对质量失去信心:计算机视觉服务的潜规则演变

Alex Cummaudo, Rajesh Vasa, J. Grundy, Mohamed Abdelrazek, A. Cain
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引用次数: 16

摘要

人工智能(AI)和机器学习(ML)的最新进展,如计算机视觉,现在可以作为智能服务使用,它们的可访问性和简单性令人信服。现在,许多供应商将这种技术作为云服务提供,开发人员希望利用这些进步为最终用户提供价值。然而,对于使用这些智能服务所产生的维护和发展风险,尚无确切的调查;特别是,它们的行为一致性和功能的透明度。我们使用3个不同的数据集评估了3种不同智能服务(特别是计算机视觉)在11个月内的响应,根据各自的文档验证了响应并评估了进化风险。我们发现存在:(1)这些服务的行为方式不一致;(2)响应中的演化风险;(3)缺乏记录这些风险和不一致的清晰沟通。我们向开发人员和智能服务提供者提出了一组建议,以告知风险并协助可维护性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
Recent advances in artificial intelligence (AI) and machine learning (ML), such as computer vision, are now available as intelligent services and their accessibility and simplicity is compelling. Multiple vendors now offer this technology as cloud services and developers want to leverage these advances to provide value to end-users. However, there is no firm investigation into the maintenance and evolution risks arising from use of these intelligent services; in particular, their behavioural consistency and transparency of their functionality. We evaluated the responses of three different intelligent services (specifically computer vision) over 11 months using 3 different data sets, verifying responses against the respective documentation and assessing evolution risk. We found that there are: (1) inconsistencies in how these services behave; (2) evolution risk in the responses; and (3) a lack of clear communication that documents these risks and inconsistencies. We propose a set of recommendations to both developers and intelligent service providers to inform risk and assist maintainability.
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