关于可解释人工智能算法可理解性的用户研究所得数据集
Dataset resulting from the user study on comprehensibility of explainable AI algorithms
AI总结：
本文发布了一个基于149名候选者中三组不同背景参与者的用户研究数据集，包含39份访谈转录及解释可视化、主题分析和调查数据，用于多学科定性评估XAI算法的可理解性。
摘要：
本文介绍了一个数据集，该数据集是一项关于可解释人工智能（XAI）算法可理解性的用户研究的结果。研究参与者从149名候选人中招募，形成三个组，分别代表真菌学领域专家（DE）、具有数据科学和可视化背景的学生（IT）以及来自社会科学和人文学科的学生（SSH）。数据集的主要部分包含39份访谈转录文本，在访谈过程中，参与者被要求完成一系列任务并回答与解释机器学习模型决策相关的问题，该模型经过训练用于区分可食用和不可食用蘑菇。转录文本辅以额外数据，包括向用户展示的解释可视化、主题分析结果、参与者提供的解释改进建议，以及用于确定参与者领域知识和数据分析素养的初始调查结果。转录文本经过人工标注，以便在文本与特定片段相关的其他数据之间进行自动匹配。随着XAI技术领域的快速发展，对可解释性进行多学科定性评估的需求已成为该社区中新兴的主题之一。我们的数据集不仅能够重现我们所进行的研究，还为我们所收集材料的分析开辟了广泛的可能性。
英文摘要：
This paper introduces a dataset that is the result of a user study on the comprehensibility of explainable artificial intelligence (XAI) algorithms. The study participants were recruited from 149 candidates to form three groups representing experts in the domain of mycology (DE), students with a data science and visualization background (IT) and students from social sciences and humanities (SSH). The main part of the dataset contains 39 transcripts of interviews during which participants were asked to complete a series of tasks and questions related to the interpretation of explanations of decisions of a machine learning model trained to distinguish between edible and inedible mushrooms. The transcripts were complemented with additional data that includes visualizations of explanations presented to the user, results from thematic analysis, recommendations of improvements of explanations provided by the participants, and the initial survey results that allow to determine the domain knowledge of the participant and data analysis literacy. The transcripts were manually tagged to allow for automatic matching between the text and other data related to particular fragments. In the advent of the area of rapid development of XAI techniques, the need for a multidisciplinary qualitative evaluation of explainability is one of the emerging topics in the community. Our dataset allows not only to reproduce the study we conducted, but also to open a wide range of possibilities for the analysis of the material we gathered.
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。
