AI Washing Inflates Expected Performance but Not Interaction Outcomes: An AI Placebo Study Using Fitts' Law
Journal
ACM Conference on Fairness, Accountability, and Transparency (FAccT '26)
Type
conference contribution
Date Issued
2026-06-27
Author(s)
Abstract
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 withinsubjects 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.
Keywords
Artificial Intelligence
Human-Centered AI
Placebo Effect
AI Washing
Deceptive Marketing
Input Devices
Fitts' Law
Computer Mouse
Usability
Workload
Measurement
HSG Classification
not classified
Refereed
Yes
Publisher
Association of computing macheiner
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
AI_Placebo_Fitts_Law___Facct2026___Preprint.pdf
Size
2.93 MB
Format
Adobe PDF
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