AI for Not Bad.
AI for Not Bad.
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DOI：
10.3389/fdata.2019.00032
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发表时间：
2019
影响因子：
3.1
通讯作者：
Moore J
中科院分区：
文献类型：
--
作者：
Moore J
炒作围绕着“人工智能 (AI) 造福社会”及其相关排列的宣传、愿望和概念。这些术语在数据科学中，特别是在公共话语中使用时，是模糊的。这些术语与数据科学家或人工智能从业者绝非无关，它们创造了所构建系统的公众概念。通过批判性反思，我探讨了人工智能社会公益的概念是如何模糊的，提供的判断标准不足，并忽略了人工智能系统的外部性和结构性相互依赖。相反，“人工智能造福社会”这个领域最好理解为“人工智能不坏”。
Hype surrounds the promotions, aspirations, and notions of “artificial intelligence (AI) for social good” and its related permutations. These terms, as used in data science and particularly in public discourse, are vague. Far from being irrelevant to data scientists or practitioners of AI, the terms create the public notion of the systems built. Through a critical reflection, I explore how notions of AI for social good are vague, offer insufficient criteria for judgement, and elide the externalities and structural interdependence of AI systems. Instead, the field known as “AI for social good” is best understood and referred to as “AI for not bad.”