Towards a Business Case for AI Ethics
Abstract
The increasing integration of artificial intelligence (AI) into software engineering (SE) highlights the need to prioritize ethical considerations within management practices. This study explores the effective identification, representation, and integration of ethical requirements guided by the principles of IEEE Std 7000–2021. Collaborating with 12 Finnish SE executives on an AI project in autonomous marine transport, we employed an ethical framework to generate 253 ethical user stories (EUS), prioritizing 177 across seven key requirements: traceability, communication, data quality, access to data, privacy and data, system security, and accessibility. We incorporate these requirements into a canvas model, the ethical requirements canvas. The canvas model serves as a practical business case tool in management practices. It not only facilitates the inclusion of ethical considerations but also highlights their business value, aiding management in understanding and discussing their significance in AI-enhanced environments.
Main Authors
Format
Conferences
Conference paper
Published
2024
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202402211975Use this for linking
Parent publication ISBN
978-3-031-53226-9
Review status
Peer reviewed
ISSN
1865-1348
DOI
https://doi.org/10.1007/978-3-031-53227-6_17
Conference
International Conference on Software Business
Language
English
Published in
Lecture Notes in Business Information Processing
Is part of publication
Software Business : 14th International Conference, ICSOB 2023, Lahti, Finland, November 27–29, 2023, Proceedings
Citation
- Agbese, M., Halme, E., Mohanani, R., & Abrahamsson, P. (2024). Towards a Business Case for AI Ethics. In S. Hyrynsalmi, J. Münch, K. Smolander, & J. Melegati (Eds.), Software Business : 14th International Conference, ICSOB 2023, Lahti, Finland, November 27–29, 2023, Proceedings (pp. 231-246). Springer. Lecture Notes in Business Information Processing. https://doi.org/10.1007/978-3-031-53227-6_17
Copyright© 2024 the Authors