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Field
Last Published
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Before
March 21, 2025 12:48 AM
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After
March 27, 2025 10:38 AM
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Field
Intervention (Public)
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Before
Individuals make a decision to determine how a private lender allocate a $10000-loan. Participants are randomized into a neutral treatment where payoffs are not tied to actual loan repayment outcome, or a "lender-aligned" treatment where they have with direct stakes tied to loan repayment.
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After
Individuals make a decision to determine how a private lender allocate a $10000-loan. Participants are randomized into a neutral treatment where payoffs are not tied to actual loan repayment outcome, or a "lender-aligned" treatment where they have with direct stakes tied to loan repayment.
The actual date of the experiment will be pre-registered here before launch.
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Field
Primary Outcomes (End Points)
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Before
(1) Binary decision of whether the participant want to see an explanation of how the AI made the prediction of the default risk of the borrowers before making a loan allocation decision
(2) Binary decision of whether the participant want to see the predicted default risk of the borrowers before making a loan allocation decision
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After
(1) Binary decision of whether the participant want to see an explanation of how the AI made the prediction of the default risk of the borrowers before making a loan allocation decision
** The full set of outcome variables that we intend to analyze is listed in the stata do file attached to this experiment before the experiment itself; besides those tables, we plan to present the word cloud formed by the responses to the question “You chose to see an explanation of how the AI Algorithm made the default risk predictions BEFORE making the loan decision, what were you hoping to learn from the explanation?”, among the participants who was presented and taken up the option to review an explanation where the chance to see the role race and gender play in the default risk calculation by the AI is made salient
(2) Binary decision of whether the participant want to see the predicted default risk of the borrowers before making a loan allocation decision
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Field
Planned Number of Observations
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Before
3,000
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After
2,000
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Field
Sample size (or number of clusters) by treatment arms
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Before
Evenly for non-lender-aligned and for lender-aligned for main arm. Same shares for a variant of the main arm where race-gender descriptors for borrowers are replaced by odd/even number birth-day/month. Main arm, in particular active choice of whether to see explanation will be 3X sampled relative to other arms in this group.
1/3 as much as above, but within this even between non-lender-aligned and lender-aligned for an arm similar to main arm except that participants also have a choice to see the predicted default risk generated by AI or not. Same numbers for a variant of the main arm where race-gender descriptors for borrowers are replaced by odd/even number birth-day/month.
3000 in total.
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After
Evenly for non-lender-aligned and for lender-aligned for main arm. 1000 each.
3/4 will be in the arms where they choose whether or not to see the explanation: Same shares for a variant of the main arm where race-gender descriptors for borrowers are replaced by odd/even number birth-day/month. (total 1500 across these arms)
1/4 as much as above, but within this even between non-lender-aligned and lender-aligned for an arm similar to main arm except that participants have a choice to see the predicted default risk generated by AI or not. These participants will be randomized to see an explanation. (total 500)
2000 in total.
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