"AI slop", that is, low-quality AI-generated content, is increasingly affecting software development, from generated code and pull requests to documentation and bug reports. However, there is limited empirical research on how developers perceive and respond to this phenomenon. We qualitatively analyzed how developers discuss AI slop in 1{,}154 Reddit and Hacker News posts, developing a codebook of 15 codes organized into three thematic clusters: Review Friction (how AI slop burdens reviewers, erodes trust, and prompts countermeasures), Quality Degradation (damage to codebases, knowledge resources, and developer competence), and Forces and Consequences (systemic incentives, mandated adoption, craft erosion, and workforce disruption). Our findings frame AI slop as a tragedy of the commons, where individual productivity gains externalize costs onto reviewers, maintainers, and the broader community. We report the concerns developers raise and the mitigation strategies they propose, with implications for tool developers, team leads, and educators.

翻译："人工智能垃圾"（AI slop），即低质量的AI生成内容，正日益影响软件开发领域——从生成的代码、拉取请求到文档和缺陷报告。然而，关于开发者如何感知并应对这一现象的实证研究仍较为有限。我们对Reddit和Hacker News上1154条帖子中开发者讨论AI垃圾的方式进行了定性分析，构建了一个包含15个编码的编码手册，这些编码分为三个主题簇：审查摩擦（AI垃圾如何加重审查者负担、侵蚀信任并引发反制措施）、质量退化（对代码库、知识资源及开发者能力的损害），以及动因与后果（系统性激励、强制采用、工艺侵蚀与劳动力扰乱）。我们的研究将AI垃圾视为公地悲剧：个体生产力提升的成本被外部化，转嫁至审查者、维护者及更广泛的社群。我们报告了开发者提出的担忧及应对策略，并为工具开发者、团队领导者和教育者提供了启示。