Laws, Ethics, and Fairness in Software Engineering
Software engineering in the era of generative AI, large data sets and superfast pace of software development often tends to focus on technology, tools and methods, putting aside us, software engineers. In this column, we focus on softer aspects of software engineering and report from two conferences: 28th International Conference on Evaluation and Assessment in Software Engineering (EASE 2024) and 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2024). The selection of papers provides a glimpse on handling privacy, documenting ethical considerations in AI models and trustworthy AI.
Authors
- Jennifer Horkoff (ORCID: https://orcid.org/0000-0002-2019-5277)
- Alexander Serebrenik (ORCID: https://orcid.org/0000-0002-1418-0095)
- Silvia Abrahão (ORCID: https://orcid.org/0000-0003-3580-2014)
- Miroslaw Staron (ORCID: https://orcid.org/0000-0002-9052-0864)
- Birgit Penzenstadler (ORCID: https://orcid.org/0000-0002-5771-0455)
- Chetan Honnenahalli (ORCID: https://orcid.org/0009-0007-9120-5587)
Institutions
- Menlo School (US)
- Chalmers University of Technology (SE)
- Eindhoven University of Technology (NL)
- University of Gothenburg (SE)
Publication Details
- Journal
- IEEE Software
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1109/ms.2024.3469488
- Citations
- 4
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 2.10