|
Field
Last Published
|
Before
September 17, 2024 01:52 PM
|
After
September 27, 2024 05:57 AM
|
|
Field
Intervention Start Date
|
Before
September 16, 2024
|
After
September 27, 2024
|
|
Field
Intervention End Date
|
Before
September 30, 2024
|
After
October 11, 2024
|
|
Field
Secondary Outcomes (End Points)
|
Before
For each message, we make the LLM explain its "reasoning" variable-by-variable. That is, for every variable (e.g., age), the LLM explains why the message should be appealing to somebody who is young (if the message was tailored to a young person). At the end of the survey, participants choose which aspect (if any) they find most or least convincing.
|
After
For each message, we make the LLM explain its "reasoning" variable-by-variable. That is, for every variable (e.g., age), the LLM explains why the message should be appealing to somebody who is young (if the message was tailored to a young person). At the end of the survey, participants choose which aspect (if any) they find most or least convincing. Furthermore, we ask participants at the end of the survey whether they think that an artificial intelligence, a human, or both of them authored the post together.
|
|
Field
Secondary Outcomes (Explanation)
|
Before
This question serves to understand whether the LLM's proposed reasons why the message should be convincing to a person with a certain characteristic (e.g., who is young) are agreed upon by participants who actually do have that characteristic.
|
After
The reasoning question serves to understand whether the LLM's proposed reasons why the message should be convincing to a person with a certain characteristic (e.g., who is young) are agreed upon by participants who actually do have that characteristic. The question on human vs. AI authorship serves to analyze whether personalization affects the perceived authorship.
|