TRACE：用计算机科学原则治理 AI 辅助研究
TRACE: Governing AI-Assisted Research with Principles from Computer Science
研究者从软件工程与安全研究中提炼出 TRACE 五项原则——记录追踪、对照来源审查、独立验收、控制交接、评估修正，用于在 AI 辅助研究中保持人类控制。配套开源系统 TRACE-OS 通过共享指令、工具和记录把原则落到现有工作流中，帮助团队按人类注意力而非 AI 产出速度安排工作。论文共 27 页、7 张表，尚未完成同行评审。
arXiv:2610.24035v1 Announce Type: cross Abstract: Artificial intelligence (AI) makes it easier than ever to produce research outputs. The pressing question is how researchers should organize their work with this technology. The question is not new: software engineering and security research have long studied how teams of people and machines keep control of a shared body of work with many contributors. We distil principles from the practices these literatures report and transpose them to AI-assisted research. The principles form TRACE: Track records, Review against sources, Accept independently, Control transitions, and Evaluate corrections. Together, the five principles give researchers a common basis for remaining in control while integrating AI into their workflows. By bounding units of work and attending to how each is shaped, they help researchers pace AI-assisted work to human attention rather than to the speed at which AI produces content. We also introduce TRACE-OS, an open source operating system for AI-assisted research projects. It puts the principles into practice through shared instructions, tools, and records that fit researchers' existing workflows. The shared standard can contribute to building trust, which allows teams to delegate and realize the productivity that AI promises. More broadly, we aim to open a conversation about the governing principles through which the research community can benefit from AI.
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来源：arXiv · Human-Computer Interaction · arxiv.org