AI-powered training, soft skills, and labor market outcomes

Last registered on December 18, 2021

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Pre-Trial

Trial Information

General Information

Title

AI-powered training, soft skills, and labor market outcomes

RCT ID

AEARCTR-0007853

Initial registration date

June 20, 2021

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

June 21, 2021, 11:51 AM EDT

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

Last updated

December 18, 2021, 5:41 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

United States of America

Region

Primary Investigator

Name

Song Ma

Affiliation

Yale School of Management

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Constantine Yannelis

PI Affiliation

University of Chicago

Contact Investigator

Additional Trial Information

Status

In development

Start date

2021-07-01

End date

2022-12-31

Keywords

Behavior, Education, Firms & Productivity, Gender, Labor

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

How do communication and presentation skills impact job-finding and labor market search? Can training improve communication and presentation skills? The role of communication is vital in improving social mobility and determining economic outcomes such as job-finding and productivity, as well as determinants of managerial performance We propose to conduct an experiment to determine (1) if communication training can impact job- finding rates and (2) which aspects of communication matter most. We will conduct the experiment partnering with TalkMeUp, an AI based software company focused on communication training, as well as Goodwill.

External Link(s)

Registration Citation

Citation

Ma, Song and Constantine Yannelis. 2021. "AI-powered training, soft skills, and labor market outcomes." AEA RCT Registry. December 18. https://doi.org/10.1257/rct.7853-1.1

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Experimental Details

Interventions

Intervention(s)

We willl randomize the usage of a communications training platform, TalkMeUp. The basic experimental design would be to randomize TalkMeUp usage among individuals who are about to go into job interviews or similar settings. The individuals would be divided into two groups: a treatment and a control group. The treatment group would benefit from free usage of TalkMeUp for an extended period of time, while the control group would only have free usage for a shorter period of time.

Intervention Start Date

2021-07-01

Intervention End Date

2022-06-30

Primary Outcomes

Primary Outcomes (end points)

The labor market outcomes we will explore are time until an individual obtains a job offer, interview of job conversion rates, and salary of final job offer. We will further, if possible, collect variables such as number of interviews, interview formats (phone, video, in person, etc.), interview length, offer/not, and starting salary range to further understand the training's usefulness.

We will also collect information on pre-post communication score based on the TalkMeUp platform record and an exit survey of participants.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

We will explore heterogeneity with components of communications as recorded by the TMU software.

Secondary Outcomes (explanation)

Experimental Design

Step 1: Subjects are recruited and randomized
- We will code basic information for job seekers in partner organizations: Information collected from the application form, including age, race, gender, education, work experience, prior salary, and unemployment duration.

Step 2: Subjects receive TalkMeUp-based training conducted by partner organizations
- We will offer each treated subject free TalkMeUp (TMU) usage for the whole program in partner organizations
- The TMU platform provides communication training by offering immediate feedback to the practice talks recorded through a webcam. The platform identified areas for improvements such as eye contact, facial expression, and storytelling and tracks individuals’ improvements.
- Reminders will be sent to encourage the subjects to use the training platform

Step 3: Track labor market outcomes
The labor market outcomes we will explore are time until an individual obtains a job offer, interview of job conversion rates, and salary of final job offer. We will further, if possible, collect variables such as number of interviews, interview formats (phone, video, in person, etc.), inter-view length, offer/not, and starting salary range to further understand the training’s usefulness.

Experimental Design Details

Randomization Method

Computerized random draw.

Randomization Unit

Individuals

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1,000 individuals (we may increase or decrease this depending on funding availability)

Sample size: planned number of observations

1,000 individuals

Sample size (or number of clusters) by treatment arms

~500 treated individuals and ~500 control

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

The minimum effect size we can detect following Czibor, Jimenez-Gomez and List (2029) will be .0885 standard deviations of the outcome variable. Assuming a Bernoulli random variable, and 1000 participants in total (500 treatment) then the worst case minimum detectable effect size will be 4.4 percentage points. The worst case means equal probability of finding a job, hence the highest variance.

Supporting Documents and Materials

IRB