论文标题
可解释的人工智能中的定性调查：社会科学的更多见解
Qualitative Investigation in Explainable Artificial Intelligence: A Bit More Insight from Social Science
论文作者
论文摘要
我们对可解释的人工智能（XAI）中的用户研究进行了重点分析，需要定性研究。我们利用社会科学公司提出改善XAI研究人员使用观察，访谈，焦点小组和/或问卷来捕获定性数据的研究的方法。根据定性研究文献中描述的严格组成部分，我们将分析中包含的XAI论文的介绍进行情境化：1）基础理论或框架，2）方法论方法，3）数据收集方法和4）数据分析过程。我们的分析结果支持XAI社区中其他人的电话，主张与从社会学科到严格和用户研究中有效性的专家合作。
We present a focused analysis of user studies in explainable artificial intelligence (XAI) entailing qualitative investigation. We draw on social science corpora to suggest ways for improving the rigor of studies where XAI researchers use observations, interviews, focus groups, and/or questionnaires to capture qualitative data. We contextualize the presentation of the XAI papers included in our analysis according to the components of rigor described in the qualitative research literature: 1) underlying theories or frameworks, 2) methodological approaches, 3) data collection methods, and 4) data analysis processes. The results of our analysis support calls from others in the XAI community advocating for collaboration with experts from social disciplines to bolster rigor and effectiveness in user studies.
