Generative AI and Perceived Competence Bias: Evidence from a Field Experiment

Last registered on March 23, 2026
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Pre-Trial

Trial Information

General Information

Title
Generative AI and Perceived Competence Bias: Evidence from a Field Experiment
RCT ID
AEARCTR-0018036
Initial registration date
March 19, 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
March 23, 2026, 7:51 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
Jiarui Wang
Affiliation
Boston University
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Other Primary Investigator(s)

PI Name
Raymond Fisman
PI Affiliation
Boston University
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Additional Trial Information

Status
In development
Start date
2026-04-07
End date
2026-04-08
Keywords
Behavior, Education, Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines how AI assistance affects individuals' beliefs about their own abilities. We use a randomized field experiment to estimate the causal effect of AI assistance on individuals' perceived competence and related outcomes.
External Link(s)

Registration Citation

Citation
Fisman, Raymond and Jiarui Wang. 2026. "Generative AI and Perceived Competence Bias: Evidence from a Field Experiment." AEA RCT Registry. March 23. https://doi.org/10.1257/rct.18036-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants are randomly assigned to one of three conditions: AI-assistance, human-collaboration, and control condition.
Intervention Start Date
2026-04-07
Intervention End Date
2026-04-08

Primary Outcomes

Primary Outcomes (end points)
Self-perceived competence
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We use a randomized controlled trial with three treatment arms: AI-assistance, human-collaboration, and control condition. Randomization is conducted at the cluster level. We measure impacts on self-perceived competence and related outcomes.
Experimental Design Details
Not available
Randomization Method
Computer-generated random assignment
Randomization Unit
Course section (cluster-level randomization)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
22 class sections
Sample size: planned number of observations
Around 400 students
Sample size (or number of clusters) by treatment arms
Around 130 participants per treatment 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
Boston University Charles River Campus Institutional Review Board
IRB Approval Date
2026-01-12
IRB Approval Number
8301X
Analysis Plan

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