用户对AI写作助手的理解方式，影响其纠错能力和最终写作质量。
From Use to Oversight: How Mental Models Influence User Behavior and Output in AI Writing Assistants
- 通过不同描述诱导用户形成功能或结构化心智模型
- 结构化模型用户理解更好但错误更多，信任过高导致疏于检查
- 适合关注人机协作中信任与控制平衡的研究者
基于AI的写作助手已广泛使用，但用户心智模型如何影响其使用行为仍不明确。本文研究两种心智模型——功能型（系统做什么）和结构型（系统如何工作）——及其对用户控制行为（请求、接受或修改建议）和写作结果的影响。在实验中，48名参与者被不同系统描述引导形成特定心智模型后，使用一个偶尔提供预设语法错误建议的写作助手完成求职信撰写任务。结果显示，结构型心智模型组虽更理解系统且认为其更易用，但产生的语法错误反而更多，表明对系统的深入理解可能因过度信任而削弱用户监督能力，揭示了在需人工纠错的场景下，理解、信任与控制之间的复杂关系。
原文摘要 · Abstract (English)
AI-based writing assistants are ubiquitous, yet little is known about how users' mental models shape their use. We examine two types of mental models -- functional or related to what the system does, and structural or related to how the system works -- and how they affect control behavior -- how users request, accept, or edit AI suggestions as they write -- and writing outcomes. We primed participants ($N = 48$) with different system descriptions to induce these mental models before asking them to complete a cover letter writing task using a writing assistant that occasionally offered preconfigured ungrammatical suggestions to test whether the mental models affected participants' critical oversight. We find that while participants in the structural mental model condition demonstrate a better understanding of the system, this can have a backfiring effect: while these participants judged the system as more usable, they also produced letters with more grammatical errors, highlighting a complex relationship between system understanding, trust, and control in contexts that require user oversight of error-prone AI outputs.
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