Data underlying the paper "Towards Effective Human Intervention in Algorithmic Decision-Making"

This project captures perceptions of ability, benevolence, integrity and fairness towards different decision-maker configurations in algorithmic decision-making for policy enforcement. It consists of two studies. In the first study, we interview 21 participants with experience renting out their properties out as short-term rentals. Through these interviews we identify the main characteristics that interviewees considered when evaluating the appropriateness of decision-maker configurations (i.e., decision-maker profile, model type, data provenance). In the second study, we run a crowdsourced user study in Prolific with 223 participants. They were shown an illegal holiday identification scenario. Each participant was assigned to a scenario with a decision-maker configuration with varying decision-maker profile, different model types, and data provenance. The dataset includes:<br>The prompts used for running the interviewsThe interview protocolPre-registration of the crowdsourced studyThe materials used for designing the crowdsourced user studyThe (anonymized) data from the crowdsourced studyThe script used to analyze the crowdsourced dataA document with all the rationales behind the statistical analysis of the crowdsourced dataAnalysis of open-ended questions of the crowdsourced study

本项目聚焦政策执行场景下的算法决策，采集了不同决策主体配置对应的能力、善意、诚信与公平感知数据。本项目包含两项研究。第一项研究中，我们访谈了21名曾将房产作为短期民宿对外出租的参与者，通过访谈梳理出受访者在评估决策主体配置合理性时重点考量的核心特征，即决策主体画像、模型类型与数据来源。第二项研究中，我们在众包平台Prolific上开展了一项包含223名参与者的线上用户研究，向参与者展示了非法假日住宿识别场景，并为每位参与者分配了带有差异化配置的决策主体场景，涵盖不同的决策主体画像、多样的模型类型以及不同的数据来源。本数据集包含以下内容：
访谈所用提示语
访谈流程方案
众包研究的预注册文件
众包用户研究的设计材料
众包研究的（匿名化）数据
众包数据分析脚本
众包数据统计分析依据的全部理论依据文档
众包研究开放式问题的分析结果