Generative AI and Task Choice: Experimental Evidence on Task Choice and Income Gap

Last registered on June 13, 2025
View Trial History

Pre-Trial

Trial Information

General Information

Title
Generative AI and Task Choice: Experimental Evidence on Task Choice and Income Gap
RCT ID
AEARCTR-0016197
Initial registration date
June 10, 2025

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 13, 2025, 8:03 AM EDT

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

Locations

Country
Korea (Republic of)
Region
Seoul

Primary Investigator

Name
Junghyun Park
Affiliation
Seoul National University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2025-05-13
End date
2025-06-24
Keywords
Behavior, Labor
Additional Keywords
Generative AI, Task choice, Income gap, Task mismatch
JEL code(s)
J24, O33
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study investigates the causal effects of generative AI (e.g., ChatGPT) on individuals’ task choices and resulting income disparities using a randomized controlled trial (RCT) within an experimental economics framework. Participants first complete two tasks—decoding (low-skill) and programming (high-skill)—without AI assistance during the Baseline stage. In the Task Round, participants are randomly assigned to one of four groups. The control group receives no AI assistance. All three treatment groups are granted access to AI but differ in additional design features: the basic AI treatment group performs the task with AI; the information treatment group receives summary statistics of prior participants’ task choices and earnings before making their own decision; and the repeated-task group completes two consecutive task rounds with AI. The primary outcome variables include the rate of high-skilled task selection (task choice), the rate of selecting a task misaligned with one’s baseline ability (task mismatch), and the income difference between the Task Round and Baseline stages. This design allows us to disentangle the effects of AI availability, informational nudges, and repeated exposure on task selection and income inequality.
External Link(s)

Registration Citation

Citation
Park, Junghyun. 2025. "Generative AI and Task Choice: Experimental Evidence on Task Choice and Income Gap." AEA RCT Registry. June 13. https://doi.org/10.1257/rct.16197-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Participants are randomly assigned to one of four groups. One group performs tasks without AI. The remaining three treatment groups are given access to ChatGPT under different conditions: standard AI access, AI with informational support (past participants’ data), and AI with repeated task rounds. The intervention aims to examine how AI affects task choice and income inequality.
Intervention (Hidden)
After completing a baseline stage involving two tasks (decoding and programming) without AI, participants are randomly assigned to one of four groups:
Control: No AI access; complete one task round.
AI Only Treatment: ChatGPT access; complete one task round.
AI + Info Treatment: ChatGPT access and provided with statistical summaries of previous participants’ task choices and earnings before task selection.
AI + Repetition Treatment: ChatGPT access; complete two task rounds sequentially.
All participants select a task and perform it under time constraints. Main outcomes include task choice, task mismatch (relative to baseline productivity), and income differences. The intervention isolates the effects of AI exposure, informational priming, and repetition on economic decision-making.
Intervention Start Date
2025-05-13
Intervention End Date
2025-06-24

Primary Outcomes

Primary Outcomes (end points)
Task choice, Task mismatch, Income difference
Primary Outcomes (explanation)
Ability

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study uses a randomized controlled trial (RCT) to investigate how generative AI affects individuals’ task choice and income. Participants first complete two tasks without AI support in the Baseline stage. They are then randomly assigned to one of four groups: one control group (no AI) and three treatment groups with different AI conditions. All groups choose and perform a task in the Task Round. The study aims to measure task selection, task mismatch, and income difference across groups.
Experimental Design Details
The experiment consists of a Baseline stage followed by a Task Round. In the Baseline, all participants perform both a low-skill task (decoding) and a high-skill task (programming) without any AI assistance to establish individual productivity. Participants are then randomly assigned to one of four groups:
Control Group: Performs one task without AI in the Task Round.
AI Only Group: Performs one task with access to ChatGPT.
AI + Information Group: Performs one task with AI and receives summary information about prior participants’ task choices and earnings before making their own decision.
AI + Repetition Group: Performs two task rounds with AI support in both, allowing for potential learning and adaptation.
Task choices and resulting incomes are measured and compared with baseline performance to evaluate AI’s impact on task selection behavior and income inequality.
Randomization Method
Randomization was conducted using a computer-based algorithm implemented through the oTree platform.
Randomization Unit
The unit of randomization varies by treatment arm. For the control group and the AI-only treatment group, randomization was conducted at the individual level. For the information treatment group and the repetition treatment group, randomization was conducted at the session level, with all participants in a given session receiving the same treatment. This mixed randomization structure was implemented to accommodate interventions that required shared information or session-wide instructions.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
We plan to conduct 13 experimental sessions, each involving approximately 20 participants. For the AI + Information and AI + Repetition groups, treatment will be randomized at the session level, with each session constituting one cluster. In the Control and AI-only groups, randomization will occur at the individual level.
Sample size: planned number of observations
250 participants
Sample size (or number of clusters) by treatment arms
Approximately 60 participants per group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Seoul Natioanl University Institutional Review Board(IRB)
IRB Approval Date
2025-04-28
IRB Approval Number
No.2505/001-013
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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

Request Information

Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials