Exploring Ethical Requirements Elicitation for Applications in the Context of AI


Ethical concerns arises from the proliferation of Artificial Intelligence (AI) based systems in use. AI ethics has been approached mainly in guidelines and principles, not providing enough practical guidance for developers. Hence, we aim to present RE4AI Ethical Guide and its evaluation. We used the Design Science Research methodology to understand the problem, present the guide and evaluate it through a focus group. The Guide is composed of 26 cards across 11 principles. We evaluated it with 5 AI professionals and our preliminary results reveal that it has the potential to facilitate the elicitation of ethical requirements. Thus, we contribute to bridge the gap between principles and practice by assisting developers to elicit ethical requirements and operationalise ethics in AI.

Palavras-chave: Ehics, Artificial Intelligence, Requirements Engineering, Ethics in Artificial Intelligence


Araujo, R., Maciel, R., and Boscarioli, C. (2017). I grandsi-br: Grandes desafios de pesquisa em sistemas de informação no brasil (2016-2026). Relatório Técnico. Comissão Especial de Sistemas de Informação (CE-SI) da Sociedade Brasileira de Computação (SBC). 67p.

Belani, H., Vukovic, M., and Car, Z. (2019). Requirements engineering challenges in building ai-based complex systems. In 27th IEEE International Requirements Engineering Conference Workshops, RE 2019 Workshops, Jeju Island, Korea (South), September 23-27, 2019, pages 252–255, 10.1109/REW.2019.00051. IEEE.

Benjamins, R., Barbado, A., and Sierra, D. (2019). Responsible ai by design in practice. arXiv, 1:1–10.

Cerqueira, J. A. S., Acco Tives, H., and Canedo, E. D. (2021a). Ethical guidelines and principles in the context of artificial intelligence. In XVII Brazilian Symposium on Information Systems, pages 1–8.

Cerqueira, J. A. S., Dos Santos Althoff, L., Santos De Almeida, P., and Canedo, E. D. (2021b). Ethical perspectives in AI: A two-folded exploratory study from literature and active development projects. In Proceedings of the 54th Hawaii International Conference on System Sciences, page 5240.

Cerqueira, J. A. S., Pinheiro De Azevedo, A., Acco Tives, H., and Canedo, E. D. (2022). Guide for Artificial Intelligence Ethical Requirements Elicitation - RE4AI Ethical Guide. Proceedings of the Annual Hawaii International Conference on System Sciences.

Commission, E. (2019). Ethics Guidelines for Trustworthy AI High-Level Expert Group on Artificial Intelligence.

de Ágreda, Á . G. (2020). Ethics of autonomous weapons systems and its applicability to any AI systems. Telecommunications Policy, 44:101953.

Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., and Srikumar, M. (2020). Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI. SSRN Electronic Journal, 1(1):1–39.

Floridi, L. and Cowls, J. (2019). A unified framework of five principles for AI in society. Issue 1, 1.

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., and Vayena, E. (2018). Ai4people - an ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds Mach., 28(4):689–707.

Guizzardi, R. S. S., Amaral, G. C. M., Guizzardi, G., and Mylopoulos, J. (2020). Ethical requirements for AI systems. In Canadian Conference on AI, volume 12109 of Lecture Notes in Computer Science, pages 251–256, https://doi.org/10.1007/978-3-030-47358-7_24. Springer.

Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds Mach., 30:99–120.

IEEE (2019). Ethically Aligned Design: A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems (EAD FirstEdition).

Jobin, A., Ienca, M., and Vayena, E. (2019). The global landscape of ai ethics guidelines. Nature Machine Intelligence, 1(9):389–399.

Kitchenham, B. A. and Pfleeger, S. L. (2002). Principles of survey research part 4: questionnaire evaluation. ACM SIGSOFT Softw. Eng. Notes, 27(3):20–23.

Kontio, J., Lehtola, L., and Bragge, J. (2004). Using the focus group method in software engineering: Obtaining practitioner and user experiences. In 2004 International Symposium on Empirical Software Engineering (ISESE 2004), 19-20 August 2004, Redondo Beach, CA, USA, pages 271–280. IEEE Computer Society.

Kostova, B., Gurses, S., andWegmann, A. (2020). On the interplay between requirements, engineering, and artificial intelligence. In Proceedings of REFSQ-2020 Workshops, Pisa, Italy, 2020, pages 1–5.

Krafft, T., Hauer, M., Fetic, L., Kaminski, A., Puntschuh, M., Otto, P., Hubig, C., Fleischer, T., Grünke, P., Hillerbrand, R., Hustedt, C., and Hallensleben, S. (2020). From principles to practice - an interdisciplinary framework to operationalise ai ethics.

Langford, J. and McDonagh, D. (2002). Focus groups: Supporting effective product development.

Lwakatare, L. E., Raj, A., Bosch, J., Olsson, H. H., and Crnkovic, I. (2019). A taxonomy of software engineering challenges for machine learning systems: An empirical investigation. In Kruchten, P., Fraser, S., and Coallier, F., editors, Agile Processes in Software Engineering and Extreme Programming - 20th International Conference, XP 2019, Montréal, QC, Canada, May 21-25, 2019, Proceedings, volume 355 of Lecture Notes in Business Information Processing, pages 227–243. Springer.

Mayer, A.-S., Haimerl, A., Strich, F., and Fiedler, M. (2021). How corporations encourage the implementation of ai ethics. In ECIS.

Méndez, D., Graziotin, D., Wagner, S., and Seibold, H. (2020). Open science in software engineering. In Felderer, M. and Travassos, G. H., editors, Contemporary Empirical Methods in Software Engineering, pages 477–501. Springer.

Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1(11):501–507.

Morley, J., Floridi, L., Kinsey, L., and Elhalal, A. (2019). From what to how: An initial review of publicly available ai ethics tools, methods and research to translate principles into practices. Science and Engineering Ethics, pages 1–28.

Newman, J. (2020). Decision Points in AI Governance: Three case studies explore efforts to operationalize AI principles. Center for Long-Term Cybersecurity - UC Berkeley.

Nguyen-Duc, A., Sundbø, I., Nascimento, E., Conte, T., Ahmed, I., and Abrahamsson, P. (2020). A multiple case study of artificial intelligent system development in industry. In Li, J., Jaccheri, L., Dingsøyr, T., and Chitchyan, R., editors, EASE ’20: Evaluation and Assessment in Software Engineering, Trondheim, Norway, April 15-17, 2020, pages 1–10. ACM.

Raji, I. D., Smart, A., White, R., Mitchell, M., Gebru, T., Hutchinson, B., Smith-Loud, J., Theron, D., and Barnes, P. (2020). Closing the ai accountability gap: defining an end-to-end framework for internal algorithmic auditing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency.

Rothenberger, L., Fabian, B., and Arunov, E. (2019). Relevance of ethical guidelines for artificial intelligence - a survey and evaluation. In vom Brocke, J., Gregor, S., and Müller, O., editors, 27th European Conference on Information Systems - Information Systems for a Sharing Society, ECIS 2019, Stockholm and Uppsala, Sweden, June 8-14, 2019, volume 27, pages 1–12.

Ryan, M. and Stahl, B. C. (2020). Artificial intelligence ethics guidelines for developers and users: clarifying their content and normative implications. Journal of Information, Communication and Ethics in Society.

Schiff, D., Ayesh, A., Musikanski, L., and Havens, J. C. (2020a). IEEE 7010: A new standard for assessing the well-being implications of artificial intelligence. ArXiv, abs/2005.06620.

Schiff, D., Rakova, B., Ayesh, A., Fanti, A., and Lennon, M. (2020b). Principles to practices for responsible ai: Closing the gap. arXiv preprint arXiv:2006.04707.

Schleier-Smith, J. (2015). An architecture for agile machine learning in real-time applications. In Cao, L., Zhang, C., Joachims, T., Webb, G. I., Margineantu, D. D., and Williams, G., editors, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, August 10-13, 2015, pages 2059–2068. ACM.

Smit, K., Zoet, M., and van Meerten, J. (2020). A review of AI principles in practice. In Vogel, D., Shen, K. N., Ling, P. S., Hsu, C., Thong, J. Y. L., Marco, M. D., Limayem, M., and Xu, S. X., editors, 24th Pacific Asia Conference on Information Systems, PACIS 2020, Dubai, UAE, June 22-24, 2020, page 198.

Vaishnavi, V. K. and Kuechler,W. (2015). Design science research methods and patterns: innovating information and communication technology. Crc Press.

Vakkuri, V., Kemell, K., and Abrahamsson, P. (2020a). ECCOLA - a method for implementing ethically aligned AI systems. CoRR, abs/2004.08377.

Vakkuri, V., Kemell, K.-K., Kultanen, J., and Abrahamsson, P. (2020b). The current state of industrial practice in artificial intelligence ethics. IEEE Software.

Zeng, Y., Lu, E., and Huangfu, C. (2019). Linking artificial intelligence principles. ArXiv, abs/1812.04814.
CERQUEIRA, José Antonio Siqueira de; CANEDO, Edna Dias. Exploring Ethical Requirements Elicitation for Applications in the Context of AI. In: CONCURSO DE TESES E DISSERTAÇÕES EM SISTEMAS DE INFORMAÇÃO - SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 18. , 2022, Curitiba/PR. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 150-163. DOI: https://doi.org/10.5753/sbsi_estendido.2022.222269.