大学生算法素养的伦理维度:案例研究与跨学科联系

IF 2.5 3区 管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Susan Gardner Archambault , Shalini Ramachandran , Elisa Acosta , Sheree Fu
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引用次数: 0

摘要

本文探讨了与算法素养的伦理层面相关的三个关键问题。首先,文章综合现有文献,确定了六个核心伦理要素,包括偏见、隐私、透明度、问责制、准确性和非恶意性。其次,交叉分析了这些原则在大学与研究图书馆协会的《高等教育信息素养框架》和计算机协会的《道德与职业行为准则》以及《负责任的算法系统原则联合声明》中的交叉点。这项分析揭示了在不公平和透明度等问题上的重大重叠,有助于确定教学主题的优先次序。最后,案例研究展示了根据交叉分析结果制定的伦理教学策略。针对不同本科生和计算机科学专业学生的研讨会采用了算法偏差的真实案例,以引发对意外伤害、可竞争性和负责任开发的反思。事后调查显示,干预措施扩大了批判性视角。通过系统地研究共同的价值观和测试教学方法,本研究提供了塑造算法伦理思维的实用工具。它还展示了跨学科负责任地推进算法素养的可行做法。归根结底,培养跨学科意识和多管齐下的教育举措可以让学生有能力质疑算法的权威性和偏见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ethical dimensions of algorithmic literacy for college students: Case studies and cross-disciplinary connections

This article addresses three key questions related to the ethical facets of algorithmic literacy. First, it synthesizes existing literature to identify six core ethical components, including bias, privacy, transparency, accountability, accuracy, and non-maleficence. Second, a crosswalk maps the intersections of these principles across the Association of College and Research Libraries' Framework for Information Literacy for Higher Education and the Association of Computing Machinery's Code of Ethics and Professional Conduct and Joint Statement on Principles for Responsible Algorithmic Systems. This analysis reveals significant overlap on issues like unfairness and transparency, helping prioritize topics for instruction. Finally, case studies showcase pedagogical strategies for teaching ethical considerations, informed by the crosswalk. Workshops for diverse undergraduates and computer science students employed reallife instances of algorithmic bias to prompt reflection on unintended harm, contestability, and responsible development. Pre-post surveys indicated expanded critical perspectives after the interventions. By systematically examining shared values and testing instructional approaches, this study provides practical tools to shape ethical thinking on algorithms. It also demonstrates promising practices for responsibly advancing algorithmic literacy across disciplines. Ultimately, fostering interdisciplinary awareness and multipronged educational initiatives can empower students to question algorithmic authority and biases.

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来源期刊
Journal of Academic Librarianship
Journal of Academic Librarianship INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
5.30
自引率
15.40%
发文量
120
审稿时长
29 days
期刊介绍: The Journal of Academic Librarianship, an international and refereed journal, publishes articles that focus on problems and issues germane to college and university libraries. JAL provides a forum for authors to present research findings and, where applicable, their practical applications and significance; analyze policies, practices, issues, and trends; speculate about the future of academic librarianship; present analytical bibliographic essays and philosophical treatises. JAL also brings to the attention of its readers information about hundreds of new and recently published books in library and information science, management, scholarly communication, and higher education. JAL, in addition, covers management and discipline-based software and information policy developments.
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