Machine Learning Model Cards Transparency Review : Using model card toolkit

A. Wadhwani, Priyank Jain
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引用次数: 11

Abstract

In our day to day life, we rely on information that is provided by product makers to make rightful choices such as the nutritional content of food, warnings in medications, strength parameters of a constructed road, etc but when it comes to AI there’s has not been any such provided information. The machine learning models are very often distributed without a proper clear understanding of how it functions, i.e. under what conditions would it perform the best and most consistently, whether or not it has blind spots, and, if so, then where are they.Model cards are a very recent and hot topic of research. In Machine Learning (ML), transparency with model cards is relevant as it affects a wide range of domains, from health care to finance and jobs, etc. This research paper presents the importance of model cards and transparency issues.
机器学习模型卡透明度审查:使用模型卡工具包
在我们的日常生活中,我们依靠产品制造商提供的信息来做出正确的选择,比如食物的营养成分、药物的警告、筑路的强度参数等,但当涉及到人工智能时,还没有任何这样的信息。机器学习模型通常在没有正确理解其功能的情况下分发,即在什么条件下它会表现得最好和最一致,它是否有盲点,如果有,那么盲点在哪里。模型卡是一个最近的热门研究课题。在机器学习(ML)中,模型卡的透明度是相关的,因为它影响到广泛的领域,从医疗保健到金融和就业等。本研究报告提出了模型卡和透明度问题的重要性。
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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