Teresa Sletten

Papers

Total Citations

H-Index

About

Teresa Sletten investigates the intersection of human-robot interaction and cognitive ergonomics, with a primary focus on how autonomous systems affect human performance and decision-making. Her research critically examines the hidden costs of multimodal interfaces and adaptive autonomy, demonstrating that while robots with multiple operating modes offer expanded functionality, they paradoxically increase user stress, cognitive workload, and error rates. Her most cited work, “I’m Not in the Mode to Help” (2020), has garnered 2 citations and stands as a foundational critique of design assumptions in robotics—showing that simply adding more autonomous capabilities can degrade rather than improve human-robot collaboration. Sletten’s contributions are particularly valuable for the development of transparent, user-centered automation, where her findings inform interface designs that reduce mode confusion and support operator trust. By foregrounding the psychological and operational costs of complex robotic systems, her work has shaped emerging guidelines for safer, more intuitive human-autonomy teaming. Sletten’s research is essential reading for engineers and cognitive scientists working to build robots that truly assist rather than overwhelm their human partners.