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Authors: Maísa Kely de Melo 1 ; 2 ; Silvia Reis 1 ; 3 ; Vinícius Di Oliveira 4 ; 5 ; 6 ; Allan Faria 1 ; 7 ; Ricardo de Lima 8 ; 6 ; Li Weigang 4 ; 6 ; Jose Salm Junior 1 ; 9 ; Joao Souza 1 ; 10 ; Vérica Freitas 11 ; Pedro Brom 4 ; 12 ; 6 ; Herbert Kimura 1 ; 3 ; Daniel Cajueiro 1 ; 13 ; Gladston Luiz da Silva 1 ; 7 and Victor Celestino 1 ; 3

Affiliations: 1 LAMFO - Lab. of ML in Finance and Organizations, University of Brasília, Campus Darcy Ribeiro, Brasília, Brazil ; 2 Department of Mathematics, Federal Institute of Education, Science and Technology of Minas Gerais, Formiga, Brazil ; 3 Department of Business Administration, University of Brasília, Campus Darcy Ribeiro, Brasília, Brazil ; 4 TransLab, Department of Computer Science, University of Brasília, Campus Darcy Ribeiro, Brasília, Brazil ; 5 Federal District Secretariat of Economy, Brasília, Brazil ; 6 Department of Computer Science, University of Brasília, Campus Darcy Ribeiro, Brasília, Brazil ; 7 Department of Statistics, University of Brasília, Campus Darcy Ribeiro, Brasília, Brazil ; 8 Ministry of Management and Innovation in Public Services, Federal District, Brazil ; 9 University of the State of Santa Catarina, Florianópolis, Santa Catarina, Brazil ; 10 Department of Economics and Business Administration, Brazilian Institute of Education Development and Research - IDP, Brasília, Brazil ; 11 School of Business and Management, Uberlandia Federal University, Uberlândia, Brazil ; 12 Department of Mathematics, Federal Institute of Education, Science and Technology of Brasília, Campus Estrutural, Brasília, Brazil ; 13 Department of Economics, University of Brasília, Campus Darcy Ribeiro, Brasília, Brazil

Keyword(s): Brazil, Design Sprint, Public Administration, AI, Machine Learning, LLM.

Abstract: The website portal of the Brazilian federal government (Gov.br) consists of pages from almost 40 ministries, 180 public agencies and up to 5000 public services for all citizens, posing a significant challenge in improving service quality. This article presents an innovative methodology to implement artificial intelligence (AI) to address these challenges, to enhance the efficiency, accessibility, and quality of services to the population. The methodology combines elements of Lean Office, Design Sprint, Analytic Hierarchy Process (AHP), and advanced AI techniques, particularly Large Language Models (LLMs), making it flexible and adaptable to the needs of government entities. Developed in collaboration with project managers, public servants, and stakeholders, the methodology includes a survey of demands, selection, and prototyping of AI projects in a complex government context. The practical application selected the Gov.br portal for prototyping, involving the development of an advance d generative agent to interact with citizens, clarify doubts, direct to the requested services, and provide human interaction when necessary. The recommended practices offer a valuable contribution to other developing countries seeking to integrate AI solutions into their public services. (More)

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Paper citation in several formats:
Kely de Melo, M.; Reis, S.; Di Oliveira, V.; Faria, A.; de Lima, R.; Weigang, L.; Salm Junior, J.; Souza, J.; Freitas, V.; Brom, P.; Kimura, H.; Cajueiro, D.; Luiz da Silva, G. and Celestino, V. (2024). Implementing AI for Enhanced Public Services Gov.br: A Methodology for the Brazilian Federal Government. In Proceedings of the 20th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-718-4; ISSN 2184-3252, SciTePress, pages 90-101. DOI: 10.5220/0012997000003825

@conference{webist24,
author={Maísa {Kely de Melo}. and Silvia Reis. and Vinícius {Di Oliveira}. and Allan Faria. and Ricardo {de Lima}. and Li Weigang. and Jose {Salm Junior}. and Joao Souza. and Vérica Freitas. and Pedro Brom. and Herbert Kimura. and Daniel Cajueiro. and Gladston {Luiz da Silva}. and Victor Celestino.},
title={Implementing AI for Enhanced Public Services Gov.br: A Methodology for the Brazilian Federal Government},
booktitle={Proceedings of the 20th International Conference on Web Information Systems and Technologies - WEBIST},
year={2024},
pages={90-101},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012997000003825},
isbn={978-989-758-718-4},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Web Information Systems and Technologies - WEBIST
TI - Implementing AI for Enhanced Public Services Gov.br: A Methodology for the Brazilian Federal Government
SN - 978-989-758-718-4
IS - 2184-3252
AU - Kely de Melo, M.
AU - Reis, S.
AU - Di Oliveira, V.
AU - Faria, A.
AU - de Lima, R.
AU - Weigang, L.
AU - Salm Junior, J.
AU - Souza, J.
AU - Freitas, V.
AU - Brom, P.
AU - Kimura, H.
AU - Cajueiro, D.
AU - Luiz da Silva, G.
AU - Celestino, V.
PY - 2024
SP - 90
EP - 101
DO - 10.5220/0012997000003825
PB - SciTePress