Making sense of AI: how lay users negotiate the shifting human–machine boundaries in talking about AI

IF 6.1 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Patricia Jimenez, Younhee Kim, Richard Fitzgerald
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引用次数: 0

Abstract

This paper examines how lay users make sense of artificial intelligence (AI) in everyday encounters and through practical reasoning and situated categorisation practices. Drawing on data from digital diaries and in-person group discussions, the study explores the local and situated ways lay users determine what kind of “thing” AI is, what it does, and how it should be judged. Rather than approaching AI as a fixed defined entity, the paper centres in participants procedures for meaning making. Specifically, the analysis focuses on three categorisation practices: the relational exclusion of the human-machine device, the assemblage of branched taxonomies, and the troubling of categorial boundaries. These practices reflect an ongoing negotiation of intelligibility, in which AI is explained not through formal and technically accurate definitions but through occasioned and socially recognisable use of every day categories. The paper draws on Membership Categorisation Analysis and Occasioned Semantics to show that the intelligibility of AI is both locally and culturally accomplished. In doing so, the paper reframes the notion of AI explainability as a situated achievement of human reasoning, rather than a system’s feature. An insight, we hope would have implications, if not at least a provocation, to the field of explainable AI and, more broadly, to the way we understand AI literacy, trust, and the everyday grammar of intelligence.

理解人工智能:外行用户在谈论人工智能时如何协调不断变化的人机边界
本文研究了外行用户如何在日常遭遇中以及通过实际推理和情境分类实践来理解人工智能(AI)。根据数字日记和面对面小组讨论的数据,该研究探索了本地和情境用户确定人工智能是什么样的“东西”、它做什么以及应该如何判断它的方式。本文没有将人工智能视为一个固定的定义实体,而是以参与者的意义生成过程为中心。具体来说,分析集中在三种分类实践:人机设备的关系排斥,分支分类法的组合,以及分类边界的麻烦。这些实践反映了对可理解性的持续协商,其中人工智能不是通过正式和技术上准确的定义来解释的,而是通过日常类别的偶然和社会可识别的使用来解释的。本文利用隶属度分类分析和偶然语义来表明人工智能的可理解性是本地和文化共同完成的。在此过程中,本文将人工智能可解释性的概念重新定义为人类推理的一种情境成就,而不是系统的特征。我们希望这一见解对可解释的人工智能领域产生影响,如果不是至少是一种挑衅,更广泛地说,对我们理解人工智能读写、信任和日常智能语法的方式产生影响。
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来源期刊
AI & Society
AI & Society COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
8.00
自引率
20.00%
发文量
257
期刊介绍: AI & Society: Knowledge, Culture and Communication, is an International Journal publishing refereed scholarly articles, position papers, debates, short communications, and reviews of books and other publications. Established in 1987, the Journal focuses on societal issues including the design, use, management, and policy of information, communications and new media technologies, with a particular emphasis on cultural, social, cognitive, economic, ethical, and philosophical implications. AI & Society has a broad scope and is strongly interdisciplinary. We welcome contributions and participation from researchers and practitioners in a variety of fields including information technologies, humanities, social sciences, arts and sciences. This includes broader societal and cultural impacts, for example on governance, security, sustainability, identity, inclusion, working life, corporate and community welfare, and well-being of people. Co-authored articles from diverse disciplines are encouraged. AI & Society seeks to promote an understanding of the potential, transformative impacts and critical consequences of pervasive technology for societies. Technological innovations, including new sciences such as biotech, nanotech and neuroscience, offer a great potential for societies, but also pose existential risk. Rooted in the human-centred tradition of science and technology, the Journal acts as a catalyst, promoter and facilitator of engagement with diversity of voices and over-the-horizon issues of arts, science, technology and society. AI & Society expects that, in keeping with the ethos of the journal, submissions should provide a substantial and explicit argument on the societal dimension of research, particularly the benefits, impacts and implications for society. This may include factors such as trust, biases, privacy, reliability, responsibility, and competence of AI systems. Such arguments should be validated by critical comment on current research in this area. Curmudgeon Corner will retain its opinionated ethos. The journal is in three parts: a) full length scholarly articles; b) strategic ideas, critical reviews and reflections; c) Student Forum is for emerging researchers and new voices to communicate their ongoing research to the wider academic community, mentored by the Journal Advisory Board; Book Reviews and News; Curmudgeon Corner for the opinionated. Papers in the Original Section may include original papers, which are underpinned by theoretical, methodological, conceptual or philosophical foundations. The Open Forum Section may include strategic ideas, critical reviews and potential implications for society of current research. Network Research Section papers make substantial contributions to theoretical and methodological foundations within societal domains. These will be multi-authored papers that include a summary of the contribution of each author to the paper. Original, Open Forum and Network papers are peer reviewed. The Student Forum Section may include theoretical, methodological, and application orientations of ongoing research including case studies, as well as, contextual action research experiences. Papers in this section are normally single-authored and are also formally reviewed. Curmudgeon Corner is a short opinionated column on trends in technology, arts, science and society, commenting emphatically on issues of concern to the research community and wider society. Normal word length: Original and Network Articles 10k, Open Forum 8k, Student Forum 6k, Curmudgeon 1k. The exception to the co-author limit of Original and Open Forum (4), Network (10), Student (3) and Curmudgeon (2) articles will be considered for their special contributions. Please do not send your submissions by email but use the "Submit manuscript" button. NOTE TO AUTHORS: The Journal expects its authors to include, in their submissions: a) An acknowledgement of the pre-accept/pre-publication versions of their manuscripts on non-commercial and academic sites. b) Images: obtain permissions from the copyright holder/original sources. c) Formal permission from their ethics committees when conducting studies with people.
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