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Last Published August 16, 2025 06:03 PM August 17, 2025 10:03 AM
Experimental Design (Public) A sample of university students in Australia are recruited through Prolific to complete an online survey. Participants are asked to report their own use of generative AI tools, their personal attitudes toward generative AI, and their second-order beliefs. These beliefs include perceptions about their peers’ adoption of generative AI, peers’ moral attitudes toward generative AI, and employers’ attitudes toward generative AI in the labor market. Second-order beliefs are elicited by asking participants to guess the percentage of others who hold specific behaviors or views. In addition to a base payment, a small number of participants whose guesses are closest to the average values receive bonus payments. The survey concludes with basic demographic questions. In the second-stage experiment, participants will be randomly assigned in a 1:1 ratio to either a treatment or a control group. The treatment group will receive corrective information (e.g., a bar graph summarising peer generative AI usage from stage 1) before completing outcome measuring questions. The control group will not receive any such information and will proceed directly to the same outcome tasks. This random assignment is designed to estimate the effect of belief correction on generative AI-related attitudes and willingness to pay. The second-stage experiment details will be based on the results of the first stage, and this preregistration will be updated accordingly before second-stage data collection. A sample of university students in Australia are recruited through UTS Behavioural Lab to complete an online survey. Participants are asked to report their own use of generative AI tools, their personal attitudes toward generative AI, and their second-order beliefs. These beliefs include perceptions about their peers’ adoption of generative AI, peers’ moral attitudes toward generative AI, and employers’ attitudes toward generative AI in the labor market. Second-order beliefs are elicited by asking participants to guess the percentage of others who hold specific behaviors or views. In addition to a base payment, a small number of participants whose guesses are closest to the average values receive bonus payments. The survey concludes with basic demographic questions. In the second-stage experiment, participants will be randomly assigned in a 1:1 ratio to either a treatment or a control group. The treatment group will receive corrective information (e.g., a bar graph summarising peer generative AI usage from stage 1) before completing outcome measuring questions. The control group will not receive any such information and will proceed directly to the same outcome tasks. This random assignment is designed to estimate the effect of belief correction on generative AI-related attitudes and willingness to pay. The second-stage experiment details will be based on the results of the first stage, and this preregistration will be updated accordingly before second-stage data collection.
Secondary Outcomes (End Points) Other second-order beliefs: perceived moral attitudes Experience with generative AI: type of tasks, generative AI tools used, paid subscription Attitudes toward generative AI: moral attitudes, direct utility benefit (enjoyable to use), direct utility cost (difficult to use), patience with generative AI, trust in accuracy, confidence in skills, perceived benefits, concerns about using generative AI Experience with generative AI: type of tasks, tools used, paid subscription Attitudes toward generative AI: moral attitudes, perceived benefits, direct utility benefit (enjoyable to use), direct utility cost (difficult to use), trust in accuracy, confidence in skills, patience with generative AI, concerns about using GenAI
Secondary Outcomes (Explanation) We include a list experiment to test whether social desirability bias influences responses to the moral attitude question.
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