A Means to what End? Evaluating the Explainability of Software Systems using Goal-Oriented Heuristics

Hannah Deters, Jakob Droste, K. Schneider
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引用次数: 1

Abstract

Explainability is an emerging quality aspect of software systems. Explanations offer a solution approach for achieving a variety of quality goals, such as transparency and user satisfaction. Therefore, explainability should be considered a means to an end. The evaluation of quality aspects is essential for successful software development. Evaluating explainability allows an assessment of the quality of explanations and enables the comparison of different explanation variants. As the evaluation depends on what quality goals the explanations are supposed to achieve, evaluating explainability is non-trivial. To address this problem, we combine the already well-established method of expert evaluation with goal-oriented heuristics. Goal-oriented heuristics are heuristics that are grouped with respect to the goals that the explanations are meant to achieve. By establishing appropriate goal-oriented heuristics, software engineers are enabled to evaluate explanations and identify problems with affordable resources. To show that this way of evaluating explainability is suitable, we conducted an interactive user study, using a high-fidelity software prototype. The results suggest that the alignment of heuristics with specific goals can enable an effective assessment of explainability.
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A达到什么目的的手段?用面向目标的启发式方法评估软件系统的可解释性
可解释性是软件系统质量的一个新兴方面。说明提供了实现各种质量目标的解决方案方法,例如透明度和用户满意度。因此,可解释性应被视为达到目的的一种手段。质量方面的评估对于成功的软件开发是必不可少的。评估可解释性允许对解释的质量进行评估,并使不同的解释变体能够进行比较。由于评估取决于解释应该达到的质量目标,因此评估可解释性是非常重要的。为了解决这个问题,我们将已经建立的专家评估方法与面向目标的启发式方法相结合。目标导向的启发式是根据解释要达到的目标进行分组的启发式。通过建立适当的面向目标的启发式方法,软件工程师能够用可负担的资源评估解释并识别问题。为了证明这种评估可解释性的方法是合适的,我们使用高保真软件原型进行了交互式用户研究。结果表明,启发式与特定目标的对齐可以有效地评估可解释性。
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