Ethics principles appear in AI coding agent configuration files
Ethics by Configuration: AI Ethics Principles in Coding Agent Instructions
Software Engineering
Summary
As AI coding helpers become more common, people set up configuration files to guide how these helpers behave. The researchers looked at many such files on GitHub to see if they included ethical rules. They found that many files did include ethics-related instructions, focusing on things like accountability, privacy, and fairness. However, these rules mostly help developers and people working on the code, rather than the wider public or users.
What this means in practice
- •For software developers: Use ethics-focused configuration files to guide AI coding agents during development workflows, ensuring attention to accountability and transparency.
- •For software project maintainers: Review ethics-related instructions in configuration files to improve developer and maintainer oversight of AI coding agents.
Tested on one dataset.
Authors
Haoyu Gao, Peerachai Banyongrakkul, Marc Cheong, Christoph Treude, Sebastian Baltes, Mansooreh Zahedi
Abstract
As AI coding agents become integral to software development, projects increasingly utilise configuration files, such as context files and skills, to govern agent behaviour. While AI ethics principles are widely used in research and policy, little is known about whether and how they are reflected when developers configure coding agents. We studied ethics principles in 40,079 configuration files across 8,893 GitHub repositories. Using a validated large language model (LLM) classification, we measured the prevalence of ethics-related statements, and qualitatively analysed 702 stratified samples across 679 files to uncover the ethical considerations reflected in these files and the parties they concern. Ethics-related statements appeared in 39.4% of files and 61.5% of repositories; concentrated on accountability, transparency, privacy protection, and reliability; and occurred more often in task-specific files such as skills than in project-wide context files. Our qualitative analysis identified 30 categories of ethical considerations, which take the form of concrete rules for the agent. Accountability appeared mainly as requirements for human approval, transparency as explain and honestly report the agent's work, and fairness as accessibility and localisation. These considerations reveal a difference in focus. Whereas public ethics frameworks aim to protect society and end users, configuration files mainly concern developers, maintainers, and community members in the development workflow. Ethics-related content appeared mainly in prose-based files, and whether agents follow these instructions remains untested. We discuss the implications for practitioners, researchers, and policymakers.