five

Ethical Requirements in the Age of Artificial Intelligence - Supplementary material

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://zenodo.org/record/14170192
下载链接
链接失效反馈
官方服务:
资源简介:
Context: Software developers and users are growing concerned about the ethical use of software, especially with Artificial Intelligence (AI). In this context, we investigated how ethical requirements can be elicited and incorporated into software development. Problem: The challenge is identifying and defining effective methods for eliciting and managing ethical requirements in software development. Solution: We conducted a Systematic Literature Review (SLR) to identify techniques, methods, processes, frameworks, and tools for eliciting, analyzing, and specifying ethical requirements. IS Theory: We explore the application of theories related to requirements engineering, ethics in technology, and data governance. It focuses, in particular, on ensuring that information systems comply with ethical and legal principles from the beginning of the development cycle. Method: Following the Kitchenham and Charters protocol, we conducted an SLR with stages of planning, conducting, and reporting the results. Summarization of Results: We have identified 47 primary studies. These studies address different approaches to eliciting ethical requirements, including techniques based on user stories, analysis of ethical guidelines, specific frameworks such as ECCOLA, and methods such as interviews and modeling. Contributions and Impact on the IS area: The report contributes to the field by consolidating existing practices in the literature regarding ethical requirements. It provides a comprehensive overview of the techniques and tools available for integrating ethical considerations into software systems and identifies gaps and opportunities for future research. The study significantly impacts the IS field by providing practical and theoretical guidelines for eliciting ethical requirements in information systems. Supplementary material of SLR.
创建时间:
2025-02-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作