IV Seminar on the Grand Challenges of Computing in Brazil: Presented Papers

Authors

André Luis de Medeiros Santos (ed)
UFPE
Flávio Rech Wagner (ed)
UFRGS

Keywords:

Ethics in Artificial Intelligence, Large-Scale Language Models, Machine Learning, Unsecure Contexts, Intelligent Conversational Agents, Digital Inclusion, Supercomputing, SQL, Natural Language Processing, Low-Energy Software, Sustainable Computing, Cybersecurity, Brazilian Quantum Internet, Ubiquitous Access, Digital Inequality, Resilience to Natural Disasters, Protection of Children and Adolescents in Social Media Environments, Combating Disinformation, Digital Literacy, Digital Citizenship, Quantum Computing

Synopsis

The Brazilian Computing Society (SBC) organized its first event aimed at defining its Grand Challenges in 2006, in São Paulo. It was a pioneering initiative in the field of Computing in the country, with the purpose of planning and guiding research in Computing over a ten-year period (from 2006 to 2016). During this event, five Grand Challenges were defined, which proved to be both precise and comprehensive in their vision for the future of Computing. These challenges served as the foundation for subsequent events held in 2008, 2009, 2013, and 2014.

In November 2024, SBC held a new edition of the Grand Challenges in Computing Seminar, bringing together more than 80 researchers and industry representatives with the aim of strengthening research within the Computing scientific community around the challenges for the coming decade. New Grand Challenges were proposed in light of the many scientific advancements since the 2006 seminar, with a special focus on the socioeconomic impacts of Computing, considering the accelerated digital transformation currently underway and the widespread use of computational solutions in virtually all aspects of our lives.

This eBook contains the papers presented at the seminar, submitted by researchers from our academic community, who helped define the new Grand Challenges in the areas of Artificial Intelligence and Data Science; Sustainable Computing; Cybersecurity; Internet Ubiquity; Quantum Computing; and Computing and Society. We hope these works will inspire the development of projects that advance the state of the art in these areas and generate social and technological impact in Brazil.

Chapters

  • 1. Ethics in Artificial Intelligence: how to support developers
    Geber L. Ramalho
  • 2. A Big Challenge: Tools to Guarantee Robust and Controlled Behavior of Large Language Models
    Fabio G. Cozman, Sarajane M. Peres, Marcelo Finger, Renata Wassermann, Anna H. Reali Costa, Edson S. Gomi, Artur J. L. Correia, Anarosa A. F. Brandão, Karina V. Delgado, Denis D. Mauá, Thiago A. S. Pardo, Fátima L. S. N. Marques
  • 3. Adversarial Machine Learning: Aprendizado de Máquina em Contextos Inseguros
    Oscar Zibordi de Paiva, Marcos Antonio Simplício Jr, Charles Christian Miers
  • 4. Intelligent Conversational Agents for Digital Inclusion
    Vasco Furtado, Elizabeth S. Furtado
  • 5. Supercomputing in the Age of Artificial Intelligence
    Alba C. M. A. Melo, Philippe O. A. Navaux, Lucia M. A. Drummond, Cristina Boeres, Vinod Rebello, Alfredo Goldman, Márcio Castro
  • 6. This Future Without SQL
    Eduardo C. de Almeida, Eduardo H. M. Pena, Altigran S. da Silva
  • 7. "More with Less" – Intelligent and Sustainable Natural Language Processing Based on Data Engineering and Advanced Artificial Intelligence
    Marcos André Gonçalves, Leonardo Rocha, Washington Cunha, Guilherme Dal Bianco
  • 8. Low-Energy Software Development and Automation – Refining the Topic of Sustainable Computing
    Luigi Carro
  • 9. Sustainable and Energy-Efficient Computing
    Daniel Cordeiro, Emilio Francesquini, Alessandro Santiago dos Santos, Alvaro Luiz Fazenda, Silvana Rossetto
  • 10. Cybersecurity Challenges in the BCS/SBC Frameworks
    Aldri Santos, Altair Santin, André Grégio, Carlos Raniery, Daniel Batista, Dianne Medeiros, Diego Kreutz, Diogo Mattos, Edelberto Franco, Igor Moraes, Lourenço Pereira Jr., Marcos Simplicio, Michele Nogueira, Michelle Wangham, Natalia Fernandes, Rodrigo Miani
  • 11. Computational Challenges for a Brazilian Quantum Internet
    Antônio Abelém, Alberto Schaeffer-Filho, Gabriel Nazar, Jéferson Nobre, Juliano Wickboldt, Lisandro Granville, Luciano Gaspary, Weverton Cordeiro
  • 12. Internet for All: Challenges of Ubiquitous Access
    Anelise Munaretto, Carlos Kamienski, Eduardo Cerqueira, Leobino Sampaio, Miguel Elias M. Campista, Rossana M. C. Andrade
  • 13. Disconnected and Invisible World: Challenges and Opportunities to Mitigate Digital Inequality
    Alberto Schaeffer-Filho, Antônio Abelém, Gabriel Nazar, Jéferson Nobre, Juliano Wickboldt, Lisandro Granville, Luciano Gaspary, Weverton Cordeiro
  • 14. Computational Challenges for Natural Disaster Resilience
    Alberto Schaeffer-Filho, Gabriel Nazar, Jéferson Nobre, Juliano Wickboldt, Lisandro Granville, Luciano Gaspary, Weverton Cordeiro
  • 15. Kids Online: how to contribute to the protection of children and adolescents in social media environments?
    Humberto T. Marques-Neto, Jussara M. Almeida, Fabrício Benevenuto
  • 16. Combating Disinformation on Digital Platforms: Challenges and Opportunities
    Julio C. S. Reis, Philipe Melo, Márcio Silva, Fabrício Benevenuto
  • 17. The Urgent Need for Digital Literacy
    Glaucio de Sousa Santos, Claudia Lage Rebello da Motta
  • 18. Universalization of Digital Citizenship
    Flavia Bernardini, Raissa Barcellos, Claudia Cappelli, José Viterbo, Cristiano Maciel

Downloads

Download data is not yet available.

References

“AI Model Risk Management Framework”. Cloud Security Alliance. (Julho/2024).

A4AI (2018). A4AI Affordability Report 2018 [Online]. Available: [link].

Abadi, D., Ailamaki, A., Andersen, D. G., Bailis, P., Balazinska, M., Bernstein, P. A., Boncz, P. A., Chaudhuri, S., Cheung, A., Doan, A., Dong, L., Franklin, M. J., Freire, J., Halevy, A. Y., Hellerstein, J. M., Idreos, S., Kossmann, D., Kraska, T., Krishnamurthy, S., Markl, V., Melnik, S., Milo, T., Mohan, C., Neumann, T., Ooi, B. C., Ozcan, F., Patel, J. M., Pavlo, A., Popa, R. A., Ramakrishnan, R., Ré, C., Stonebraker, M., and Suciu, D. (2022). The seattle report on database research. Commun. ACM, 65(8):72–79.

ABELEM, A.; TOWSLEY, D.; VARDOYAN, G. Quantum internet: The future of internetworking. In: . Shortcourses’ Book of the XXXVIII Brazilian Symposium on Computer Networks and Distributed Systems (SBRC 2020). Porto Alegre, RS, Brasil: Brazilian Computing Society SBC), 2020. cap. 2.

Afonso, A., Martins, P., and da Silva, A. (2024). Sereia: document store exploration through keywords. Knowledge and Information Systems.

AHMED, N. Quantum computing algorithms for integer factorization: A comparative analysis. Modern Dynamics: Mathematical Progressions, v. 1, n. 1, p. 6–9, 2024.

Akter, M., Godfrey, A., Kropczynski, J., Lipford, H. and Wisniewski, P. (2022). From Parental Control to Joint Family Oversight: Can Parents and Teens Manage Mobile Online Safety and Privacy as Equals? Proc. ACM Hum.-Comput. Interact. 6, CSCW1, Article 57, 28 pages.

Alam, Ashraf. Developing a Curriculum for Ethical and Responsible AI: A University Course on Safety, Fairness, Privacy, and Ethics to Prepare Next Generation of AI Professionals. Intelligent Communication Technologies and Virtual Mobile Networks. Singapore: Springer Nature Singapore, 2023. 879-894

Aldboush et al. Building Trust in Fintech: An Analysis of Ethical and Privacy Considerations in the Intersection of Big Data, AI, and Customer Trust. International Journal of Financial Studies 11.3 (2023): 90.

Almeida, V., Almeida, J. M., and Meira, W. (2024). The role of computer science in responsible ai governance. IEEE Internet Computing, 28(3):55–58.

Andrade, G. (2023). Crescimento da internet desacelera e mais de 2,7 bilhões estão sem acesso. [link].

Anuyah, O., Badillo-Urquiola, K., and Metoyer, R. (2023). Characterizing the technology needs of vulnerable populations for participation in research and design by adopting maslow’s hierarchy of needs. In 2023 CHI Conference on Human Factors in Computing Systems, pages 1–20.

Assis, J. V. and Valença, G. (2024). Is My Child Safe Online? - On Requirements for Parental Control Tools in Apps used by Children. Journal on Interactive Systems, 15(1), 823–838.

B. Dudley et al. Bp statistical review of world energy 2016. British Petroleum Statistical Review of World Energy, Bplc. editor, Pureprint Group Limited, UK, 2019.

Baldassarre et al. Fostering Human Rights in Responsible AI: A Systematic Review for Best Practices in Industry. IEEE Transactions on Artificial Intelligence (2024).

Barcellos, R., Bernardini, F. and Viterbo, J. (2022). “Towards defining data interpretability in open data portals: Challenges and research opportunities”. Information Systems, 106, 101961. DOI: 10.1016/j.is.2021.101961

BBC (2024). A cronologia da tragédia no rio grande do sul. BBC News Brasil: [link]. Acessado em setembro de 2024.

BBC News (2024). Como pagers do Hezbollah explodiram, em ataque atribuído ao Mossad. [link].

Bell, G. (2015). Supercomputers: The amazing race. Microsoft Technical Report MSR-TR-2015-2, Microsoft Research.

Belli, L., and Doneda, D. Data protection in the BRICS countries: legal interoperability through innovative practices and convergence. International Data Privacy Law 13.1 (2023): 1-24.

Benevenuto, F. and Melo, P. (2024). Misinformation campaigns through whatsapp and telegram in presidential elections in brazil. Communications of the ACM, 67(8):72–77.

Bengio, Y. (2023). AI and catastrophic risk. Journal of democracy, 34(4), 111-121. Chancellor, S. (2023).

BENNETT, C. H.; BRASSARD, G. Quantum cryptography: Public key distribution and coin tossing. Theoretical computer science, Elsevier, v. 560, p. 7–11, 2014.

Bentley, S. V., Naughtin, C. K., McGrath, M. J., Irons, J. L., and Cooper, P. S. (2024). The digital divide in action: how experiences of digital technology shape future relationships with artificial intelligence. AI and Ethics, pages 1–15.

Bergozzi, V.; Carro, L. Low energy decision trees. Relatório interno.

Bommasani, R. et al. (2021). On the opportunities and risks of foundation models. ArXiv.

Božić, V. (2023). Artifical intelligence as the reason and the solution of digital divide. Language Education and Technology, 3(2).

Bozzola, E., Spina, G., Agostiniani, R., Barni, S., Russo, R., Scarpato, E., Di Mauro, A., Di Stefano, A. V., Caruso, C., Corsello, G. and Staiano, A. (2022). The Use of Social Media in Children and Adolescents: Scoping Review on the Potential Risks. Intíl Journal of Environmental Research and Public Health, 19(16), 9960.

Bubeck, S. et al. (2023). Sparks of artificial general intelligence: Early experiments with GPT-4.

Buchanan, B. (2024). The social engineering of XZ. [link].

Butler, R.; Pennotti, M. The evolution of software and its impact on complex system design in robotic spacecraft embedded systems. Dec 2013, Procedia Computer Science.

Caldeira, C., Nurain, N., and Connelly, K. (2022). “i hope i never need one”: Unpacking stigma in aging in place technology. In 2022 CHI Conference on Human Factors in Computing Systems, pages 1–12.

Calero. C.; Polo, M.; Moraga, A. Investigating the impact on execution tiem and energy consumption of developing with Spring. Sustainable Computing: Informatics and Systems. 2021, Elsevier.

Cao, Y., Zhao, Y., Wang, Q., Zhang, J., Ng, S. e Hanzo, L. (2022). The evolution of quantum key distribution networks: On the road to the Qinternet. IEEE Communications Surveys & Tutorials, 24(2):839–894.

Cappelli, C. (2009). “Uma Abordagem para Transparência em Processos Organizacionais Utilizando Aspectos”. Tese de Doutorado – Departamento de Informática, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brasil.

Carpenter, B. E. (1996). Architectural Principles of the Internet. RFC 1958. Acessado em [link].

Carro, L. and Nazar, G. L. (2023). Desafios para a computação energeticamente eficiente. Sociedade Brasileira de Computação.

Carro, L. and Nazar, G. L. (2023). Desafios para a computação energeticamente eficiente. Sociedade Brasileira de Computação.

Cazzaniga et. al., “Gen-AI: Artificial Intelligence and the Future of Work.” IMF Staff Discussion Note SDN2024/001, International Monetary Fund, Washington, DC.

Cetic.br (2023). Pesquisa sobre o Uso das Tecnologias de Informação e Comunicação nos Domicílios Brasileiros. TIC Domicílios. Acessado em [link].

Chade, J. (2023). Em plena era digital, 675 milhões de pessoas ainda vivem sem eletricidade. [link].

Chamberlin, D. (2024). 50 years of sql | don chamberlin computer scientist and co-inventor of sql. Accessed: 2024-08-31.

Chancellor, Stevie. Toward practices for human-centered machine learning. Communications of the ACM 66.3 (2023): 78-85.

Chien, K. The Future of Data Center Cooling: Innovations for Sustainability. [link] Último acesso em 08/09/2024.

CHEN, Y.-A. et al. An integrated space-to-ground quantum communication network over 4,600 kilometres. Nature, Nature Publishing Group UK London, v. 589, n. 7841, p. 214–219, 2021.

Chesterman, Simon. Good models borrow, great models steal: intellectual property rights and generative AI. Policy and Society (2024): puae006.

CNBC - Consumer News and Business Channel. Google’s carbon emissions surge nearly 50% due to AI energy demand (2024). Available in [link]

Cordeiro, D., Francesquini, E., Amarís, M., Castro, M., Baldassin, A., and Lima, J. (2023). Green cloud computing: Challenges and opportunities. In Anais Estendidos do XIX Simpósio Brasileiro de Sistemas de Informação, pages 129–131, Porto Alegre, RS, Brasil. SBC.

CORREIO DO POVO (2024). Sistema de monitoramento dá suporte nas enchentes de porto alegre. [link].

Couto, J. M., Reis, J. C., and Benevenuto, F. (2024). Can computer network attributes be useful for identifying low-credibility websites? a case study in brazil. Social Network Analysis and Mining (SNAM), 14(1):153.

Crawford K. Atlas of AI: power, politics, and the planetary costs of artificial intelligence, 1st edn. (2021). Yale University Press

Cremers, C., Dax, A. e Naska, A. (2023). Formal analysis of SPDM: Security protocol and data model version 1.2. Em USENIX Security Symposium, p. 6611–6628.

Crowcroft, J., Wolisz, A., and Sathiaseelan, A. (2015). Towards an Affordable Internet Access for Everyone: The Quest for Enabling Universal Service Commitment (Dagstuhl Seminar 14471). Dagstuhl Reports, 4(11):78–137.

D. Patterson et al. The carbon footprint of machine learning training will plateau, then shrink. Computer, 55(7):18–28, 2022.

da Silva, T. H. O., Furtado, V., Furtado, E., Mendes, M., Almeida, V., and and, L. S. (2022). How do illiterate people interact with an intelligent voice assistant? International Journal of Human–Computer Interaction, 40(3):584–602.

de Farias, V. A. E., Brito, F. T., Flynn, C. J., Machado, J. C., Majumdar, S., and Srivastava, D. (2020). Local dampening: Differential privacy for non-numeric queries via local sensitivity. Proc. VLDB Endow., 14(4):521–533.

Dobson, S., Hutchison, D., Mauthe, A., Schaeffer-Filho, A., Smith, P., and Sterbenz, J. P. G. (2019). Self-organization and resilience for networked systems: Design principles and open research issues. Proceedings of the IEEE, 107(4):819–834.

Drew, Christopher. (2018). Four Questions to Ask When Using YouTube in the Classroom. eLearn 2018, 2, Article 3 (02-01-2018).

Dwivedi et al. Explainable AI (XAI): Core ideas, techniques, and solutions. ACM Computing Surveys 55.9 (2023): 1-33.

Emanuilov, I. (2020). Security through transparency and openness in computer design. Em Int. Conf. on Risks and Security of Internet and Systems, p. 105–116. Springer.

European Union - The EU Artificial Intelligence Act. Available in [link] (2024)

European Union Agency for Cybersecurity, Malatras, A., Agrafiotis, I., and Adamczyk, M. "Securing machine learning algorithms". Publications Office of the European Union.

European Union Agency for Cybersecurity. "Artificial Intelligence and Cybersecurity Research".

F. M. Nardini, C. Rulli, S. Trani, and R. Venturini. Neural network compression using binarization and few full-precision weights. arXiv preprint arXiv:2306.08960, 2023.

F. Viegas, A. Pereira, W. Cunha, C. França, C. Andrade, E. Tuler, L. Rocha, and M. A. Gonçalves. Exploiting contextual embeddings in hierarchical topic modeling and investigating the limits of the current evaluation metrics. Computational Linguistics, pages 1–41, 03 2025.

F. Viegas, S. Canuto, C. Gomes, W. Luiz, T. Rosa, S. Ribas, L. Rocha, and M. A. Gonçalves. Cluwords: Exploiting semantic word clustering representation for enhanced topic modeling. In Proc. of the 12th ACM Int. Conf. on Web Search and Data Mining, WSDM ’19, page 753–761, 2019.

F. Viegas, S. D. Canuto, W. Cunha, C. França, C. M. V. de Andrade, G. Fonseca, A. Machado, L. Rocha, and M. A. Gonçalves. Pipelining semantic expansion and noise filtering for sentiment analysis of short documents - clusent method. J. Interact. Syst., 15(1):561–575, 2024.

F. Viegas, W. Cunha, C. Gomes, A. Pereira, L. Rocha, and M. Goncalves. CluHTM - semantic hierarchical topic modeling based on CluWords. In ACL, pages 8138–8150, 2020.

Falcão, J. (2025). Open Algorithms: an interdisciplinary inquiry of artificial intelligence systems. Tese de doutorado. Centro de Informática – UFPE.

Farahani, M. S. and Ghasemi, G. (2024). Artificial intelligence and inequality: challenges and opportunities. Qeios, 7:1–14.

Flores, H. (2024). Opportunistic multi-drone networks: Filling the spatiotemporal holes of collaborative and distributed applications. IEEE Internet of Things Magazine, 7(2):94–100.

Floridi L, Cowls J, Beltrametti M, et al (2018) AI4People-An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds Mach 28:689–707.

G. D. Bianco, D. Duarte, and M. A. Gonçalves. Reducing the user labeling effort in effective high recall tasks by fine-tuning active learning. IIS, 61(2):453–472, 2023.

Gao, Y. et al. (2024). Retrieval-augmented generation for large language models: A survey.

Garcez, A. d. and Lamb, L. C. (2023). Neurosymbolic AI: the 3rd wave. Artificial Intelligence Review, 56(11):12387–12406.

Gasser, U. and Virgilio Almeida. A layered model for AI governance. IEEE Internet Computing 21.6 (2017): 58-62.

Gero, K. I., Desai, M., Schnitzler, C., Eom, N., Cushman, J., and Glassman, E. L. (2025). Creative writers’ attitudes on writing as training data for large language models. CHI ’25, New York, NY, USA. Association for Computing Machinery.

Ghasemaghaei, M. and Kordzadeh, N. (2024). Understanding how algorithmic injustice leads to making discriminatory decisions: An obedience to authority perspective. Information and Management, 61(2):103921.

Gkini, O., Belmpas, T., Koutrika, G., and Ioannidis, Y. (2021). An in-depth benchmarking of text-to-sql systems. In Proceedings of the 2021 International Conference on Management of Data, SIGMOD ’21, page 632–644, New York, NY, USA. Association for Computing Machinery.

Gonçalves, L.R.; Moura, R.F.; Carro, L. Aggressive energy reduction for video inference with software-only strategies. ACM transactions Embedded Computer Systems, v.18, issue 5, p. 1-20, 2019.

Google. Google Play Families Policies. Available in [link]. (2024)

Google. Responsible AI. Available in [link]. (2024b)

Govett, M., Bah, B., Bauer, P., et al. (2024). Exascale computing and data handling: Challenges and opportunities for weather and climate prediction. Bulletin of the American Meteorologic Society, early access.

Guo, Y., Zheng, Y., Tan, M., Chen, Q., Chen, J., Zhao, P., and Huang, J. (2019). NAT: Neural architecture transformer for accurate and compact architectures. In Advances in Neural Information Processing Systems (NeurIPS 2019), volume 32, pages 1–12. Curran Associates, Inc.

HARRIS, Tristan and RASKIN, Aza. (2023) “The AI Dilemma. [S.l.]: Center for Humane Technology” [link]. Acesso em: 19 set. 2024.

Hassan, M., Mubashir Rehmani, & Jinjun Chen. Differential privacy techniques for cyber physical systems: A survey. IEEE Communications Surveys & Tutorials 22.1 (2019): 746-789.

Hennessy, J. L. and Patterson, D. A. (2019). A new golden age for computer architecture. Commun. ACM, 62(2):48–60.

Hintz, A., Dencik, L. and Wahl-Jorgensen, K. (2019). “Digital Citizenship in a Datafied Society”. Polity Press, United Kingdom.

Hohma, E. & Christoph Lütge. From trustworthy principles to a trustworthy development process: The need and elements of trusted development of AI systems. AI 4.4 (2023): 904-925.

Holgersson, J., Kävrestad, J., and Nohlberg, M. (2021). Cybersecurity and digital exclusion of seniors: What do they fear? In International Symposium on Human Aspects of Information Security and Assurance, pages 12–21. Springer.

Huang et al. An overview of artificial intelligence ethics. IEEE Transactions on Artificial Intelligence 4.4 (2022): 799-819.

Hundt, A., Schuller, J. & Severin Kacianka. Towards Equitable Agile Research and Development of AI and Robotics. arXiv preprint arXiv:2402.08242 (2024).

IBGE (2022). Panorama do censo 2022. [link].

IBM. AI Fairness 360. Available in [link] (2024)

IETF GAIA (2024). IETF GAIA. Available: [link].

Janaćković, G., Vasović, D. and Bojan Vasović. Artificial Intelligence standardisation efforts. Engineering management and competitiveness (EMC 2024) (2024): 250.

Jobin et al. The global landscape of AI ethics guidelines. Nat Mach Intell 1:389–399. (2019)

Jones-Jang, S. M., Mortensen, T., and Liu, J. (2021). Does media literacy help identification of fake news? information literacy helps, but other literacies don’t. American Behavioral Scientist, 65(2):371–388.

Jones, N. et al. (2018). How to stop data centres from gobbling up the world’s electricity. nature, 561(7722):163–166.

Jungmair, M., Kohn, A., and Giceva, J. (2022). Designing an open framework for query optimization and compilation. Proc. VLDB Endow., 15(11):2389–2401.

Jurafsky, D. and Martin, J. H. (2024). Speech and Language Processing.

Katsogiannis-Meimarakis, G. and Koutrika, G. (2021). A deep dive into deep learning approaches for text-to-sql systems. In Li, G., Li, Z., Idreos, S., and Srivastava, D., editors, SIGMOD ’21: International Conference on Management of Data, Virtual Event, China, June 20-25, 2021, pages 2846–2851. ACM.

Katsogiannis-Meimarakis, G. and Koutrika, G. (2023). A survey on deep learning approaches for text-to-sql. The VLDB Journal, 32(4):905–936.

Kersten, T., Leis, V., Kemper, A., Neumann, T., Pavlo, A., and Boncz, P. A. (2018). Everything you always wanted to know about compiled and vectorized queries but were afraid to ask. Proc. VLDB Endow., 11(13):2209–2222.

Kirkpatrick, K. It’s not the algorithm, it’s the data. Communications of ACM 60:21–23. (2017)

KOZLOWSKI, W. et al. RFC 9340 Architectural principles for a quantum internet. Wilmington, DE, USA: RFC Editor, 2023.

Kreps, S., McCain, R. M., and Brundage, M. (2022). All the news that’s fit to fabricate: Ai-generated text as a tool of media misinformation. Journal of experimental political science, 9(1):104–117.

Kumar, M., Dwivedi, V., Sanyal, A., Bhatt, P. and Koshariya, R. (2021). Parental Security Control: A tool for monitoring and securing children's online activities. In Proc. ACM 13th International Conference on Contemporary Computing, 469–474.

Łabuz, M. & Nehring, C. On the way to deep fake democracy? Deep fakes in election campaigns in 2023. European Political Science (2024): 1-20.

Lamb, L. C. et al. (2020). Graph neural networks meet neural-symbolic computing: A survey and perspective. In Int. Joint Conf. on Artificial Intelligence.

Leiner, B. M., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., Postel, J., Roberts, L. G., and Wolff, S. (2009). A brief history of the Internet. ACM SIGCOMM Computer Communication Review, 39(5):22–31.

Lessig L Code: And Other Laws of Cyberspace, Version 2.0, 2nd edn. Basic Books (2006)

Li, F. and Jagadish, H. V. (2014). Constructing an interactive natural language interface for relational databases. Proc. VLDB Endow., 8(1):73–84.

Li, H., Zhang, J., Liu, H., Fan, J., Zhang, X., Zhu, J., Wei, R., Pan, H., Li, C., and Chen, H. (2024). Codes: Towards building open-source language models for text-to-sql. Proc. ACM Manag. Data, 2(3):127.

Li, Tian, et al. Federated learning: Challenges, methods, and future directions. IEEE signal processing magazine 37.3 (2020): 50-60.

LI, Y. et al. A survey of quantum internet protocols from a layered perspective. IEEE Communications Surveys & Tutorials, IEEE, 2024.

Liang, P. et al. (2023). Holistic evaluation of language models. arXiv preprint arXiv:2211.09110.

Lie, S. (2023). Inside the cerebras wafer-scale cluster: Cerebras systems. In IEEE Hot Chips Symposium (HCS), volume 35, pages 1–41. IEEE.

Lima, L., Furtado, V., Furtado, E., and Almeida, V. (2019). Empirical analysis of bias in voice-based personal assistants. In Companion Proceedings of The 2019 World Wide Web Conference, pages 533–538.

Ling, A. and Inglês, R. (2024). Como porto alegre ficou debaixo d’água. Folha de São Paulo: [link]. Acessado em agosto de 2024.

Liu, A., Sheng, Q., and Hu, X. (2024). Preventing and detecting misinformation generated by large language models. In Proc. of the International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 3001–3004.

Liu, Y. "A hitchhiker’s guide to jailbreaking chatgpt via prompt engineering". 4th International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things, SEA4DQ 2024. ACM.

Locatelli, M. S. et al. (2024). Examining the behavior of LLM architectures within the framework of standardized national exams in Brazil. arXiv preprint arXiv:2408.05035.

Lu et al. Responsible AI pattern catalogue: A collection of best practices for AI governance and engineering. ACM Computing Surveys 56.7 (2024): 1-35.

Lucaj, L., Van Der Smagt, P. and Djalel Benbouzid. "AI regulation is (not) all you need." Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. (2023).

Lythreatis, S., Singh, S. K., and El-Kassar, A.-N. (2022). The digital divide: A review and future research agenda. Technological Forecasting and Social Change, 175:121359.

Lyu, B., Chen, J., Wang, S., et al. (2024). Graphene nanoribbons grown in hbn stacks for high-performance electronics. Nature, 628:758–764.

M. Siino, I. Tinnirello, and M. La Cascia. Is text preprocessing still worth the time? a comparative survey on the influence of popular preprocessing methods on transformers. Inf. Sys., 121:102342, 2024.

Macêdo, R. J., de Sá, A. S., Freitas, A. E. S., Veríssimo, P. E., Gorender, S., and de Sá, M. O. S. (2023). 42a Jornada de Atualização em Informática, chapter Confiabilidade e Segurança nos Sistemas Distribuídos Físico-Digitais. SBC. DOI: 10.5753/sbc.12853.0.2.

Maciel, C.; Slaviero, C. ; Cappelli, C. ; Garcia, A. C. B. (2016). Technologies for popular participation: a research agenda. In: 17th Annual International Conference on Digital Government Research, Shanghai-China. Internet Plus Government: New Opportunities to Solve Public Problems. New York: ACM, 2016. p. 202-211. DOI: 10.1145/2912160.291219

Madaio et al. Co-designing checklists to understand organizational challenges and opportunities around fairness in AI. Proceedings of the 2020 CHI conference on human factors in computing systems. (2020)

Marasco, S., Kammouh, O., and Cimellaro, G. P. (2022). Disaster resilience quantification of communities: A risk-based approach. International Journal of Disaster Risk Reduction, 70:102778.

Martins, P., Afonso, A., and da Silva, A. S. (2023). Pylathedb - A library for relational keyword search with support to schema references. In 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023, pages 3627–3630. IEEE.

Matsuoka, S., Domkel, J., Wahib, M., Drozd, A., and Hoefler, T. (2023). Myths and legends in high-performance computing. Int. Journal of High Performance Computing and Applications, 37(3-4):245–259.

MAVROEIDIS, V. et al. The impact of quantum computing on present cryptography. International Journal of Advanced Computer Science and Applications, The Science and Information Organization, v. 9, n. 3, 2018. DOI: 10.14569/IJACSA.2018.090354.

McCoy et al. Ethical responsibilities for companies that process personal data. The American Journal of Bioethics 23.11 (2023): 11-23.

Melo, P. F., Hoseini, M., Zannettou, S., and Benevenuto, F. (2024). Don’t break the chain: Measuring message forwarding on whatsapp. In Proc. of the Int’l AAAI Conference on Weblogs and Social Media (ICWSM), pages 1054–1067.

MetSul (2024). Imagens de satélite mostram enchente arrasadora na grande porto alegre. [link].

Microsoft. Empowering responsible AI practices. Available in [link]. (2024)

Monte, A. (2019). A influência da escolaridade e do sexo/gênero no uso variável da concordância verbal de terceira pessoa do plural. Revista Diálogos, 7:89–104.

Morley, J., Floridi, L., et al. From what to how: an initial review of publicly available AI ethics tools, methods and research to translate principles into practices. Sci. Eng. Ethics 26, 2141–2168 (2020).

Mothukuri et al. A survey on security and privacy of federated learning, Future Generation Computer Systems, vol. 115, pp. 619–640, (2021).

Mueller et al. Addressing driver disengagement and proper system use: human factors recommendations for level 2 driving automation design. Journal of cognitive engineering and decision making 15.1 (2021): 3-27.

Muñoz, A., Rios, R., Román, R. e López, J. (2023). A survey on the (in) security of trusted execution environments. Computers & Security, 129:103180.

Murthy, V. (2023). Social Media and Youth Mental Health – The U.S. Surgeon General’s Advisory. Disponível em: [link]

Myrdal, G. (1968). Teoria econômica das regiões. Saga. [link].

N. Jones. How to stop data centres from gobbling up the world’s electricity. Nature, 561(7722):163–167, 2018.

Nagumo, E., Teles, L. F., and Silva, L. de A. (2020). A utilização de vídeos do Youtube como suporte ao processo de aprendizagem. Revista Eletrônica De Educação, 14, e3757008.

Neumann, M. M., Park, E., Soong, H., Nichols, S. and Selim, N. (2022). Exploring the social media networks of primary school children. Education 3-13, 1–15.

Neves Camêlo, M. and Alves, C. (2023). G-priv: A guide to support lgpd compliant specification of privacy requirements. iSys - Brazilian Journal of Information Systems, 16:2:1 – 2.

NIC.Br (2024). Conectividade significativa: Propostas para medição e o retrato da população no brasil. [link].

Oda, R., Cordeiro, D., and Braghetto, K. R. (2018). Dynamic resource provisioning for scientific workflow executions in clouds. In 2018 IEEE International Conference on Services Computing (SCC), pages 291–294. IEEE.

OECD (2022). Rights in the Digital Age: Challenges and Ways Forward. OECD Digital Economy Papers, No. 347. Disponível em: [link].

Oliveira, J., Silva, T., Oliveira, R., and Furtado, E. (2025). Recommendations of embodied conversational agents to healthcare applications.

P. Liang et al. Holistic evaluation of language models. Transactions on Machine Learning Research, 2023. Featured Certification, Expert Certification.

Paiva, D. M. B., Freire, A. P., and de Mattos Fortes, R. P. (2021). Accessibility and software engineering processes: A systematic literature review. Journal of Systems and Software, 171:110819.

Pasupat, P. and Liang, P. (2015). Compositional semantic parsing on semi-structured tables. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL 2015, July 26-31, 2015, Beijing, China, Volume 1: Long Papers, pages 1470–1480. The Association for Computer Linguistics.

Pena, E. H. M., de Almeida, E. C., and Naumann, F. (2021). Fast detection of denial constraint violations. Proc. VLDB Endow., 15(4):859–871.

Pereira, R., Darin, T., and Silveira, M. S. (2024). Grandihc-br: Grand research challenges in human-computer interaction in brazil for 2025-2035. In Proceedings of the XXIII Brazilian Symposium on Human Factors In Computing Systems.

Pollini, A., Callari, T. C., Tedeschi, A., Ruscio, D., Save, L., Chiarugi, F. e Guerri, D. (2022). Leveraging human factors in cybersecurity: an integrated methodological approach. Cognition, Technology & Work, 24(2):371–390.

Porto, A. V. F. and Furtado, M. E. S. (2024). Framework to specify dialogues for natural interaction with conversational assistants applied in prompt engineering. In Arai, K., editor, Intelligent Systems and Applications, pages 231–253, Cham. Springer Nature Switzerland.

Prem, E. From ethical AI frameworks to tools: a review of approaches. AI and Ethics 3.3 (2023): 699-716.

Preto, S. and Finger, M. (2023). Proving properties of binary classification neural networks via łukasiewicz logic. Log. J. IGPL, 31(5):805–821.

Procempa (2024). Procempa mantém operações apesar de alagamento. [link].

Ramezanpour, K. e Jagannath, J. (2022). Intelligent zero trust architecture for 5G/6G networks: Principles, challenges, and the role of machine learning in the context of O-RAN. Computer Networks, 217:109358.

Ray, P. P., Mukherjee, M., and Shu, L. (2017). Internet of things for disaster management: State-of-the-art and prospects. IEEE Access, 5:18818–18835.

Reed, D., Gannon, D., and Dongarra, J. (2023). HPC Forecast: Cloudy and uncertain. Commun. ACM, 66(2):82–90.

Reis, J. C., Correia, A., Murai, F., Veloso, A., and Benevenuto, F. (2019). Supervised learning for fake news detection. IEEE Intelligent Systems, 34(2):76–81.

Reis, J. C., Melo, P., Silva, M., and Benevenuto, F. (2023). Desinformação em plataformas digitais: Conceitos, abordagens tecnológicas e desafios. Congresso da Sociedade Brasileira de Computação (CSBC). Jornada de Atualização em Informática (JAI).

Ren, X., Su, L., Gu, Z., Wang, S., Li, F., Xie, Y., Bian, S., Li, C., and Zhang, F. (2022). HEDA: multi-attribute unbounded aggregation over homomorphically encrypted database. Proc. VLDB Endow., 16(4):601–614.

Robinson, L., Cotten, S. R., Ono, H., Quan-Haase, A., Mesch, G., Chen, W., Schulz, J., Hale, T. M., and Stern, M. J. (2015). Digital inequalities and why they matter. Information, communication & society, 18(5):569–582.

Robles-Carrillo, M. (2024). Digital identity: an approach to its nature, concept, and functionalities. International Journal of Law and Information Technology, 32(1), eaae019. DOI: 10.1093/ijlit/eaae019

Rocha, F. W., Fukuda, J. C., Francesquini, E., and Cordeiro, D. (2022). Accelerating smart city simulations. In Gitler, I., Barrios Hernández, C. J., and Meneses, E., editors, High Performance Computing, pages 148–162, Cham. Springer International Publishing.

Rodrigues, R. (2020). Legal and human rights issues of ai: Gaps, challenges and vulnerabilities. Journal of Responsible Technology, 4.

Safari, F., Savić, I., Kunze, H., Ernst, J., and Gillis, D. (2023). A review of ai-based manet routing protocols. In 2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pages 43–50.

Sanderson et al. AI Ethics Principles in Practice: Perspectives of Designers and Developers, IEEE Transactions on Technology and Society, pp. 1–1, (2023).

SANTAGATI, R. et al. Challenges and opportunities for applying quantum computers to drug design. Bulletin of the American Physical Society, APS, 2024.

SBC (2023). Referenciais de formação para o curso de bacharelado em cibersegurança. Relatório técnico, Sociedade Brasileira de Computação (SBC).

Scheibe, A., Reichert, W., Gaspary, L., and Cordeiro, W. (2021). Programmable low-end networks: Powering internet connectivity for the other three billion. In 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM), pages 187–195. IEEE.

Senado Federal Brasileiro. Projeto de Lei n° 2338. Disponível em [link] (2023)

Shaheen, M. M. Z., Amer, H. H., and Ali, N. A. (2023). Robust air-to-air channel model for swarms of drones in search and rescue missions. IEEE Access, 11:68890–68896.

SHAP. Available in [link]. (2024)

Shneiderman, B. (2020). Bridging the gap between ethics and practice: Guidelines for reliable, safe, and trustworthy human-centered ai systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 10(4):1–31.

Shu, K., Sliva, A., Wang, S., Tang, J., and Liu, H. (2017). Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter, 19(1):22–36.

Silva, V., Furtado, E., Oliveira, J., and Furtado, V. (2024). Engenharia de prompts em assistentes conversacionais para promoção de autocuidado baseados em modelos amplos de linguagem. In Simpósio Brasileiro de Computação Aplicada à Saúde, Goiânia.

Sin, J., L. Franz, R., Munteanu, C., and Barbosa Neves, B. (2021). Digital design marginalization: New perspectives on designing inclusive interfaces. In 2021 CHI Conference on Human Factors in Computing Systems, pages 1–11.

Slattery, P., S. A. K., Grundy, Emily A. C.; Graham, J., Noetel, M.; Uuk, R. D. J. P. S. C. S., and Thompson, N. (2024). The ai risk repository: A comprehensive meta-review, database, and taxonomy of risks from artificial intelligence.

Sociedade Brasileira de Computação (2022). Tecnologias digitais para o meio ambiente: Manifesto SBC. coordenação de Marcelo Rita Pias e Raimundo José de Araújo Macêdo. DOI: 10.5753/sbc.rt.2022.07.01.

Sony Global. Sony Group's Initiatives for Responsible AI. Available in [link]. (2024)

Soomro, K. A., Kale, U., Curtis, R., Akcaoglu, M., and Bernstein, M. (2020). Digital divide among higher education faculty. International Journal of Educational Technology in Higher Education, 17:1–16.

Sterbenz, J. P., Hutchison, D., Çetinkaya, E. K., Jabbar, A., Rohrer, J. P., Schöller, M., and Smith, P. (2010). Resilience and survivability in communication networks: Strategies, principles, and survey of disciplines. Computer Networks, 54(8):1245 – 1265. Resilient and Survivable networks.

Streit, J., Bukvin, I., Chan, S., et al. (2024). The ribosome lowers the entropic penalty of protein folding. Nature, 633:232–239.

Suarez-Lledo, V. and Alvarez-Galvez, J. (2021). Prevalence of health misinformation on social media: systematic review. Journal of medical Internet research, 23(1):e17187.

Sudo, M. A., Fazenda, A. L., and Souto, R. P. (2022). Mixed precision applied on common mathematical procedures over gpu. In Simpósio em Sistemas Computacionais de Alto Desempenho (SSCAD), pages 265–275. SBC.

Sunyé, M. S. (2020). A quem servem os dados? SBC Horizontes, 4.

Swire-Thompson, B., Lazer, D., et al. (2020). Public health and online misinformation: challenges and recommendations. Annu Rev Public Health, 41(1):433–451.

Tarallo, F. (1985). A pesquisa sociolinguística. Ática.

Thadani, Trisha, et al. Tesla drivers run Autopilot where it's not intended-with deadly consequences. The Washington Post (2023): NA-NA.

Tiribelli, S. The AI ethics principle of autonomy in health recommender systems. Argumenta 16 (2023): 1-18.

Treen, K. M. d., Williams, H. T., and O’Neill, S. J. (2020). Online misinformation about climate change. Wiley Interdisciplinary Reviews: Climate Change, 11(5):e665.

Trevisan, D., Maciel, C., & Souza, T. F. M. de. (2022). O Lugar da Crítica na Mobilização de Letramentos Digitais. Revista de Educação do Vale do Arinos - RELVA, 9(2), 110-133. DOI: 10.30681/relva.v9i2.6023

Tubella, A. Marçal Mora-Cantallops, A. and Juan Carlos Nieves. How to teach responsible AI in Higher Education: challenges and opportunities. Ethics and Information Technology 26.1 (2024): 3.

UNICEF (2020). Dois terços das crianças em idade escolar no mundo não têm acesso à internet em casa, diz novo relatório do unicef-itu. [link].

United Nations (2016). The promotion, protection and enjoyment of human rights on the internet. UN Digital Library, A/HRC/32/L.20(32):1–4.

Van Dijk, J. (2017). Digital divide: Impact of access. The international encyclopedia of media effects, 1:1–11.

Vassilev et. al., “Adversarial machine learning: A taxonomy and terminology of attacks and mitigations.”

Vassilev, A., Oprea, A., Fordyce, A. e Anderson, H. (2024). Adversarial machine learning: A taxonomy and terminology of attacks and mitigations. Relatório técnico, National Institute of Standards and Technology.

Veers, P., Bottasso, C. L., Manuel, L., et al. (2023). Grand challenges in the design, manufacture, and operation of future wind turbine systems. Wind Energy Science, 8(7):1071–1131.

Viterbo, J.; Bernardini, F. (2022). Empoderamento Digital: O Papel da Computação na Construção de uma Sociedade Inclusiva e Democrática. Computação Brasil, 48, p. 12–14. DOI: 10.5753/compbr.2022.48.2777

Vosoughi, S., Roy, D., and Aral, S. (2018). The spread of true and false news online. Science, 359(6380):1146–1151.

W. Cunha et al. A comparative survey of instance selection methods applied to nonneural and transformer-based text classification. ACM Comput. Surv., 2023.

W. Cunha, A. Moreo Fernández, A. Esuli, F. Sebastiani, L. Rocha, and M. A. Gonçalves. A noise-oriented and redundancy-aware instance selection framework. ACM Trans. Inf. Syst., 43(2), Jan. 2025.

W. Cunha, A. Pasin, M. Goncalves, and N. Ferro. A quantum annealing instance selection approach for efficient and effective transformer fine-tuning. In ACM ICTIR, 2024.

W. Cunha, C. França, G. Fonseca, L. Rocha, and M. A. Gonçalves. An effective, efficient, and scalable confidence-based instance selection framework for transformer-based text classification. In ACM SIGIR, pages 665–674, 2023.

W. Cunha, S. Canuto, F. Viegas, T. Salles, C. Gomes, V. Mangaravite, E. Resende, T. Rosa, M. Gonçalves, and L. Rocha. Extended pre-processing pipeline for text classification: On the role of meta-feature representations, sparsification and selective sampling. IP&M, 2020.

W. Cunha, V. Mangaravite, C. Gomes, S. Canuto, C. Nascimento, F. Viegas, C. França, W. S. Martins, J. M. Almeida, et al. On the cost-effectiveness of neural and non-neural approaches and representations for text classification: A comprehensive comparative study. IP&M, 58(3):102481, 2021.

W. L. M. da Cunha. A comprehensive exploitation of instance selection methods for automatic text classification. PhD thesis, Aug. 2024. Available at [link].

W. Luiz, F. Viegas, R. Alencar, F. Mourão, T. Salles, D. Carvalho, M. A. Gonçalves, and L. Rocha. A feature-oriented sentiment rating for mobile app reviews. In WWW’18, pages 1909–1918, 2018.

WANG, C. et al. RFC 9583 Application Scenarios for the Quantum Internet. Wilmington, DE, USA: RFC Editor, 2024.

WANG, J. et al. Quantum-safe cryptography: crossroads of coding theory and cryptography. Science China Information Sciences, Springer, v. 65, n. 1, p. 111301, 2022.

Weiser, M. (1999). The computer for the 21st century. SIGMOBILE Mob. Comput. Commun., 3(3):3–11.

Wikipedia. Source lines of code. [link] Último acesso em 08/09/2024.

Wilson-Menzfeld, G., Erfani, G., Young-Murphy, L., Charlton, W., De Luca, H., Brittain, K., and Steven, A. (2024). Identifying and understanding digital exclusion: a mixed-methods study. Behaviour & Information Technology, pages 1–18.

Wu, J., Guo, J., and Hooi, B. (2024). Fake news in sheep’s clothing: Robust fake news detection against llm-empowered style attacks. In Proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pages 3367–3378.

Ximenes B & Ramalho G. Concrete Ethical Guidelines and Best Practices in Machine Learning Development. In: Proceedings of IEEE International Symposium on Technology and Society. (2021)

Ximenes, B. Salcedo, D. & Ramalho, G. Towards broadening the perspective on lethal autonomous weapon systems ethics and regulations. Rio Seminar on Autonomous Weapons Systems. (Rio de Janeiro, Naval War College) - Brasília: FUNAG, 2020

Xing, J., Wang, X., and Jagadish, H. V. (2024). Data-driven insight synthesis for multi-dimensional data. Proc. VLDB Endow., 17(5):1007–1019.

Yasavur, U.; Lisetti, C. and Rishe, N. (2014). Let’s talk! speaking virtual counselor offers you a brief intervention. Journal on Multimodal User Interfaces, 8(4):381–398.

Yu, J. X., Qin, L., and Chang, L. (2010). Keyword search in relational databases: A survey. IEEE Data Eng. Bull., 33(1):67–78.

Yudkowsky, Eliezer. "The AI alignment problem: why it is hard, and where to start." Symbolic Systems Distinguished Speaker 4.1 (2016).

Zhang, L., Zhang, J., Ke, X., Li, H., Huang, X., Shao, Z., Cao, S., and Lv, X. (2023). A survey on complex factual question answering. AI Open, 4:1–12.

Zhang, T., Qin, Y., & Li, Q. (2021). Trusted artificial intelligence: technique requirements and best practices. International Conference on Cyberworlds (CW). IEEE (2021).

Downloads

Publication date

November 27, 2024

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Details about the available publication format: Full Volume

Full Volume

ISBN-13 (15)

978-85-7669-640-7