AI Assistance, Social Preferences, and Beliefs in Economic Games

Last registered on July 23, 2026
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Pre-Trial

Trial Information

General Information

Title
AI Assistance, Social Preferences, and Beliefs in Economic Games
RCT ID
AEARCTR-0019198
Initial registration date
July 17, 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
July 23, 2026, 8:01 AM EDT

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

Locations

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Primary Investigator

Name
Xin Jiang
Affiliation
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Other Primary Investigator(s)

PI Name
Bohan Ye
PI Affiliation
University of California, Riverside
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Additional Trial Information

Status
In development
Start date
2026-09-21
End date
2026-12-31
Keywords
Behavior
Additional Keywords
Artificial intelligence; economic games; dictator game; trust game; public goods; beliefs; social preferences
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines whether access to AI assistance changes human decisions, beliefs, and reasoning in canonical economic games. Participants complete dictator-game, trust-game, and public-goods decisions first without AI assistance and then with the option to consult an AI assistant. The main analysis compares matched within-subject decisions across the no-AI and AI-assist conditions, with secondary analyses of belief revision, heterogeneity by baseline beliefs and reasons, and the content of AI prompts.
External Link(s)

Registration Citation

Citation
Jiang, Xin and Bohan Ye. 2026. "AI Assistance, Social Preferences, and Beliefs in Economic Games." AEA RCT Registry. July 23. https://doi.org/10.1257/rct.19198-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants in the AI-assist condition are allowed to consult an AI assistant before submitting decisions in the dictator game, trust game, and public-goods game. The interface asks participants to record the prompt they gave to the AI assistant and the AI response. Participants may choose not to use AI assistance. In the no-AI condition, participants complete the same economic-game decisions without AI assistance.
Intervention Start Date
2026-09-23
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
Dictator-game giving
Amount given to Player B in the dictator game.


Trust-game sending
Amount sent by Player A to Player B in the trust game.


Trust-game returning
Mean return share in the trust game, calculated for each participant as the average of returned amount divided by received amount across all nonzero received amounts.


Public-goods contribution
Amount contributed to the group project.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary outcomes include expected average public-goods contribution by others, trust-game expectations when collected, changes in beliefs between conditions, AI prompt use, AI prompt categories, and AI response content.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study uses a two-arm sequence design. In both arms, participants first complete the same set of economic-game tasks without AI assistance. Participants are then assigned to one of two second-wave conditions.

In the control arm, participants complete the tasks again without AI assistance: no AI -> no AI. In the AI-assist arm, participants complete the tasks again with access to AI assistance: no AI -> AI.
The economic-game tasks include a dictator game, a trust game, and a public-goods game. Participants are matched across the two waves using a study identifier.
Experimental Design Details
Not available
Randomization Method
randomization done by a computer
Randomization Unit
No clustered treatment assignment is planned. The unit of observation is the individual participant.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
We plan to recruit approximately 500-600 participants total
Sample size (or number of clusters) by treatment arms
We plan to recruit 150-200 participants to the no AI -> no AI control sequence and 300-400 participants to the no AI -> AI treatment sequence.
This unequal allocation reflects expected implementation capacity and the study’s interest in measuring heterogeneity and mechanisms within the AI-assist condition. The primary treatment effect will compare the Wave 1 to Wave 2 change in the AI-assist arm with the corresponding change in the control arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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