Are People Blaming A.I. More or Less for Incorrect Advice?

Last registered on April 02, 2024
View Trial History

Pre-Trial

Trial Information

General Information

Title
Are People Blaming A.I. More or Less for Incorrect Advice?
RCT ID
AEARCTR-0013277
Initial registration date
April 01, 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
April 02, 2024, 12:49 PM EDT

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Martin Abel
Affiliation
Middlebury College
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Anh Nguyen
PI Affiliation
Bowdoin College
Contact Investigator

Additional Trial Information

Status
In development
Start date
2024-04-02
End date
2025-04-01
Keywords
Behavior, Finance & Microfinance
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This research investigates the impact of the advisor's identity—human versus artificial intelligence (AI)—on trust and blame allocation following incorrect advice. Advisors give advice on projects and recommend whether participants should or should not invest. Participants may or may not follow this advice and could potentially change their behavior toward their assigned advisor in round two by trusting and being influenced more or less by the advisor’s advice. We randomly assign participants to one of five types of advisors: i) human advisors, ii) AI advisors, iii) AI advisors combined with a short informational video on AI, iv) anthropomorphized AI (female), or v) anthropomorphized AI (female).
External Link(s)

Registration Citation

Citation
Abel, Martin and Anh Nguyen. 2024. "Are People Blaming A.I. More or Less for Incorrect Advice?." AEA RCT Registry. April 02. https://doi.org/10.1257/rct.13277-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-04-02
Intervention End Date
2024-04-23

Primary Outcomes

Primary Outcomes (end points)
Investment, beliefs of investment success, attention (More details provided in PAP. )
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomly assign participants to one of five types of advisors: i) human advisors, ii) AI advisors, iii) AI advisors combined with a short informational video on AI, iv) anthropomorphized AI (female), or v) anthropomorphized AI (female). We measure primary outcomes and how they vary in the second round (depending on whether previous advice was correct or not). In addition, we conduct a survey to learn more about the reason why people may trust different advisors. More details provided in PAP.
Experimental Design Details
Not available
Randomization Method
Done by Qualtrics.
Randomization Unit
Participant (investor) level
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1,300 participants
Sample size: planned number of observations
Two outcomes per participant, i.e. 2,600.
Sample size (or number of clusters) by treatment arms
Human: 1/3
AI only: 1/6
AI + info: 1/6
AI female: 1/6
AI male: 1/6
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Bowdoin College
IRB Approval Date
2024-03-20
IRB Approval Number
2024-19
Analysis Plan

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information