AI 中文总结
通过混合方法研究448名微软开发者，发现AI自主性接受度因任务和个体而异，身份定义、面向人类和设计类工作接受度最低，而AI经验和风险容忍度高的开发者接受度更高。
AI 中文摘要
随着AI承担更多的软件工作，人类与AI努力之间的界限正在发生变化。开发者围绕AI自主性划定的界限影响着我们如何设计保留有意义工作的工具和角色。借鉴认知评价理论、工作设计和自动化研究，我们对微软的448名专业开发者进行了混合方法研究，以调查他们在软件工程工作中对AI自主性的接受水平。大多数开发者接受AI在其监督下产生工作，尽管接受的自主性在任务和个体之间存在实质性差异。对于身份定义、面向人类和设计导向的工作，接受度最低；而在具有更多AI经验和风险容忍度的开发者中，接受度更高。任务责任与允许AI代表开发者行动的可能性较低相关，而任务身份与授予AI决策自主权的可能性较低相关。任务需求则产生相反效果，增加了将决策委托给AI的意愿。我们的发现表明，对AI自主性的偏好反映了开发者如何认知地体验其工作，突出了设计有意义工作的重要考虑因素。
英文摘要
As AI takes on more software work, the line between human and AI effort is shifting. Where developers draw that line around AI autonomy bears on how we design tools and roles that preserve meaningful work. Drawing on cognitive appraisal theory, work design, and automation research, we conducted a mixed-methods study of 448 professional developers at Microsoft to investigate their accepted levels of AI autonomy across software engineering work. Most developers accepted AI producing work under their oversight, although accepted autonomy varied substantively across tasks and individuals. Acceptance was lowest for identity-defining, human-facing, and design-oriented work, and higher among developers with more AI experience and risk tolerance. Task accountability was associated with lower odds of allowing AI to act on developers' behalf, whereas task identity was associated with lower odds of granting AI decision-making autonomy. Task demands had the opposite effect, increasing willingness to delegate decision-making to AI. Our findings suggest that preferences for AI autonomy reflect how developers cognitively experience their work, highlighting important considerations for designing meaningful work.
