AI Beliefs and Policy Preferences

Last registered on June 18, 2026
View Trial History

Pre-Trial

Trial Information

General Information

Title
AI Beliefs and Policy Preferences
RCT ID
AEARCTR-0018927
Initial registration date
June 13, 2026

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
June 18, 2026, 9:27 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Marcel Preuss
Affiliation
Cornell University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Nicolas Bottan
PI Affiliation
Cornell University
Contact Investigator

Additional Trial Information

Status
In development
Start date
2026-06-16
End date
2026-06-27
Keywords
Education, Labor
Additional Keywords
Inequality, AI
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Rapid advancements in Artificial Intelligence (AI) have sparked public debate regarding its impact on labor markets, inequality, and social mobility. The goal of this study is to understand whether economic literacy affects people's attitudes, beliefs, and policy preferences regarding those topics.
External Link(s)

Registration Citation

Citation
Bottan, Nicolas and Marcel Preuss. 2026. "AI Beliefs and Policy Preferences." AEA RCT Registry. June 18. https://doi.org/10.1257/rct.18927-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-06-16
Intervention End Date
2026-06-27

Primary Outcomes

Primary Outcomes (end points)
Labor Market Expectations index
Macroeconomic Beliefs (Income) index
Personal Expectations index
General Redistribution Policy index
AI-Specific Regulation index
Wealth Inequality and Capital Taxation index
Behavioral: upskilling opt-in (binary)
Open-text: topic indicators
Open-text: sentiment
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This survey experiment uses a 3 × 2 × 2 between-subjects factorial design. Participants are independently randomized into one of three video conditions, one of two capital information conditions, and one of two AI salience prompt conditions.
Experimental Design Details
Not available
Randomization Method
Each of the three treatment factors is randomized independently and with equal probability by the Qualtrics survey platform at its corresponding point in the survey flow, rather than all at the outset.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
NA
Sample size: planned number of observations
1500 survey participants
Sample size (or number of clusters) by treatment arms
250 per main treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information
IRB

Institutional Review Boards (IRBs)

IRB Name
Cornell Office of Research Integrity and Assurance
IRB Approval Date
2026-06-04
IRB Approval Number
IRB0148072
Analysis Plan

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information