Healthy Friction in Job Recommender Systems

Host Kyle Polich interviews Roan Schellingerhout, a PhD student researching explainable AI-powered job matching systems that balance the needs of job seekers, recruiters, and companies, with findings showing that users strongly prefer simple textual explanations over technical visualizations. The conversation covers the technical architecture using knowledge graphs and large language models, ongoing research into fairness considerations, and Roan's vision for AI systems that support rather than replace human recruiters in making the job search process less grueling.

Guest

Roan Schellingerhout: Hi there 👋 I’m Roan, a PhD student at Maastricht University supervised by Nava Tintarev and Francesco Barile.