When Humans Encounter LLMs: An Experiment on Copy Writing and User Perception on Social Media

Last registered on August 04, 2024

Pre-Trial

Trial Information

General Information

Title
When Humans Encounter LLMs: An Experiment on Copy Writing and User Perception on Social Media
RCT ID
AEARCTR-0011347
Initial registration date
May 12, 2023

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 17, 2023, 2:48 PM EDT

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

Last updated
August 04, 2024, 7:53 AM EDT

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

Locations

Region

Primary Investigator

Affiliation
Peking University

Other Primary Investigator(s)

PI Affiliation
Peking University

Additional Trial Information

Status
On going
Start date
2023-05-19
End date
2024-08-30
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This study wants to explore the competition and collaboration between humans and Large Language Models(e.g. ChatGPT), as well as humans' attitudes towards LLMs. We are planning to run a randomized control trial on social media platform. Four accounts will be operated simultaneously from scratch, with the copywriting for three of the accounts being generated separately by humans, LLMs, and human-AI collaboration. The copy for the other account will be randomly selected from those generated by LLMs or human-AI collaboration, but we will indicate at the beginning of the post that the copy was generated or co-generated by LLMs. Afterwards, we will allocate traffic to the four accounts and observe the views, likes, reposts and comments acquired by the accounts. We also plan to conduct a similiar survey experiment, where copies are presented for participants to rate without or with the labeling of the writer. The distinction of survey from Weibo is that attention is more abundant and individul-data is collected. We will examine (1) In the context of copywriting, who will gain more traffic and perform better: humans, LLMs, or human-AI collaboration?(2) Compared to copywriting produced by humans, will social media users have different attitudes towards copywriting generated or co-generated by LLMs? (3) For people who cooperate with LLMs to write copywriting, will they adopt more LLMs later in their work? What is the effect of LLMs adoption on performance?

External Link(s)

Registration Citation

Citation
Huang, Huaqing and Juanjuan Meng. 2024. "When Humans Encounter LLMs: An Experiment on Copy Writing and User Perception on Social Media." AEA RCT Registry. August 04. https://doi.org/10.1257/rct.11347-3.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-05-22
Intervention End Date
2024-08-30

Primary Outcomes

Primary Outcomes (end points)
Weibo Experiment:
-consumer: the number of views, likes, reposts and comments for each post; the number of growing fans for each account; the number of purchasing if the post attaches a purchasing link;
- employee(writer): humans' perceptions and attitudes towards LLMs; the adoption of LLMs; the performance before and after the adoption of LLMs.

Survey Experiment: the scores given to each post
Primary Outcomes (explanation)
Weibo Experiment
-employee: their perceptions and attitudes towards LLMs will be elicited from surveys.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Weibo Experiment:
Each group corresponds to one social media account, and four accounts will be operated simultaneously from scratch.
- Pure Human Group: Humans generate copywriting independently.
- Pure AI Group: LLMs generate copywriting independently.
- Human-AI Collaboration Group: There is no specific limitation on the collaboration method. It can be multiple rounds of interaction between humans and LLMs, or humans modifying the copywriting generated by LLMs.
- Labeled Group: Randomly select copywriting from the Pure AI Group and Human-AI Collaboration Group for posting. When posting, indicate at the beginning that "This copywriting is generated by LLMs" or "This copywriting is co-generated by humans and LLMs".

These four accounts will be used to promote the same brand and product managed by a company. We plan to recruit employees from this company to generate or co-generate copywritings at the designated time and place. There will be "an initial questionnaire" to collect the basic information of these employees and especially to survey their usage of LLMs and other AI tools. "A following questionnaire" will be released two weeks after the copywriting generation and survey their later adoption and usage of LLMs. We will combine it with their performance evaluation data from the company to analyze the productivity effect of LLMs.

Among all the copywritings, part of them will be paired with product image or purchase link or both. We will then send these posts and allocate traffic for them. We will purchase the same exposure number for each post and observe the final number of views, likes, shares, and comments data. A questionnaire for social media users to survey their perceptions and attitudes towards these posts will be released through the four accounts when the experiment is finished.

Survey Experiment 1, 2 (Labeled or not)*3(present copies written by human, AI or human-AI collaboration) between-individual design:
Each participant are asked to rate three randomly chosen copies written by human/AI/human-AI collaboration, without or with the disclosure of the writer.

Survey Experiment 2, 2 (Labeled or not, this dimension is between-individual)*3(present copies written by human, AI or human-AI collaboration, this dimension is within-individual) design: Each participant are asked to rate copies without or with the disclosure. Each participant will be presented copies written by human, AI or human-AI collaboration simultaneously.
Experimental Design Details
Randomization Method
For people we recruit to write copywriting, the randomization between "Pure Human Group" and "Human-AI Collaboration Group" is done in office by a computer.
For copy release on Weibo, the consumer is allocated to see posts by Weibo platform.
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
Weibo experiment: 150 individuals for copy writing, with each individual generate or co-generate two posts; another 300 posts are generated by LLMs or randomly selected from the existing posts. 600 posts in total. The number of planned exposure we purchase for each post is 10000-20000 users. 6000000-12000000 social media users exposed to copywritings for the above four accounts in total. survey experiment 1: Each participant rates three copies, 300-500 participants per treatment, 1800-3000participants in total. Survey Experiment 2: Each participant rates 4-6 copies, 250 participants per treatment, 500 participants in total.
Sample size (or number of clusters) by treatment arms
Weibo experiment:
150 posts generated by humans independently; 150 posts generated by LLMs independently; 150 posts generated by human-AI collaboration; 150 posts randomly selected from posts generated/co-generated by LLMs and labeled "generated/ cogenerated by LLMs".
1500000-3000000 users exposed to copywritings for each account.

Survey experiment 1:
Each participant rates three copies, 300-500 participants per treatment; Each copy is rated by 7-11 participants on average.

Survey experiment 2:
Each participant rates 4-6 copies, 250 participants per treatment; Each copy is rated by 7-9 participants on average.
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

Post-Trial

Post Trial Information

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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