AI and Labour Market Expectations: an Experimental Study

Last registered on November 01, 2023

Pre-Trial

Trial Information

General Information

Title
AI and Labour Market Expectations: an Experimental Study
RCT ID
AEARCTR-0012339
Initial registration date
October 30, 2023

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
November 01, 2023, 4:28 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
Maastricht University

Other Primary Investigator(s)

PI Affiliation
Maastricht University
PI Affiliation
Maastricht University; Dongbei University of Finance and Economics

Additional Trial Information

Status
In development
Start date
2024-02-01
End date
2024-06-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project is a experimental study that explores the changes of labor market expectations of students when given information intervention. It aims to answer the following research question:

Whether and how does the information intervention (introducing AI technology, particularly Large Language Model (LLM), e.g. ChatGPT) affect vocational post-secondary students’ career choice and labor market expectations.
External Link(s)

Registration Citation

Citation
Yang, Tianyu, Xinxin Zhu and Ziyue Zhu. 2023. "AI and Labour Market Expectations: an Experimental Study." AEA RCT Registry. November 01. https://doi.org/10.1257/rct.12339-1.0
Experimental Details

Interventions

Intervention(s)
We will conduct a randomized controlled trial in a field context. The interventions are delivered in video format. Students will be randomly assigned into groups presented with videos which contain positive, negative, neutral information regarding LLM, and information not related to AI, respectively. The information we use is retrieved from scientific articles and reliable sources.
Intervention Start Date
2024-02-01
Intervention End Date
2024-06-30

Primary Outcomes

Primary Outcomes (end points)
the career choice of the students: the probability of choosing a digital(AI)-intense career path or not. The probability is measured on a scale from 1 to 100.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
(1) wage expectations (own and others)
(2) belief towards the labour market
(3) belief towards self ability
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This is a randomized controlled trial. We will determine whether participants randomized to the group treated with positive/negative information regarding AI tools tended to choose/avoid occupations involved AI within a sample of vocational post-secondary students. Additionally, we will explore the mechanisms through different channels.

We will track research participants’ (1) realized internship choices; and (2) realized occupational choices after graduation.
Experimental Design Details
Experimental design
The basic procedure
The experimental design encompasses four distinct phases, including the pre-intervention assessment, intervention, post-intervention assessment, and basic information.
During Phase 1 of the study, the initial questionnaire is distributed to the participants. The initial set of questionnaires comprises five questions, including students' career preferences, their perceptions of the availability of places in the labor market, their beliefs regarding the acquisition of new skills, their beliefs of the prevailing wage among the majority of individuals, and their personal beliefs on wages.
During Phase 2, the participants will be allocated into four groups using a random assignment method. The initial cohort will be provided with arbitrary information that is unrelated to AI/LLMs technology and will be designated as the placebo group. In the case of the second group, we implement our intervention by providing selected students neural, objective information regarding the development of LLMs. In the third group, participants will be provided with two practical examples showcasing the application of ChatGPT. Additionally, they will receive positive statements regarding the LLMs tools in the context of labor market outcomes. The information provided in group will also be provided to group 3. The final group will have same information to group 3, with the exception that the positive information will be substituted with negative information.
During Phase 3, all participants are requested to do the assessment which have descripted in Phase 1 once again and collect the post intervention results.
During Phase 4, participants will be requested to provide demographic information, including their gender, birthplace, working experience, parents' occupations, and education level, and whether their parents had experienced unemployment. Additionally, participants will be asked to provide school-related information, such as their faculties, academic majors, and academic performance. Furthermore, we also investigate participants' preferences in job selection, their willingness to invest in acquiring LLMs skills, their attitudes towards a newly proposed LLMs course, their perceptions of the extent to which LLMs will affect their chosen careers, and their prior experience with AI. Last, we will also collect participants' preferences for risk, job search time, and uncertainty.
Two incentives will be implemented in this study. First, we raffled off 10% of our total participants and who were then awarded a monetary incentive ranging from 50 to 100 CNY (equivalent to 8 to 16 Euros) for their involvement in the experiment. Second, in relation to question 4 of the questionnaires, participants will be provided with a reward of 10 CNY if their responses closely align with the actual average income.
Randomization Method
randomization done by computer program (ie. Qualtrics or Otree)
Randomization Unit
individual
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
5 faculties
Sample size: planned number of observations
2160 students
Sample size (or number of clusters) by treatment arms
540 students control, 540 students for each treatment groups
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
The Ethics Review Committee of the Laboratory of Experimental Economics, Dongbei University of Finance and Economics (LEE, DUFE)
IRB Approval Date
2023-10-16
IRB Approval Number
202301003
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials