Brainwriting na elicitação de requisitos para IA confiável
Resumo
Falhas apontadas em sistemas de Aprendizado de Máquina (AM) têm afetado a confiança dos usuários, tornando-se essencial abordar o tema. Este estudo investiga o uso da técnica Brainwriting na elicitação de requisitos para Inteligência Artificial (IA) confiável, com foco em AM, por meio da colaboração multidisciplinar dos papéis envolvidos. O estudo foi conduzido com um grupo de mulheres com perfis de atuação diferentes, facilitado por um mediador. Ao final do estudo, um conjunto de perguntas abertas foi aplicado para compreender a perspectiva das participantes em relação à IA confiável. Com o estudo foi possível criar requisitos para a IA confiável, com ênfase em AM, além de proporcionar a participação multidisciplinar, utilizando Brainwriting.
Referências
Ahmad, K., Bano, M., Abdelrazek, M., Arora, C., and Grundy, J. (2021). What’s up with requirements engineering for artificial intelligence systems? In 2021 IEEE 29th International Requirements Engineering Conference (RE), pages 1–12.
Bellaby, R. W. (2021). Can ai weapons make ethical decisions? Criminal Justice Ethics, 40(2):86–107.
Calazans, A. T. S., Paldês, R. Á., Masson, E. T. S., and Guimarães, F. d. A. (2018). As técnicas de elicitação e de documentação de requisitos nos métodos ágeis. In CIbSE, pages 487–500.
Dastin, J. (2018). Amazon scraps secret ai recruiting tool that showed bias against women. In Ethics of Data and Analytics, pages 296–299. Auerbach Publications.
de Cerqueira, J. A. S., De Azevedo, A. P., Leão, H. A. T., and Canedo, E. D. (2022). Guide for artificial intelligence ethical requirements elicitation-re4ai ethical guide. In HICSS, pages 1–10.
de Oliveira Carvalho, N., Libório Sampaio, A., and de Vasconcelos, D. R. (2022). Morexai - a model to reason about the explanation design in ai systems. In Degen, H. and Ntoa, S., editors, Artificial Intelligence in HCI, pages 130–148, Cham. Springer International Publishing.
Gruber, K., Huemer, J., Zimmermann, A., and Maschotta, R. (2017). Integrated description of functional and non-functional requirements for automotive systems design using sysml. In 2017 7th IEEE International Conference on System Engineering and Technology (ICSET), pages 27–31.
Heslin, P. A. (2009). Better than brainstorming? potential contextual boundary conditions to brainwriting for idea generation in organizations. Journal of Occupational and Organizational Psychology, 82(1):129–145.
Horkoff, J. (2019). Non-functional requirements for machine learning: Challenges and new directions. In 2019 IEEE 27th International Requirements Engineering Conference (RE), pages 386–391.
Ishikawa, F. and Matsuno, Y. (2020). Evidence-driven requirements engineering for uncertainty of machine learning-based systems. In 2020 IEEE 28th International Requirements Engineering Conference (RE), pages 346–351. IEEE.
Kaur, D., Uslu, S., Rittichier, K. J., and Durresi, A. (2022). Trustworthy artificial intelligence: A review. ACM Comput. Surv., 55(2).
Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Research methods in human-computer interaction. Morgan Kaufmann.
Michinov, N. (2012). Is electronic brainstorming or brainwriting the best way to improve creative performance in groups? an overlooked comparison of two idea-generation techniques. Journal of Applied Social Psychology, 42:E222–E243.
Pazmino, A. V. (2015). Como se cria: 40 métodos para design de produtos. Editora Blucher.
Pei, Z., Liu, L., Wang, C., and Wang, J. (2022). Requirements engineering for machine learning: A review and reflection. In 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW), pages 166–175.
Thiebes, S., Lins, S., and Sunyaev, A. (2021). Trustworthy artificial intelligence. Electronic Markets, 31:447–464.
VanGundy, A. B. (1984). Brain writing for new product ideas: an alternative to brainstorming. Journal of Consumer Marketing.
Yoshioka, N., Husen, J. H., Tun, H. T., Chen, Z., Washizaki, H., and Fukazawa, Y. (2021). Landscape of requirements engineering for machine learning-based ai systems. In 2021 28th Asia-Pacific Software Engineering Conference Workshops (APSEC Workshops), pages 5–8.
Bellaby, R. W. (2021). Can ai weapons make ethical decisions? Criminal Justice Ethics, 40(2):86–107.
Calazans, A. T. S., Paldês, R. Á., Masson, E. T. S., and Guimarães, F. d. A. (2018). As técnicas de elicitação e de documentação de requisitos nos métodos ágeis. In CIbSE, pages 487–500.
Dastin, J. (2018). Amazon scraps secret ai recruiting tool that showed bias against women. In Ethics of Data and Analytics, pages 296–299. Auerbach Publications.
de Cerqueira, J. A. S., De Azevedo, A. P., Leão, H. A. T., and Canedo, E. D. (2022). Guide for artificial intelligence ethical requirements elicitation-re4ai ethical guide. In HICSS, pages 1–10.
de Oliveira Carvalho, N., Libório Sampaio, A., and de Vasconcelos, D. R. (2022). Morexai - a model to reason about the explanation design in ai systems. In Degen, H. and Ntoa, S., editors, Artificial Intelligence in HCI, pages 130–148, Cham. Springer International Publishing.
Gruber, K., Huemer, J., Zimmermann, A., and Maschotta, R. (2017). Integrated description of functional and non-functional requirements for automotive systems design using sysml. In 2017 7th IEEE International Conference on System Engineering and Technology (ICSET), pages 27–31.
Heslin, P. A. (2009). Better than brainstorming? potential contextual boundary conditions to brainwriting for idea generation in organizations. Journal of Occupational and Organizational Psychology, 82(1):129–145.
Horkoff, J. (2019). Non-functional requirements for machine learning: Challenges and new directions. In 2019 IEEE 27th International Requirements Engineering Conference (RE), pages 386–391.
Ishikawa, F. and Matsuno, Y. (2020). Evidence-driven requirements engineering for uncertainty of machine learning-based systems. In 2020 IEEE 28th International Requirements Engineering Conference (RE), pages 346–351. IEEE.
Kaur, D., Uslu, S., Rittichier, K. J., and Durresi, A. (2022). Trustworthy artificial intelligence: A review. ACM Comput. Surv., 55(2).
Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Research methods in human-computer interaction. Morgan Kaufmann.
Michinov, N. (2012). Is electronic brainstorming or brainwriting the best way to improve creative performance in groups? an overlooked comparison of two idea-generation techniques. Journal of Applied Social Psychology, 42:E222–E243.
Pazmino, A. V. (2015). Como se cria: 40 métodos para design de produtos. Editora Blucher.
Pei, Z., Liu, L., Wang, C., and Wang, J. (2022). Requirements engineering for machine learning: A review and reflection. In 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW), pages 166–175.
Thiebes, S., Lins, S., and Sunyaev, A. (2021). Trustworthy artificial intelligence. Electronic Markets, 31:447–464.
VanGundy, A. B. (1984). Brain writing for new product ideas: an alternative to brainstorming. Journal of Consumer Marketing.
Yoshioka, N., Husen, J. H., Tun, H. T., Chen, Z., Washizaki, H., and Fukazawa, Y. (2021). Landscape of requirements engineering for machine learning-based ai systems. In 2021 28th Asia-Pacific Software Engineering Conference Workshops (APSEC Workshops), pages 5–8.
Publicado
06/08/2023
Como Citar
SILVA, Francisco Luciano Quirino da; SAMPAIO, Andréia Libório; BEZERRA, Carla Ilane Moreira; MONTEIRO, Ingrid Teixeira.
Brainwriting na elicitação de requisitos para IA confiável. In: WORKSHOP SOBRE ASPECTOS SOCIAIS, HUMANOS E ECONÔMICOS DE SOFTWARE (WASHES), 8. , 2023, João Pessoa/PB.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 111-120.
ISSN 2763-874X.
DOI: https://doi.org/10.5753/washes.2023.230891.
