Expectations about the support of artificial intelligence (AI) may influence interaction outcomes similar to placebos. Such expectations may result from AI washing, a practice of overstating a system's AI capabilities when actual functionality is limited. For example, some computer mice are marketed as "AI-assisted" despite lacking AI in core functions. In a within-subjects study, 28 participants completed Fitts' Law tasks with a computer mouse under three conditions: no support, supposed predictive AI support, and supposed biosignal-enhanced AI support. Objective Fitts' Law performance indicators and subjective performance expectations, perceived workload, and perceived usability were measured. Compared to baseline, participants expected significantly improved performance in placebo conditions. However, these expectations did not translate into differences in objective or subjective assessments. This paper contributes evidence that AI washing inflates user expectations without altering actual interaction outcomes, highlighting a critical transparency issue. By exposing how deceptive AI marketing can shape user expectations, we underscore the need for accountability in AI product claims. Further, we establish Fitts' Law as a rigorous methodological lens for auditing AI-labelled input devices.

翻译：对人工智能（AI）支持的预期可能像安慰剂一样影响交互效果。此类预期可能源自"AI洗白"——一种夸大系统AI能力而实际功能有限的做法。例如，部分计算机鼠标虽缺乏核心AI功能，却以"AI辅助"为卖点进行营销。本研究开展被试内实验，28名参与者使用计算机鼠标在三种条件下完成菲茨定律任务：无AI支持、假设性预测AI支持、假设性生物信号增强AI支持。实验测量了客观菲茨定律表现指标、主观表现预期、感知工作负荷及感知可用性。相较于基线条件，参与者在安慰剂条件下对表现有显著更高的预期，但这些预期并未转化为客观或主观评估上的差异。本文证明AI洗白会抬高用户预期，却无法改变实际交互效果，揭示了关键的透明度问题。通过暴露误导性AI营销如何塑造用户预期，我们强调AI产品声明需承担问责责任。此外，我们确立菲茨定律作为审计AI标注输入设备的方法论标杆。