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Knowledge about Artificial Intelligence (AI) and appraisal ratings: How people assess AI-generated images.
Last registered on November 26, 2019

Pre-Trial

Trial Information
General Information
Title
Knowledge about Artificial Intelligence (AI) and appraisal ratings: How people assess AI-generated images.
RCT ID
AEARCTR-0005065
Initial registration date
November 26, 2019
Last updated
November 26, 2019 10:50 AM EST
Location(s)

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Request Information
Primary Investigator
Affiliation
Other Primary Investigator(s)
PI Affiliation
PI Affiliation
Additional Trial Information
Status
In development
Start date
2019-10-10
End date
2020-03-31
Secondary IDs
Abstract
Through an online experiment on Amazon's Mechanical Turk, we examine how people assess images generated by artificial intelligence (AI) in order to gain more insights into how people perceive AI. By using three different information sets at the beginning of the survey, subjects are confronted with images generated by AI and rate them according to liking, emotion, creativity, and hypothetical willingness to pay. Finally, the evaluations of the AI-generated images of the treatment groups will be compared with a control group that receives no information.
External Link(s)
Registration Citation
Citation
Hauser, David et al. 2019. "Knowledge about Artificial Intelligence (AI) and appraisal ratings: How people assess AI-generated images.." AEA RCT Registry. November 26. https://doi.org/10.1257/rct.5065-1.1.
Experimental Details
Interventions
Intervention(s)
In a between-subject design, participants are asked to rate six images all created by artificial intelligence (AI) regarding liking, emotion, creativity, and hypothetical willingness to pay. We aim to examine whether subjects assess images generated by an AI differently when subjects:
i.) have no information how an image was created;
ii.) know that an image was created by an AI;
iii.) know that an image was created by an AI and also receive basic information about how the AI creates an image;
iv.) know that an image was created by an AI and also receive information about the person and team who programmed the AI.
Intervention Start Date
2019-11-26
Intervention End Date
2019-12-03
Primary Outcomes
Primary Outcomes (end points)
- Evaluation of the general liking of the images on a scale from 0 to 100.
- Evaluations about experienced emotions, whether the subject experienced that the picture is communicating with him/her and the creativity and of the images on a 7-point Likert scale.
- Hypothetical willingness to pay for the images.
- Basic demographical metadata.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Between-subject design.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer.
Randomization Unit
Individual.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
0.
Sample size: planned number of observations
In total around 560 participants.
Sample size (or number of clusters) by treatment arms
Around 140 participants per treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Ethikkommission
IRB Approval Date
2019-11-25
IRB Approval Number
142019