The European way of doing Artificial Intelligence: The state of play implementing Trustworthy AI

Bern Beckert
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引用次数: 1

Abstract

“Trustworthy AI” is the concept of the European Commission to facilitate acceptance and diffusion of Artificial Intelligence in Europe. The concept claims that European AI applications shall be lawful, ethical and robust, both from a technical and societal perspective. The contribution asks for the state of play of implementing the concept of Trustworthy AI. More concretely, it sets out to identify concrete cases of implementing Trustworthy AI in order to analyse approaches and experiences. However, it turns out that such projects currently only exist in a research context and at neither large companies nor start-ups or medium-sized companies provide suitable examples, with only a few exceptions. This gives rise to the question, why companies today ignore or even avoid the carefully worked out guidelines to implement Trustworthy AI. Three answers are given which refer to time-to-market considerations, different mindsets of software engineers and social scientists, and the fact that implementing Trustworthy AI requires of firms to go the extra mile with additional expertise and governance structures. Following this, two possibilities are presented to increase in the number of companies actually picking up on the guidelines and concretely implementing Trustworthy AI. These possibilities are firstly to break down existing implementation guidelines to the requirements of software engineers, computer scientists and managers, and secondly to embed social scientists and stakeholders in the implementation process.
欧洲人做人工智能的方式:实现可信赖人工智能的状态
“值得信赖的人工智能”是欧盟委员会为促进人工智能在欧洲的接受和传播而提出的概念。该概念声称,从技术和社会的角度来看,欧洲的人工智能应用应该是合法的、道德的和强大的。该贡献要求实现可信赖的人工智能概念的状态。更具体地说,它旨在确定实施可信赖人工智能的具体案例,以分析方法和经验。然而,事实证明,这样的项目目前只存在于研究背景下,无论是大公司还是初创企业或中型公司都没有提供合适的例子,只有少数例外。这就产生了一个问题,为什么今天的公司忽视甚至回避了精心制定的指导方针,以实施值得信赖的人工智能。给出了三个答案,涉及到上市时间的考虑,软件工程师和社会科学家的不同心态,以及实施值得信赖的人工智能需要公司在额外的专业知识和治理结构方面付出额外的努力。在此之后,提出了两种可能性,以增加实际接受指导方针并具体实施可信赖人工智能的公司数量。这些可能性首先是将现有的实施指南分解为软件工程师、计算机科学家和管理人员的需求,其次是将社会科学家和利益相关者嵌入到实施过程中。
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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