道义逻辑领域的几种互不相关的方法来制定统一的逻辑理论。通过正式的论证和对话，解释是量身定制的，以确保被解释者的理解，并根据被解释者的先入之见和期望生成微调的解释。 LoDEx 填补了规范推理正式理论的一个核心空白，迄今为止，规范推理一直关注的是论证而不是个性化解释。法律和（生物）伦理学迫切需要道义解释，这两个领域特别涉及道义推理，并且充满冲突。为了满足这一需求，LoDEx 的正式方法将应用于这些领域的关键案例研究并对其进行评估。将开发计算机支持的工具，以便对这些方法、正式的法律和生物伦理理论以及这些理论的应用进行实验。为此，我们将使用 LogiKEy 方法。新创建的 LogiKEY 数据集的传播将实现可重用性并促进道义逻辑社区的实现。 LoDEx 方法、工具和应用程序将有助于及时应对跨学科挑战，为更加以人为本的逻辑和推理提供正式基础。