值得信赖的人工智能:综述

Davinder Kaur, Suleyman Uslu, Kaley J. Rittichier, A. Durresi
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引用次数: 137

摘要

人工智能(AI)和算法决策正在对我们的日常生活产生深远的影响。这些系统被广泛应用于不同的高风险应用,如医疗保健、商业、政府、教育和司法,将我们推向一个更加算法化的社会。然而,尽管这些系统有很多优点,但它们有时会直接或间接地对用户和社会造成伤害。因此,使这些系统安全、可靠和值得信赖变得至关重要。在这个方向上提出了一些要求,如公平性、可解释性、问责性、可靠性和可接受性,以使这些系统值得信赖。本调查通过文献的视角分析了所有这些不同的需求。它提供了不同方法的概述,这些方法可以帮助减轻人工智能风险,并通过利用用户和社会增加对系统的信任和接受度。它还讨论了验证和验证这些系统的现有策略以及可信赖人工智能的当前标准化工作。最后,我们对可信人工智能的最新进展进行了全面的介绍,以帮助感兴趣的研究人员有效地掌握该主题的关键方面,并提供可能的未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trustworthy Artificial Intelligence: A Review
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on our daily lives. These systems are vastly used in different high-stakes applications like healthcare, business, government, education, and justice, moving us toward a more algorithmic society. However, despite so many advantages of these systems, they sometimes directly or indirectly cause harm to the users and society. Therefore, it has become essential to make these systems safe, reliable, and trustworthy. Several requirements, such as fairness, explainability, accountability, reliability, and acceptance, have been proposed in this direction to make these systems trustworthy. This survey analyzes all of these different requirements through the lens of the literature. It provides an overview of different approaches that can help mitigate AI risks and increase trust and acceptance of the systems by utilizing the users and society. It also discusses existing strategies for validating and verifying these systems and the current standardization efforts for trustworthy AI. Finally, we present a holistic view of the recent advancements in trustworthy AI to help the interested researchers grasp the crucial facets of the topic efficiently and offer possible future research directions.
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