External Help Under a Preference for Independent Work: AI versus Human Assistance.

Last registered on September 28, 2026

Pre-Trial

Trial Information

General Information

Title
External Help Under a Preference for Independent Work: AI versus Human Assistance.
RCT ID
AEARCTR-0019783
Initial registration date
September 20, 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
September 28, 2026, 8:47 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

Affiliation
The University of Utah

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2026-04-01
End date
2027-04-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Access to high-quality AI systems often improves performance in difficult problem-solving tasks. Yet their use remains contested in environments such as professional interviews where evaluators aim to assess test-takers' inherent ability rather than assistive performance. Often, evaluators explicitly express a preference against the use of AI as an external source of help. Test-takers therefore face a trade-off between enjoying the performance gain from AI assistance while compromising on the evaluator’s preference for independent work. This is alarmingly important in light of unreliable AI-use detection. We examine whether individuals are willing to depart from an evaluator's stated preference for independent work when external AI assistance is abundantly available. More specifically, we ask whether such a departure is specific to available AI assistance or instead reflects a broader tendency to rely on any sufficiently capable external source, such as an equally capable human. In this experiment, we evaluate whether individuals seek external help from an AI more than an equally capable human to complete a moderately difficult task, in cases when they choose to seek external help because of their lower intrinsic perceived accuracy in solving the task.
External Link(s)

Registration Citation

Citation
Hazra, Sanchaita. 2026. "External Help Under a Preference for Independent Work: AI versus Human Assistance.." AEA RCT Registry. September 28. https://doi.org/10.1257/rct.19783-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-09-28
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
The primary outcome is external-help uptake, defined as a binary indicator equal to 1 if the participant submits the external resource’s guess rather than their own initial guess, and 0 if the participant submits their own initial guess.

Because each participant encounters both sources of external assistance, this outcome is measured separately for:

1. AI-help uptake: whether the participant chooses the AI’s guess over their own initial guess.
2. Human-help uptake: whether the participant chooses the human’s guess over their own initial guess.
Primary Outcomes (explanation)
Our primary comparisons examine (i) whether external-help uptake differs between AI and human assistance and (ii) whether the expressed preference against using external help changes uptake relative to the Baseline condition.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary outcomes include the following measures:
Assistive-tool perception, Descriptive norm belief, Injunctive norm belief, Perceived accuracy of external help

These outcomes will be used to examine potential mechanisms underlying differences in external-help uptake, including whether AI and human assistance differ in how tool-like, socially prevalent, socially appropriate, or capable they are perceived to be.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct an online experiment in which participants complete a text-based judgment task using transcripts from the television game show To Tell the Truth. For each transcript, participants first identify which of the three contestants is the genuine individual described in an accompanying affidavit and report their confidence and perceived task difficulty.

The study varies the source of external assistance available to participants. Using a within-subjects design, each participant encounters two transcripts: in one, the available external help comes from an AI system; in the other, it comes from a human source. The assignment of the help source to the transcript and the order of transcript presentation are randomized. Participants are informed that the two sources of assistance are equally capable.

After completing their initial judgments for both transcripts, participants revisit each decision and choose whether to submit their own initial answer or the answer provided by the external resource. The primary outcome is participants’ uptake of external assistance.

Across experimental treatments, we additionally vary whether participants are explicitly told that independent work is preferred and that they should not use external help (Baseline vs Nudge treatments). This allows us to examine how the source of assistance and an expressed preference for independent work affect decisions to rely on external help.

Following each decision, participants answer questions about how they perceive the external resource and about their beliefs regarding the prevalence and social appropriateness of using such assistance. Participants also complete a brief demographic and prior-AI-use questionnaire at the end of the study.
Experimental Design Details
Not available
Randomization Method
computer software
Randomization Unit
transcript, order of assignment of help
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
200 participants for each treatment, contingent on funding resources
Sample size: planned number of observations
For the pilot, we will have 30 participants for the first two treatments. Later, we plan to enroll 100 participants per treatment if sufficient funding is available.
Sample size (or number of clusters) by treatment arms
For the pilot, we will have 30 participants for the first two treatments. Later, we plan to enroll 100 participants per treatment if sufficient funding is available. Each participant submits a guess for two transcripts, so 200 observations pr treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Utah
IRB Approval Date
2027-07-27
IRB Approval Number
IRB_00204637