为智能系统评估和获取高质量文档
Towards evaluating and eliciting high-quality documentation for intelligent systems
摘要：
建立在机器学习和人工智能基础上的智能系统的信任和透明度的一个重要组成部分是开发清晰、可理解的文档。然而，这样的系统因其复杂性和不透明性而臭名昭著，这使得高质量的文档成为一项重要的任务。此外，人们对是什么让此类文档“好”知之甚少。“在本文中，我们提出并评估了一套质量维度，以确定这种类型的文档在哪些方面存在不足。然后，使用这些尺寸，我们评估三种不同的方法，引起智能系统的文档。我们将展示这些维度如何识别这些文档中的缺点，并说明如何使用这些维度来进一步使用户能够提供适合给定角色或用例的文档。
英文摘要：
A vital component of trust and transparency in intelligent systems built on machine learning and artificial intelligence is the development of clear, understandable documentation. However, such systems are notorious for their complexity and opaqueness making quality documentation a non-trivial task. Furthermore, little is known about what makes such documentation "good." In this paper, we propose and evaluate a set of quality dimensions to identify in what ways this type of documentation falls short. Then, using those dimensions, we evaluate three different approaches for eliciting intelligent system documentation. We show how the dimensions identify shortcomings in such documentation and posit how such dimensions can be use to further enable users to provide documentation that is suitable to a given persona or use case.
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。
