Explanations for AI: Computable or Not?
Explanations for AI: Computable or Not?
复制标题
人工智能的解释：可计算还是不可计算？
DOI：
10.1145/3394332.3402900
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Tsakalakis N
中科院分区：
文献类型：
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作者：
Tsakalakis N
自动化决策继续在多个行业中用于各种目的。最终，如何做出“好的”解释不仅是人工智能系统的设计者和开发者关注的焦点，也是许多学科关注的焦点，包括法律、哲学、心理学、历史学、社会学和人机交互。鉴于为人工智能生成合规、有效和有效的解释需要高水平的批判性、跨学科思维和协作，因此该领域对网络科学特别感兴趣。 “人工智能的解释：可计算与否？”（exAI’20）研讨会旨在将研究人员、从业者和那些受到社会敏感决策影响的代表聚集在一起，交流想法、方法和挑战，作为关于人工智能解释的跨学科讨论的一部分。希望本次研讨会能够建立一个跨部门、多学科的国际网络，重点关注人工智能的解释，并制定推动这项工作向前发展的议程。 exAI’20 将举行两场立场文件会议，小组成员和研讨会与会者将在互动对话中就以下关键问题进行辩论：这些会议希望通过在每篇论文后提供互动讨论时间，激发关于人工智能的解释是否可计算的激烈辩论。讨论将揭示支持和反对与社会敏感决策相关的人工智能解释的可计算性的关键论据。 PLEAD（自动决策的起源驱动和法律依据的解释）项目背后的团队将发表介绍性主题演讲，介绍人工智能的用例、场景和解释的实践经验。主题演讲将作为论文会议期间讨论所使用的基本原理、技术和/或组织措施的起点；并且，从不同角度进行叙述——例如软件设计者、实施者和那些接受自动化决策的人。在本次研讨会结束时，与会者将深入了解人工智能解释的批评和优点，包括解释可以或应该可计算的程度。他们将有机会参与并为关于人工智能可解释性的复杂主题的讨论提供信息，例如解释的法律要求、数据伦理可能推动人工智能解释的程度、对人工智能决策和人工决策解释的异同的反思，以及什么是“好的”解释以及社会敏感决策解释的词源。 exAI’20 得到工程和物理科学研究委员会的支持 [授权号 EP/S027238/1]。我们要感谢 Web Science 2019 会议的组织者同意主办我们的研讨会并给予支持。
Automated decision making continues to be used for a variety of purposes within a multitude of sectors. Ultimately, what makes a ‘good’ explanation is a focus not only for the designers and developers of AI systems, but for many disciplines, including law, philosophy, psychology, history, sociology and human-computer interaction. Given that the generation of compliant, valid and effective explanations for AI requires a high-level of critical, interdisciplinary thinking and collaboration, this area is therefore of particular interest for Web Science. The workshop ‘Explanations for AI: Computable or Not?’ (exAI’20) aims to bring together researchers, practitioners and representatives of those subjected to socially-sensitive decision-making to exchange ideas, methods and challenges as part of an interdisciplinary discussion on explanations for AI. It is hoped that this workshop will build a cross-sectoral, multi-disciplinary and international network of people focusing on explanations for AI, and an agenda to drive this work forward. exAI’20 will hold two position paper sessions, where the panel members and workshop attendees will debate the following key issues in an interactive dialogue: The sessions are hoped to stimulate a lively debate on whether explanations for AI are computable or not by providing time for an interactive discussion after each paper. The discussion will uncover key arguments for and against the computability of explanations for AI related to socially-sensitive decision-making. An introductory keynote from the team behind the project PLEAD (Provenance-Driven & Legally Grounded Explanations for Automated Decisions) will present use cases, scenarios and the practical experience of explanations for AI. The keynote will serve as a starting point for the discussions during the paper sessions about the rationale, technologies and/or organisations measures used; and, accounts from different perspectives – e.g. software designers, implementers and those subject to automated decision-making. By the end of this workshop, attendees will have gained a good insight into the critiques and the advantages of explanations for AI, including the extent in which explanations can or should be made computable. They will have the opportunity to participate and inform the discussions on complex topics about AI explainability, such as the legal requirements for explanations, the extent in which data ethics may drive explanations for AI, reflections on the similarities and differences of explanations for AI decisions and manual decisions, as well as what makes a ‘good’ explanation and the etymology of explanations for socially-sensitive decisions. exAI’20 is supported by the Engineering and Physical Sciences Research Council [grant number EP/S027238/1]. We would like to thank the organizers of the Web Science 2019 conference for agreeing to host our workshop and for their support.