Insurgent gazes:

facial recognition and technopolitics of resistance at Criptofunk 2024

Authors

DOI:

https://doi.org/10.35699/2318-2326.2026.59716

Keywords:

Facial Recognition, Public security, Community engagement

Abstract

This article reports on a community activation experience aimed at mobilizing civil society and fostering critical discussion about the risks of using Facial Recognition (FR) in public security. FR, an Artificial Intelligence-based technology, has been expanding in Brazil under the promise of efficiency and neutrality. However, it exhibits significant flaws that lead to unjust arrests and reinforce structural prejudices. Far from being merely a technical tool, FR operates as an agent within an opaque technopolitical process of surveillance that disproportionately affects black and peripheral populations. The community activation detailed in this article took place at the Criptofunk 2024 event, held in the Maré favela complex in Rio de Janeiro. It comprised four integrated activities: experimentation with Emotion Recognition algorithms; a workshop featuring a presentation and debate on FR; resistance makeup; and a live graffiti performance with the FR theme. The high level of public engagement indicates the proposal's success in connecting the university with the community, promoting horizontal exchanges, social critique and mutual learning about the impacts of these technologies.

Author Biographies

  • André Pecini, Pontifícia Universidade Católica do Paraná (PUCPR) | Curitiba | PR | BR

    Pós-doutorando, PPGTU/PUCPR - Curitiba, Brasil

  • Debora Pio, Universidade Federal do Rio de Janeiro (UFRJ) | Rio de Janeiro | RJ | BR

    Doutoranda, ECO/UFRJ - Rio de Janeiro, Brasil

  • Rubia Marafigo Sehnem, Universidade Federal do Paraná (UFPR) | Curitiba | PR | BR

    Graduanda, Geografia UFPR - Curitiba, Brasil

  • Pietra Milani Bizerril, Universidade Federal do Paraná (UFPR) | Curitiba | PR | BR

    Mestranda, PPGGEO UFPR - Curitiba, Brasil

  • Yasmin Marques dos Santos, Pontifícia Universidade Católica do Paraná (PUCPR) | Curitiba | PR | BR

    Mestranda, PPGTU/PUCPR - Curitiba, Brasil

  • Rodrigo José Firmino, Pontifícia Universidade Católica do Paraná (PUCPR) | Curitiba | PR | BR

    Professor titular, PPGTU/PUCPR - Curitiba, Brasil

  • Carolina Batista Israel, Universidade Federal do Paraná (UFPR) | Curitiba | PR | BR

    Professora, PPGGEO/UFPR - Curitiba, Brasil

  • Gilberto Vieira, Pontifícia Universidade Católica do Paraná (PUCPR) | Curitiba | PR | BR

    Doutorando, PPGTU/PUCPR - Curitiba, Brasil

References

Andron, S. (2023). Urban surfaces, graffiti, and the right to the city. Routledge.

Buolamwini, J. A. (2017). Gender shades: Intersectional phenotypic and demographic evaluation of face datasets and gender classifiers [Thesis, Massachusetts Institute of Technology]. https://dspace.mit.edu/handle/1721.1/114068

Castiglioni, M. H. (2020). [BR][Front-End] JavaScript - Reconhecimento Facial com FaceAPI. https://youtu.be/aGecIY04ymQ?si=GzkYFxh5EvS7Kys0.

Criptofunk. ([s.d.]). Criptofunk—Sobre. Criptofunk. https://criptofunk.com/

Feldman Barrett, L. (2021). AI weighs in on debate about universal facial expressions. Nature, v. 589, n. 7841, p. 202–203. https://www.nature.com/articles/d41586-020-03509-5.

Google. ([s.d.]). Guia de detecção de pontos de referência do rosto | Google AI Edge. Google AI for Developers. Recuperado 6 de junho de 2025, de https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker?hl=pt-br

Hao, K. (2019, 20 de dezembro). A US government study confirms most face recognition systems are racist. MIT Technology Review. https://www.technologyreview.com/2019/12/20/79/ai-face-recognition-racist-us-government-nist-study/

Hora, N. da. (2023). MyNews explica! Algoritmos. Edições 70.

Israel, C., Firmino, R., Kramer, H., Maia, C., & Abad, J. (2023). Reconhecimento Facial nas escolas públicas do Paraná. https://jararacalab.org/cms/wp-content/uploads/2023/10/Relatorio_RF_2023.pdf

Marques, I. C. (2023). Um breve relato sobre Inteligências Artificiais e os Estudos CTS. CTS em foco, v. 03, n. 02. https://esocite.org.br/images/BOLETIM-CTS/PDF/CTS-v3-n2.pdf

Nunes, P., de Castro, C. S. C. L., Lima, T., do Carmo, G. S. T., Pereira, M. F. R., Valadares, L., Barbosa, F., Del Grossi, V. C. D., do Amaral, A. J., & Picollo, C. (2025). Mapeando a vigilância biométrica: Levantamento nacional sobre o uso do reconhecimento facial na segurança pública. CESeC. https://drive.google.com/file/d/1bN2ssBp_dMiih8YOUonLhGl_5jRoNe5s/view

Nunes, P. (2025). Mapeando a Vigilância Biométrica. https://drive.google.com/file/d/1bN2ssBp_dMiih8YOUonLhGl_5jRoNe5s/

O’Neil, C. (2021). Algoritmos de destruição em massa. Editora Rua do Sabão.

Panóptico. (2025). Monitor de novas tecnologias na segurança pública no Brasil. https://www.opanoptico.com.br/#regioes

Pastor, J. (2018, julho 6). Pintarte la cara de payaso es la forma perfecta de evitar el reconocimiento facial automático. Xataka. https://www.xataka.com/robotica-e-ia/pintarte-cara-payaso-forma-perfecta-evitar-reconocimiento-facial-automatico

Peschanski, J. A., Jurno, A. C., & Hilsenbeck Filho, A. M. (2025). Emergência da extensão universitária digital: boas práticas e direcionamentos. Texto Livre, 18, e56372.

Prosser, E. S. (2010). Grafite Curitiba. Kairós.

Rebello, A. (2023, agosto 14). Smart Sampa: Denunciada por corrupção irá capturar seu rosto em SP. Intercept Brasil. https://www.intercept.com.br/2023/08/14/smart-sampa-denunciada-por-corrupcao-capturar-seu-rosto-em-sp/

Rhue, L. (2018) Racial Influence on Automated Perceptions of Emotions. Rochester, NY. https://papers.ssrn.com/abstract=3281765

Roy, A. (2005). Urban informality: Toward an epistemology of planning. Journal of the american planning association, 71(2), 147-158.

Silva, T. (2022). Racismo algorítmico: inteligência artificial e discriminação nas redes digitais. Edições Sesc SP.

Schiffler, V. R. (2021) Criando Detecção Facial com JavaScript e Face-api.js. https://youtu.be/tF36BEoQcyo?si=M38tM6WLZeufSsWa. Acesso em: 30 mai. 2025.

Taigman, Y., Yang, M., Ranzato, M., & Wolf, L. (2014). Deepface: Closing the gap to human-level performance in face verification. Proceedings of the IEEE conference on computer vision and pattern recognition, 1701–1708. http://openaccess.thecvf.com/content_cvpr_2014/html/Taigman_DeepFace_Closing_the_2014_CVPR_paper.html

Published

2026-02-11

Issue

Section

Artigos

How to Cite

Insurgent gazes:: facial recognition and technopolitics of resistance at Criptofunk 2024. Interfaces - Revista de Extensão da UFMG, [S. l.], v. 14, n. 1, p. 1–26, 2026. DOI: 10.35699/2318-2326.2026.59716. Disponível em: https://periodicos.ufmg.br/index.php/revistainterfaces/article/view/59716. Acesso em: 17 feb. 2026.