Jacqueline Konkol

Papers

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About

Jacqueline Konkol is a leading researcher in human-robot interaction, with a primary focus on explainable artificial intelligence (XAI) and social robotics. Her most cited work, "Self-Explaining Social Robots: An Explainable Behavior Generation Architecture for Human-Robot Interaction" (2022, 32 citations), introduces a novel architecture that enables robots to autonomously generate transparent, understandable explanations for their actions. This contribution directly addresses the critical challenge of trust and comprehension in autonomous systems, particularly as social robots become more prevalent in everyday environments. By designing robots that can articulate their decision-making processes, Konkol helps bridge the gap between complex AI behaviors and human expectations, mitigating the unrealistic attributions users often project onto machines. Her research is pivotal for developing safer, more reliable, and user-friendly robotic companions. With her work gaining traction in the XAI and robotics communities, Konkol is establishing herself as an influential voice in making intelligent systems not only more capable but also more accountable and interpretable to the people they serve.