弥合差距：人工智能信任工程工具

IF 0.7 Q4 ERGONOMICS

Ergonomics in Design Pub Date : 2024-05-08 DOI:10.1177/10648046241249903

Stephen L. Dorton, Jeff C. Stanley

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引用次数: 0

摘要

信任在人工智能（AI）技术开发中的重要性日益得到共识和重视；然而，人们对基于原则的框架存在依赖。最近的研究凸显了原则/实践之间的差距，在这种情况下，仅有原则是不可行的，在开发更值得信赖的人工智能方面也不一定完全有效。我们主张使用基于证据的补充工具来缩小原则/实践差距，并提出了 ELATE（人工智能信任工程探索性问题证据清单）作为这样一种资源。我们将讨论几种工具或方法，使 ELATE 在系统开发中具有可操作性。

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Minding the Gap: Tools for Trust Engineering of Artificial Intelligence

There is growing consensus and appreciation for the importance of trust in the development of Artificial Intelligence (AI) technologies; however, there is a reliance on principles-based frameworks. Recent research has highlighted the principles/practice gap, where principles alone are not actionable, and may not be wholly effective in developing more trustworthy AI. We argue for complementary, evidence-based tools to close the principles/practice gap, and present ELATE (Evidence-Based List of Exploratory Questions for AI Trust Engineering) as one such resource. We discuss several tools or approaches for making ELATE actionable within the context of systems development.

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来源期刊

Ergonomics in Design ERGONOMICS-

CiteScore

4.00

自引率

0.00%

发文量

期刊介绍： Ergonomics in Design: The Quarterly of Human Factors Applications is intended to serve the needs of practicing human factors/ergonomics professionals who are concerned with the usability of products, systems, tools, and environments. It provides up-to-date demonstrations of the importance of HF/E principles in design and implementation. Articles, case studies, anecdotes, debates, and interviews focus on the way in which HF/E research and methods are applied in the design, development, prototyping, test and evaluation, training, and manufacturing processes of a product or system.