AI and Online Interactions

Last registered on April 30, 2025
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Pre-Trial

Trial Information

General Information

Title
AI and Online Interactions
RCT ID
AEARCTR-0013548
Initial registration date
May 02, 2024

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
May 13, 2024, 11:51 AM EDT

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

Last updated
April 30, 2025, 5:48 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
Switzerland
Region

Primary Investigator

Name
Lena Song
Affiliation
UIUC
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Other Primary Investigator(s)

PI Name
Elliott Ash
PI Affiliation
ETH Zurich
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PI Name
Yichuan Lou
PI Affiliation
University of Tokyo
Contact Investigator

Additional Trial Information

Status
In development
Start date
2025-04-30
End date
2025-12-31
Keywords
Behavior
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study explore the impact of AI agents on online communication. We vary the presence of these entities and examine its effects on online interactions.
External Link(s)

Registration Citation

Citation
Ash, Elliott, Yichuan Lou and Lena Song. 2025. "AI and Online Interactions ." AEA RCT Registry. April 30. https://doi.org/10.1257/rct.13548-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2025-04-30
Intervention End Date
2025-12-31

Primary Outcomes

Primary Outcomes (end points)
Effort in engagement, valuation of having content shared with others
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will run an online survey experiment to look at the effect of the presence of AI agents.
Experimental Design Details
We will administer an online survey experiment. In the first section, we gather demographic data, baseline beliefs and attitudes, and ask about social media usage. Next, participants have the option to enter a lottery that donates to a cause of their choosing.

In the second section, participants read and classify different submissions as AI or human-generated. We also assess attitudes towards AI and bots in everyday life. Participants with Instagram are asked to provide their handle.

In the third section, participants are asked to submit text responses to a writing task prompts. They are told that the response will be added to a database in a follow-up online survey, where there is a chance that the a participant of the follow-up survey will read the response.

The main treatment is whether participants' messages enter a pool of exclusively human messages or a mixed pool of both human and AI messages. This allows us to study whether people write different in the presence of AI.

To manipulate the strength of the signaling motive, we will independently randomize participants into having their identity shared vs. not with equal probability. If the participant is in the identified condition and chooses to provide their Instagram handle and complete the writing task, they are informed that their Instagram handle could be shared along with their first name in the response shared in the follow-up survey. In the control condition, participants are informed that the post will be shared without their information.

In both conditions, after submitting their post, participants have the option to forfeit a portion of their payment in exchange for having their post removed from the pool of shareable content. They are asked to bid an amount they would be willing to give to remove their post. This allows us to explore how the pool's composition affects participants' willingness to pay for removing their post.
Randomization Method
in-survey randomization on qualtrics
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1000 participants
Sample size: planned number of observations
1000 participants
Sample size (or number of clusters) by treatment arms
Participants randomized with equal probability into each 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
UIUC
IRB Approval Date
2025-04-17
IRB Approval Number
IRB24-0588
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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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