Experimental Design
We recruit approximately 3,000 participants aged 18–65 in the United States from Prolific, with comparison samples from other online survey platforms. Each participant completes a survey consisting of a screener and consent form, demographic questions, a battery of incentivized tasks, and a post-task section on self-reported AI use and attitudes. The task battery spans probability reasoning, beliefs and attitudes questions, open-ended summarization, and data labeling, reflecting the range of activities common in behavioral research and machine-learning data work. We cross-randomize four dimensions: base payment (high/low), bonus payment (none/low/high), prevention tools designed to discourage AI use (present/absent), and sanctions for AI use (none/moral persuasion and monetary penalty). Base payment is randomized at the study-listing level; the remaining dimensions are randomized at the individual level. To detect AI use, we combine behavioral measures (keystrokes, mouse movement, copy-paste activity, tab-switching, time on page), text-based AI detection on open-ended responses, and self-reported AI use, aggregated into pre-specified indices.