B U I L D

R E S E A R C H

S C A L E

B U I L D R E S E A R C H S C A L E

    Technology for Impact    

Where We Live, Work, and Learn

  • Examining and innovating scalable interventions to drive more equitable outcomes from K-12 to higher education to skills development.

  • Harnessing the potential of untapped housing datasets and conducting rigorous studies with platforms to improve housing outcomes at scale.

  • Generating evidence-based, data-driven pathways to equitable technology in hiring funnels, improved workplace retention, and economic mobility.

Where Researchers,

Data & Tech      

Collide        

In the Media

Peter Bergman of the University of Texas-Austin and Learning Collider, a social science research lab, argues that recent advancements in artificial intelligence make this the right time to create an ARPA for education.
— Ulrich Boser, Forbes
We know, for example, that there are instances where human decision-making can be biased but there’s no good way to flag it. And if you can’t flag it, you can’t address it.
— Riddhima Mishra, The Cusp
Bergman has explored ways to improve communications. In a pioneering study published in 2019, Bergman and a co-author found that sending parents weekly text messages about students’ absences and missing assignments, and a monthly warning about failing grades, improved high school students’ attendance by 12% and reduced course failures by 28%.
— Jenny Anderson, TIME

Project Highlights

Resume Evaluations in the Real-World

In the recruiting funnel of most jobs stands a single gatekeeper: a recruiter tasked with screening resumes to determine who gets an interview. We teamed up with interviewing.io - the largest interview prep platform specifically for engineers - to conduct an audit study with technical recruiters.

Who gets an interview? The Ins and Outs of Resume Evaluations

Are recruiters better than a coin flip at judging resumes? Here's the data. (interviewing.io)

Equitable Outcomes in Lending

Can we further expand access to credit for historically excluded groups of borrowers without lowering repayment rates? In partnership with Kiva U.S., we conducted a randomized experiment to expand access to credit across three dimensions of their lending model. Read about the methodology and preliminary analyses:

Part I: Fair Lending R&D

Part II: Preliminary Analyses Generate Evidence for Social Underwriting

Expanding Access to Capital in the U.S. through Data-Driven Partnership (Kiva U.S.)

Rental Market Data & Analysis

In partnership with AffordableHousing.com, we analyze housing market data and household preferences relative to tenants seeking affordable rentals or accessing public housing programs. These analyses inform policymakers at periodic White House Roundtables and are summarized on our blog:

Primer | Part 1 | Part 2 | Part 3 | Part 4 | Part 5

Explore Key Findings


Recognizing Our Supporters