UMBC CSEE students win CSCW 2026 Best Paper Award for research on AI interviewers

UMBC CSEE researchers Md Nazmus Sakib, Naga Manogna Rayasam, and Dr. Sanorita Dey have received a Best Paper Award at the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2026). Their paper, “Expecting Too Much, Getting Too Little: Exploring the Challenges and Design Opportunities of Asynchronous AI Interviewers,” was selected through a highly competitive process in which no more than 1% of submissions receive the honor. The team will present the work at CSCW 2026 in Salt Lake City, Utah.

The paper examines a growing part of the hiring process: one-way, asynchronous interviews in which applicants record responses for evaluation through AI-assisted systems. Drawing on more than 18,000 Reddit posts, comments, and replies from 11 communities, along with interviews with 17 people who had experienced AI-driven interviews, the researchers found a striking gap between what applicants expected and what these systems delivered. Many encountered rigid and impersonal tools that offered little transparency or acknowledgment, leaving them feeling as though they were performing for a machine rather than participating in a meaningful interview. These concerns were particularly significant for neurodivergent applicants and others whose communication styles might not align with the system’s expectations.

Building on these findings, the team developed and evaluated alternative interview features with 180 participants. The study found that giving applicants the ability to edit transcribed responses improved their sense of control and helped them express themselves more effectively. Carefully designed feedback also helped participants feel more confident and acknowledged. The research shows that AI-assisted hiring should do more than make recruitment efficient—it should also protect applicant agency, support authentic self-presentation, and create a more transparent, inclusive, and human-centered experience.