Repository: Outpacing Governance: Artificial Intelligence and the Institutional Speed Gap in Brazil's 2024 Electoral Campaigns
Description
This dataset supports the qualitative study "Outpacing Governance: Artificial Intelligence and the Institutional Speed Gap in Brazil's 2024 Electoral Campaigns," which examines how artificial intelligence was mobilized during the 2024 Brazilian municipal elections and how the Superior Electoral Court (Tribunal Superior Eleitoral, TSE) adjudicated its use. It comprises two primary sources plus supporting materials: 1. TSE judicial case data. A structured compilation of the 15 electoral judicial cases that form the study's analytical corpus, retrieved from the TSE's official public case-law portal (search conducted in October 2025). For each case, the file records the case identifier, type of legal action, nature of the AI technology involved, legal characterization (lawful/unlawful), decision outcome, and temporal indicators (dates of content publication, complaint, and decision). The screening log documenting corpus construction from the initial 47 records is also included. 2. Interview transcripts. Full transcripts of eight in-depth, semi-structured interviews with campaign strategists, electoral lawyers, public-policy advisers, and candidates involved in the 2024 cycle. All transcripts are anonymized: participant names and any identifying details beyond professional role and state have been removed, and participants are referred to only by code (E1–E8), in accordance with the informed-consent terms under which the interviews were conducted. Supporting files include the coding framework (codebook), the systematic literature-review search syntax, and the anonymized interview guide. The materials are provided to enable verification of the analyses reported in the article and to support reuse in comparative research on AI regulation in electoral contexts. Judicial records derive from publicly available sources; interview data are shared in anonymized form only, consistent with ethical commitments to participant confidentiality.
Files
Institutions
- Universidade Municipal de São Caetano do SulSão Paulo, São Caetano do Sul