More Than "If Time Allows": The Role of Ethics in AI Education

Natalie Garrett, Nathan Beard, Casey Fiesler
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引用次数: 62

Abstract

Even as public pressure mounts for technology companies to consider societal impacts of products, industries and governments in the AI race are demanding technical talent. To meet this demand, universities clamor to add technical artificial intelligence (AI) and machine learning (ML) courses into computing curriculum-but how are societal and ethical considerations part of this landscape? We explore two pathways for ethics content in AI education: (1) standalone AI ethics courses, and (2) integrating ethics into technical AI courses. For both pathways, we ask: What is being taught? As we train computer scientists who will build and deploy AI tools, how are we training them to consider the consequences of their work? In this exploratory work, we qualitatively analyzed 31 standalone AI ethics classes from 22 U.S. universities and 20 AI/ML technical courses from 12 U.S. universities to understand which ethics-related topics instructors include in courses. We identify and categorize topics in AI ethics education, share notable practices, and note omissions. Our analysis will help AI educators identify what topics should be taught and create scaffolding for developing future AI ethics education.
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超越“如果时间允许”:伦理在人工智能教育中的作用
尽管公众要求科技公司考虑产品的社会影响的压力越来越大,但参与人工智能竞赛的行业和政府仍然需要技术人才。为了满足这一需求,大学纷纷在计算机课程中加入技术人工智能(AI)和机器学习(ML)课程,但社会和伦理考虑如何成为这一领域的一部分?我们探索了人工智能教育中伦理内容的两条路径:(1)独立的人工智能伦理课程,(2)将伦理融入技术人工智能课程。对于这两种途径,我们都要问:教授了什么?当我们培训将构建和部署人工智能工具的计算机科学家时,我们如何训练他们考虑他们工作的后果?在这项探索性工作中,我们定性分析了来自22所美国大学的31门独立的人工智能伦理课程和来自12所美国大学的20门人工智能/机器学习技术课程,以了解教师在课程中包含哪些伦理相关主题。我们对人工智能伦理教育中的主题进行识别和分类,分享值得注意的实践,并指出遗漏。我们的分析将帮助人工智能教育工作者确定应该教授哪些主题,并为发展未来的人工智能伦理教育创建框架。
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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