cff-version: 1.2.0
abstract: "<p>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:</p><p><br></p><ol><li>The prompts used for running the interviews</li><li>The interview protocol</li><li>Pre-registration of the crowdsourced study</li><li>The materials used for designing the crowdsourced user study</li><li>The (anonymized) data from the crowdsourced study</li><li>The script used to analyze the crowdsourced data</li><li>A document with all the rationales behind the statistical analysis of the crowdsourced data</li><li>Analysis of open-ended questions of the crowdsourced study</li></ol>"
authors:
  - family-names: Yurrita Semperena
    given-names: Mireia 
    orcid: "https://orcid.org/0000-0002-9685-4873"
  - family-names: Verma
    given-names: Himanshu
    orcid: "https://orcid.org/0000-0002-2494-1556"
  - family-names: Balayn
    given-names: Agathe
  - family-names: Gadiraju
    given-names: Ujwal
    orcid: "https://orcid.org/0000-0002-6189-6539"
  - family-names: Pont
    given-names: Sylvia
  - family-names: Bozzon
    given-names: Alessandro
title: "Data underlying the paper &#34;Towards Effective Human Intervention in Algorithmic Decision-Making&#34;"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/8c19bb03-14de-4c85-b781-33eed0cac44a.v1
license: CC BY 4.0
date-released: 2025-01-24