REGULATION OF ARTIFICIAL INTELLIGENCE: BETWEEN THE SWITCH AND INNOVATION – IS BRAZIL PREPARED? Supplementary Material: Detailed Document Selection and Coding Protocol
Description
This dataset -Supplementary Material A: Detailed Document Selection and Coding Protocol from the study “Regulation of Artificial Intelligence: Between the Switch and Innovation – Is Brazil Prepared?” — provides a systematically organized corpus of 52 official and analytical documents on AI governance across eight jurisdictions: Brazil (focal case), European Union, United States, United Kingdom, India, Chile, Mexico, and China. The dataset was constructed through a transparent five-phase retrieval process involving government portals, legal databases, regulatory repositories, and cross-referenced citation tracking. Inclusion criteria ensured institutional relevance, public accessibility, temporal validity (2018–2025), and thematic focus on AI governance. Documents were selected from governmental, regulatory, academic, civil society, and media sources to ensure multi-perspective representation. Weighting schemes (e.g., 60% government vs. 40% independent sources) adjusted for jurisdictional disparities in data availability. Each document was coded in MAXQDA using a hierarchical framework grounded in Lawrence Lessig’s four regulatory modalities — law, architecture, market, and social norms — complemented by institutional theory, economic regulation, and OECD’s Regulatory Impact Assessment (RIA) methodology. Subcodes captured compliance mechanisms, risk classification, incentives, fairness, and governance coordination. Inter-coder reliability was established through double-coding and reconciliation logs, with triangulation across institutional types. The dataset’s central table (Table SP1, pp. 4–11) classifies all documents by country, source institution, document title, and type (legal, regulatory, strategic, analytical, or media). For Brazil, ten documents cover Bill 2338/2023, ANPD technical notes, civil-society assessments (e.g., Data Privacy Brasil, CGI.br), and media commentary. The EU section lists six foundational sources including the AI Act, GDPR, and Ethics Guidelines for Trustworthy AI. The U.S. subset includes the AI Bill of Rights, NIST’s AI Risk Management Framework, and executive policy orders. The UK materials span the National AI Strategy and AI Regulation White Paper (2023). Comparable sets exist for India (NITI Aayog frameworks), Chile (MinCiencia 2024 policy updates), Mexico (Agenda IA 2030 and INAI guidelines), and China (CAC regulations and MIIT standards). Analytically, the dataset supports comparative cross-country evaluation of regulatory architectures, innovation incentives, and societal norms shaping AI governance. Brazil’s expanded corpus enabled a detailed OECD-style RIA of Bill 2338/2023, assessing problem definition, policy alternatives, stakeholder impacts, feasibility, and cost–benefit distribution. Validation procedures included expert reviews and cross-benchmarking with OECD and ECLAC reports.