调研50本社科期刊作者,发现社科研究者主要用生成式AI辅助写作,但信任度低且未形成使用共识。
Generative AI in Sociological Research: State of the Discipline
- 通过50本期刊作者问卷,调查真实研究场景中的生成式AI使用情况。
- 多数人用于改写、摘要、编辑和翻译,认为能省时但对输出信任度低。
- 计算与非计算学者使用差异小,未来需建立研究伦理与使用规范。
生成式人工智能(GenAI)在科研与学术中的潜力引发广泛关注。尽管社会学及相关领域已有大量关于其优势与风险的探索性研究,但多为概念验证或特定模型审计。我们对50本社会学期刊作者的调查显示,目前尚不清楚社会学家如何实际应用GenAI及其对学科未来角色的看法。研究发现,社会学家主要将GenAI用于协助写作任务,如修改、总结、编辑和翻译自身成果;受访者普遍认为其节省时间,对能力保持好奇,但并未感受到来自机构或领域的强制采纳压力。总体上,受访者对GenAI的社会与环境影响持谨慎态度,对其输出信任度较低,但多数相信其未来数年内将显著改进。计算与非计算社会学家在使用行为、态度及关切方面无显著差异,也未观察到熟悉度或使用频率带来的明显模式。研究讨论了这些发现对社会学中GenAI未来发展的影响,并强调了制定研究实践共享规范所面临的挑战。
原文摘要 · Abstract (English)
Generative artificial intelligence (GenAI) has garnered considerable attention for its potential utility in research and scholarship. A growing body of work in sociology and related fields demonstrates both the potential advantages and risks of GenAI, but these studies are largely proof-of-concept or specific audits of models and products. We know comparatively little about how sociologists actually use GenAI in their research practices and how they view its present and future role in the discipline. In this paper, we describe the current landscape of GenAI use in sociological research based on a survey of authors in 50 sociology journals. Our sample includes both computational sociologists and non-computational sociologists and their collaborators. We find that sociologists primarily use GenAI to assist with writing tasks: revising, summarizing, editing, and translating their own work. Respondents report that GenAI saves time and that they are curious about its capabilities, but they do not currently feel strong institutional or field-level pressure to adopt it. Overall, respondents are wary of GenAI's social and environmental impacts and express low levels of trust in its outputs, but many believe that GenAI tools will improve over the next several years. We do not find large differences between computational and non-computational scholars in terms of GenAI use, attitudes, and concern; nor do we find strong patterns by familiarity or frequency of use. We discuss what these findings suggest about the future of GenAI in sociology and highlight challenges for developing shared norms around its use in research practice.
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