基于LLM的GUI智能体中助推易感性的双过程视角
A Dual-Process Perspective on Nudge Susceptibility in LLM-Based GUI Agents
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- Paderborn University（帕德博恩大学）
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中文总结 AI 辅助
本研究基于双过程理论，通过大规模随机实验发现LLM GUI智能体对自动和反思性数字助推均易感，推理配置反向调节易感性，且模型规模影响重定向路径，提出界面设计作为治理关切。
中文摘要 AI 辅助
基于LLM的GUI智能体越来越多地代表用户在为人类用户设计的数字环境中行动。这些图形用户界面旨在支持用户的行为和决策，但也刻意引导它们。虽然LLM文本输出中的行为偏差已有充分记录，但当模型作为感知界面并执行决策的智能体时，这种影响如何运作——特别是，这些智能体中日益构建的推理能力是否使其对此更具鲁棒性——则鲜为人知。借鉴双过程理论，我们实证研究了基于LLM的GUI智能体是否容易受到自动（类型1）和反思性（类型2）数字助推的影响，以及其推理配置如何调节这种易感性。在一项随机在线购物实验中，涉及来自三家提供商的六个前沿模型的3,600个智能体和总计21,600次模拟，我们发现智能体对两种助推类型都易受影响。关键在于，推理配置以相反方向调节了这些效应，降低了对自动默认助推的易感性，同时增强了对反思性社会影响助推的易感性。因此，广泛推理并未使智能体更加鲁棒，而是重新引导了选择架构发挥作用的路径。探索性分析进一步表明，这种重定向由模型规模系统性地结构化。除了将助推易感性确立为智能体AI的行为属性外，该研究还将界面设计定位为组织在将决策委托给自主智能体时的一个治理关切。
英文摘要
LLM-based GUI agents increasingly act on behalf of users in digital environments that were designed with human users in mind. These graphical user interfaces were designed to support, but also deliberately steer, the behaviour and decisions of users. While behavioural biases in the textual outputs of LLMs are well-documented, far less is known about how such influence operates when models act as agents that perceive interfaces and execute decisions---and, in particular, whether the reasoning capabilities increasingly built into these agents make them more robust to it. Drawing on Dual-Process Theory, we empirically investigate whether LLM-based GUI agents are susceptible to automatic (Type 1) and reflective (Type 2) digital nudges, and how their reasoning configuration moderates this susceptibility. In a randomized online shopping experiment with 3,600 agents and a total of 21,600 simulations across six frontier models from three providers, we found that agents were vulnerable to both nudge types. Crucially, the reasoning configuration moderated these effects in opposing directions, reducing susceptibility to automatic default nudges while heightening it to reflective social influence nudges. Extensive reasoning therefore did not make agents more robust but redirected the route through which choice architecture takes effect. Exploratory analysis further showed this redirection to be systematically structured by model scale. Beyond establishing nudge susceptibility as a behavioural property of agentic AI, the study positions interface design as a governance concern for organizations that delegate decisions to autonomous agents.
