New Public Database Brings Transparency to AI Tools Used in Hiring
Artificial intelligence is increasingly shaping how people are hired, yet few understand how these systems actually work. A new project from Sloane Lab at the University of Virginia School of Data Science and College of Arts and Sciences aims to change that.
On November 6, the Talent Acquisition and Recruiting AI (TARAI) Index—a first-of-its-kind, public, interactive database—will officially launch, offering unprecedented transparency about AI tools that are used across the hiring process.
The project was developed by Mona Sloane, assistant professor of data science and media studies and Ellen Simpson, her former postdoctoral researcher at the University of Virginia School of Data Science and now a faculty member at the University of Alaska.
The TARAI Index maps more than 100 HR and recruiting technologies that use artificial intelligence to filter, rank, and evaluate job candidates.
“The TARAI Index provides a new level of transparency in the tools shaping how recruiters find and assess job candidates,” said Sloane. “By making this information public, we hope to empower recruiters, HR leaders, and policymakers to make more informed decisions about the technologies used across the hiring funnel.”
A First Step Toward AI Transparency in Hiring
Supported by Sloane’s Fellowship through the Collaboratory for Applied Data Science in Business and her research start-up fund, the TARAI Index translates technical product information into clear, comparable data. Each entry reveals what a tool automates, the claims vendors make about performance or fairness, and how clearly companies explain their use of AI.
The database draws on company product materials and more than 100 interviews with recruiters, HR professionals, and HR tech developers. Users can explore two interactive environments — one designed for practitioners, another for researchers and policymakers — to analyze trends, identify assumptions, and evaluate the clarity of AI disclosures.
Hiring technologies are now classified as ‘high risk’ in some regulations, but most existing oversight doesn’t reach into how decisions are actually automated in the tools,” Sloane explained. “Our goal is to make these systems legible and open to scrutiny for practitioners and researchers alike.”
Bridging Research and Practice
The TARAI Index is grounded in real-world recruiting practices. For HR professionals, it offers a searchable and filterable view of products across sourcing, screening, and interviewing stages, revealing where marketing promises may not align with actual functionality. For researchers and policymakers, it provides a dashboard for systemic analysis of trends in AI deployment and transparency.
The project team also included research assistants Ryan Ermovick and Michael Amadi. Roshni Raveendhran, assistant professor of business administration at the University of Virginia Darden School of Business, and Sarah Lebovitz, assistant professor of commerce at the University of Virginia McIntire School of Commerce served as faculty collaborators in the project.
“AI is becoming infrastructural to society. To make the best of it, we need better transparency about how it works in high-stakes contexts like recruiting,” said Sloane. “The TARAI Index helps us see where we are now and how we can build better systems moving forward.”
Explore the Database
The TARAI Index is available at www.tarai.org, providing open access to one of the most comprehensive resources yet for understanding how AI is shaping talent acquisition.
