arXiv 2303.055002023-03-09cs.CYcs.AIcs.HC

用户是AI透明度的北极星

Users are the North Star for AI Transparency

University of California, Santa Barbara（加州大学圣巴巴拉分校）；Carnegie Mellon University（卡内基梅隆大学）

Alex Mei, Michael Saxon, Shiyu Chang, Zachary C. Lipton, William Yang Wang

备注：: 9 pages, 3 tables

摘要：

尽管人们普遍呼吁建立透明的人工智能系统，但这个词的含义太过不同，无法表达精确的政策目标或确定具体的研究方向。因此，各利益攸关方往往各执一词，决策者表达的要求模糊不清，而从业人员制定的解决方案可能无法解决根本的关切。发生这种情况的部分原因是，人工智能透明度的明确理想在这部分工作中并未提及。我们明确地命名了这样一颗北极星--以用户为中心、用户适当和诚实的透明度。我们进行了广泛的文献调查，确定了许多类似的透明度概念集群，将每个集群与我们的北极星联系起来，分析它如何促进或阻碍我们理想的人工智能透明度目标。最后，我们讨论了所有集群的共同点，以提供更清晰的共同语言，使政策制定者，利益相关者和从业者能够传达具体的需求并提供适当的解决方案。我们希望未来在人工智能透明度方面的工作能够进一步推进自信、用户受益的目标，并为监管机构和开发人员提供清晰度。

英文摘要：

Despite widespread calls for transparent artificial intelligence systems, the term is too overburdened with disparate meanings to express precise policy aims or to orient concrete lines of research. Consequently, stakeholders often talk past each other, with policymakers expressing vague demands and practitioners devising solutions that may not address the underlying concerns. Part of why this happens is that a clear ideal of AI transparency goes unsaid in this body of work. We explicitly name such a north star -- transparency that is user-centered, user-appropriate, and honest. We conduct a broad literature survey, identifying many clusters of similar conceptions of transparency, tying each back to our north star with analysis of how it furthers or hinders our ideal AI transparency goals. We conclude with a discussion on common threads across all the clusters, to provide clearer common language whereby policymakers, stakeholders, and practitioners can communicate concrete demands and deliver appropriate solutions. We hope for future work on AI transparency that further advances confident, user-beneficial goals and provides clarity to regulators and developers alike.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

摘要：

英文摘要：

相关论文