Banca de DEFESA: RENATA DE CASTRO VIANNA PRADO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : RENATA DE CASTRO VIANNA PRADO
DATE: 26/05/2025
TIME: 17:00
LOCAL: https://teams.microsoft.com/l/meetup-join/19%3a0a9998084fcc459f92b72fb6608767f7%40thread.tacv2/17480
TITLE:

Artificial Intelligence in Brazilian Public Administration: Applications, Challenges and a Multivariate Comparative Analysis with Digital Governance Models in the European Community

KEY WORDS:

Artificial Intelligence, Public Sector, Hierarchical Clustering, Comparative Analysis, Governance

PAGES: 53
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUMMARY:

Artificial Intelligence (AI) can potentially transform public administration by optimizing decisionmaking, improving service delivery, and increasing institutional efficiency. This study compares AI adoption in Brazil’s public sector with selected European Union (EU) countries, analyzing its impact on key governance functions. The objective is to identify implementation trends, evaluate AI’s role in optimizing internal processes and resource allocation, and explore institutional engagement in AI-driven initiatives. The research is based on a dataset of 52 documented AI applications in Brazil, contrasted with similar cases in the EU. Hierarchical clustering techniques and the Elbow Method are employed to structure governance strategies and identify common patterns. The findings indicate that AI has been widely used to streamline administrative processes, strengthen transparency mechanisms, and enhance fraud detection. Advanced methodologies, such as Neural Networks and Decision TreeBased Models, stand out for their predictive power and versatility in public administration. Comparative analysis reveals that Brazil shares a governance strategy that is similar to that of countries like the Netherlands and Switzerland. However, significant challenges remain, including the uneven distribution of AI initiatives across institutions, a lack of transparency in methodological reporting, and limited engagement in specific application areas. To address these challenges, we propose a framework for standardizing AI documentation and expanding institutional participation, which could enhance transparency and decision-making efficiency in public administration. Future research should focus on developing more comprehensive frameworks for AI implementation in public administration, incorporating economic and institutional variables to refine comparative analyses. Additionally, a deeper understanding of AI’s role in policymaking, ethics, and regulation is essential to ensuring its full potential for innovation, efficiency, and transparency in the modernization of the public sector.

COMMITTEE MEMBERS:
Externa à Instituição - ANA PAULA BERNARDI DA SILVA - UCB
Presidente - 1780217 - EDNA DIAS CANEDO
Interno - 2311780 - FABIO LUCIO LOPES DE MENDONCA
Interno - 2556078 - GEORGES DANIEL AMVAME NZE