Rethinking the Ethics of GenAI in Higher Education: A Critique of Moral Arguments and Policy Implications

IF 0.9 2区 哲学 Q4 ETHICS
Karl de Fine Licht
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引用次数: 0

Abstract

This article critically examines the moral arguments for restrictive policies regarding student use of generative AI in higher education. While existing literature addresses various concerns about AI in education, there has been limited rigorous ethical analysis of arguments for restricting its use. This article analyzes two main types of moral arguments: those based on direct difference-making (where individual university actions have measurable impacts) and those centered on non-difference-making participation (where symbolic participation in harmful systems matters regardless of direct impact). Key concerns examined include environmental harm from AI energy consumption, exploitative labor practices in AI development, and privacy risks. Through careful analysis, the article argues that these arguments face significant challenges when examined in depth. The difference-making arguments often fail to establish that individual university actions meaningfully contribute to claimed harms, while the non-difference-making arguments lead to impractical conclusions when applied consistently across university operations. Rather than supporting blanket restrictions, the analysis suggests universities should focus on fostering responsible AI engagement through ethical guidelines, licensed tools, and education on responsible use. The article concludes that a balanced approach considering both moral and practical factors is more effective than restrictive policies in addressing ethical concerns while preserving educational benefits.

重新思考高等教育中的遗传伦理:对道德争论和政策影响的批判
本文批判性地考察了关于学生在高等教育中使用生成人工智能的限制性政策的道德论点。虽然现有文献解决了人工智能在教育中的各种问题,但对限制其使用的论点进行严格的伦理分析却有限。本文分析了两种主要的道德论点:基于直接影响(个别大学的行为具有可衡量的影响)的道德论点和以非影响参与为中心的道德论点(无论直接影响如何,对有害系统的象征性参与都很重要)。研究的主要问题包括人工智能能源消耗对环境的危害、人工智能开发中的剥削性劳动行为以及隐私风险。通过仔细的分析,本文认为,当深入研究时,这些论点面临重大挑战。造成差异的论点往往无法证明个别大学的行为有意义地造成了声称的伤害,而非造成差异的论点在整个大学运作中一致应用时导致不切实际的结论。分析表明,大学不应支持全面限制,而应通过道德准则、许可工具和负责任使用的教育,专注于促进负责任的人工智能参与。文章的结论是,考虑道德和实际因素的平衡方法比限制性政策在解决伦理问题的同时保持教育利益更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
71
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