Consumer Responses to Disclosing AI Involvement in Advertising Content Creation

Last registered on January 22, 2026

Pre-Trial

Trial Information

General Information

Title
Consumer Responses to Disclosing AI Involvement in Advertising Content Creation
RCT ID
AEARCTR-0017641
Initial registration date
January 12, 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
January 22, 2026, 6:14 AM EST

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

Locations

Region

Primary Investigator

Affiliation
Peking University

Other Primary Investigator(s)

PI Affiliation
ROI Festival Foundation
PI Affiliation
Peking University

Additional Trial Information

Status
In development
Start date
2026-01-15
End date
2026-04-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study will examine: (i) whether there will be differences in the quality of advertising copy written by independent humans, through human–AI collaboration, and by independent AI; and (ii) how consumers will respond to the disclosure of AI involvement in content creation. We plan to address these questions using a two-stage experimental design. In the first stage, we will collect advertising copy for suitcase (a durable good) and package tour service (service product). Based on uniform product information and specified writing topic, we will recruit participants to write advertising copy. Participants will be randomly assigned to either an independent human writing group or a human–AI collaboration group. In independent AI Group, copies were autonomously generated by ChatGPT. In the second stage, we will recruit participants through an online survey platform to evaluate the advertising copies, either with or without disclosure of authorship. We will measure participants’ willingness to interact with the content and their willingness to purchase the product. This design will allow us to examine differences in copy quality under non-disclosure, as well as the effect of AI disclosure, distinguishing between disclosure of independent AI creation and disclosure of human–AI collaboration. Finally, we plan to explore the mechanisms underlying the disclosure effect, focusing on curiosity, AI preferences and etc.
External Link(s)

Registration Citation

Citation
He, Xinhao, Huaqing Huang and Juanjuan Meng. 2026. "Consumer Responses to Disclosing AI Involvement in Advertising Content Creation." AEA RCT Registry. January 22. https://doi.org/10.1257/rct.17641-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-01-15
Intervention End Date
2026-04-30

Primary Outcomes

Primary Outcomes (end points)
rating in the survey: including willingness to interact, willingness to purchase.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
curiosity measure and preference measure
Secondary Outcomes (explanation)
mainly for mechanism analysis

Experimental Design

Experimental Design
For Copy Writing:
Given uniform product info and specified writing topics,
Human Group:copies were independently written by employees of the company;
Human-ChatGPT Group: copies were collaboratively created by employees and ChatGPT;
ChatGPT Group: copies were autonomously generated by ChatGPT.

For Copy Rating:
the copy is presented with or without disclosure.
The wording of disclosure is:
This copy is written independently by human;
This copy is written collaboratively by humans and ChatGPT;
This copy is written independently by ChatGPT.
Experimental Design Details
Not available
Randomization Method
For people we recruit for copywriting, the randomization between "Independent Human Group" and "Human-AI Collaboration Group" is done in office by a computer.
For copy rating in survey, the participant is randomized to different version of surveys by the survey platform.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No cluster. same as below.
Sample size: planned number of observations
Copy Collection: around 100 people * 4 copies per person= around 400 copies Copy rating: 600-800 people * 6 copy rating per person =3600-4800 observations
Sample size (or number of clusters) by treatment arms
Copy collection: around 100 people, half in independent Human Writing Group; half in Human-AI Collaboration Group.
Copy rating: 600-800 people, 300-400 for undisclosed survey; 300-400 for disclosed survey.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Guanghua School of Management, Peking University
IRB Approval Date
2023-04-25
IRB Approval Number
#2023-09