Using AI in Small-loan Mediation: A Field Experiment

Last registered on December 09, 2024
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Pre-Trial

Trial Information

General Information

Title
Using AI in Small-loan Mediation: A Field Experiment
RCT ID
AEARCTR-0014962
Initial registration date
December 04, 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
December 09, 2024, 4:51 PM EST

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

Locations

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Primary Investigator

Name
Zhitao Huang
Affiliation
The University of Hongkong
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Zhuang Liu
PI Affiliation
The University of Hong Kong
PI Name
Yingmao Tang
PI Affiliation
Fudan University

Additional Trial Information

Status
In development
Start date
2024-12-15
End date
2025-05-31
Keywords
Behavior
Additional Keywords
Artificial Intelligence, Legal Technology, Settlement
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Settlement through mediation is a crucial mechanism for dispute resolution. However, the effectiveness of mediation can vary significantly based on case characteristics. This study develops an artificial intelligence (AI) model that predicts mediation success probability in small-loan disputes. We plan to conduct a field experiment in collaboration with a mediation center in China, investigating whether and how the use of AI predictions influences mediation behavior and mediation results. AI predictions of mediation success probability will be introduced in the treatment group.
This research contributes to the growing literature on AI’s applications in the judicial settings and provides empirical evidence on how predictive analytics can affect dispute resolution.
External Link(s)

Registration Citation

Citation
Huang, Zhitao, Zhuang Liu and Yingmao Tang. 2024. "Using AI in Small-loan Mediation: A Field Experiment." AEA RCT Registry. December 09. https://doi.org/10.1257/rct.14962-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The treatment consists of providing mediators with AI-generated predictions of mediation success probability. Before each mediation session, cases in the treatment group will include a report showing the AI-predicted likelihood of reaching a settlement.
Intervention Start Date
2024-12-31
Intervention End Date
2025-03-31

Primary Outcomes

Primary Outcomes (end points)
Whether the use of AI prediction influences:
1. Average time spent on mediation
2. Number of mediation sessions per case
3. Settlement rate
4. Collection of debt
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Random introduction of AI prediction to half of the mediation cases. These cases will involve loan defaults with amounts typically below $10,000, representing common small-loan disputes.
Experimental Design Details
Not available
Randomization Method
Fully Randomized at the case level by a computer.
Randomization Unit
Case level
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
5000 cases
Sample size: planned number of observations
5000 cases
Sample size (or number of clusters) by treatment arms
Treatment arm: 2500 cases
Control arm: 2500 cases
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The University of Hong Kong
IRB Approval Date
2024-02-04
IRB Approval Number
EA240192
Analysis Plan