About
Guide developed by José Antonio Siqueira de Cerqueira (https://orcid.org/0000-0002-8143-1042), advised by Prof. Dr. Edna Dias Canedo (https://orcid.org/0000-0002-2159-339X), as a result of the research in the Academic Master's Degree in the Graduate Program in Informatics (PPGI) from the University of Brasilia (UnB).
Site implemented with the support of Anayran Pinheiro de Azevedo, also advised by Edna Dias Canedo, as a requirement for the undergraduate dissertation in Computing at the University of Brasilia (UnB).
Contact:
José Antonio Siqueira de Cerqueira
jose.siqueira.cerqueira@gmail.com
Master in Informatics by the Post Graduation Program in Informatics of the University of Brasília (UnB)
Guide developer
Edna Dias Canedo
ednacanedo@unb.br
PhD in Electrical Engineering from the University of Brasília (unB)
Professor at the Department of Computer Science University of Brasília (UnB)
This Guide is initially inspired by the ECCOLA method conceived by Vakkuri et al. [1] - where we expanded and implemented the cards in a web-based system - and by the ethical principles in AI and its ethical issues identified by Ryan and Stahl [2].
The source code of the Guide is available at: https://github.com/josesiqueira/RE4AIEthicalGuide under the GNU GPLv3 license, i.e. it is a free software, so it is possible to modify functionalities, adapt the cards, and include more principles, according to the needs of the development team.
Our previous works:
1. SIQUEIRA DE CERQUEIRA, José Antonio; Dos Santos Althoff, Lucas; Santos De Almeida, Paulo; Dias Canedo, Edna. 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. 2021. p. 5240.
2. SIQUEIRA DE CERQUEIRA, José Antonio; ACCO TIVES, Heloise; DIAS CANEDO, Edna. Ethical Guidelines and Principles in the Context of Artificial Intelligence. In: XVII Brazilian Symposium on Information Systems. 2021. p. 1-8.
3. SIQUEIRA DE CERQUEIRA, José Antonio, 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
How to cite this work:
@Manual{Siqueira2021EthicsElicitationGuide,
title = {Guide for Artificial Intelligence Ethical Requirements Elicitation},
author = {Jos{\'{e}} Antonio Siqueira de Cerqueira and
Anayran Pinheiro de Azevedo and
Edna Dias Canedo},
year = 2021,
month = apr,
note = {\url{https://josesiqueira.github.io/RE4AIEthicalGuide/}}
}
References:
[1] VAKKURI, Ville; KEMELL, Kai-Kristian; ABRAHAMSSON, Pekka. ECCOLA-a method for implementing ethically aligned AI systems. In: 2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE, 2020. p. 195-204.
[2] RYAN, Mark; STAHL, Bernd Carsten. Artificial intelligence ethics guidelines for developers and users: clarifying their content and normative implications. Journal of Information, Communication and Ethics in Society, 2020.
References in the contents of the cards:
MORLEY, Jessica et al. 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, v. 26, n. 4, p. 2141-2168, 2020.
SMIT, Koen; ZOET, Martijn; VAN MEERTEN, John. A Review of AI Principles in Practice. 2020.
FJELD, Jessica et al. Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI. Berkman Klein Center Research Publication, n. 2020-1, 2020.
LESLIE, David. Understanding artificial intelligence ethics and safety: A guide for the responsible design and implementation of AI systems in the public sector. Available at SSRN 3403301, 2019.
WHITTLESTONE, Jess et al. Ethical and societal implications of algorithms, data, and artificial intelligence: a roadmap for research. London: Nuffield Foundation, 2019.
GUIZZARDI, Renata et al. Ethical requirements for ai systems. In: Canadian Conference on Artificial Intelligence. Springer, Cham, 2020. p. 251-256.
KELECHI, Anabi Hilary et al. Artificial Intelligence: An Energy Efficiency Tool for Enhanced High performance computing. Symmetry, v. 12, n. 6, p. 1029, 2020.