Title: Human-AI Interaction Dynamics with Voice-Driven Autonomous Pilots in MEDEVAC Operations While autonomous systems advance, human involvement remains crucial in critical domains like medical evacuation, where precise human discernment is essential. In our study, we explored human-AI collaboration between an AI Pilot (AP) and a medical professional in simulated MEDEVAC situations. We recruited 22 primarily […]
Teerthaa Parakh presents her paper at the Workshop on Theory of Mind at the 34th International Joint Conference on Artificial Intelligence (IJCAI)
Transparency in AI systems has shown mixed effects on human decision-making, sometimes leading to under-reliance, other times to over-reliance. We investigate this inconsistency through the lens of users’ mental models: internal representations people form about how AI systems behave. Focusing on AI confidence scores as a form of transparency, we examine how users’ trust and […]
Ranjani Narayanan presents her paper at IEEE CogSIMA 2025 and receives the Best Student Paper Award
Ranjani Narayanan presents her work at the 2025 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) held in Duisburg, Germany. The paper was awarded the Best Student Paper Award of the year. Abstract: With increasing opportunities for collaboration between humans and AI, a crucial aspect of effective teaming is humans’ ability to […]
Human-AI Interaction in Autonomous Aerial Vehicles: A MedEvac Scenario
This project explores the interaction between human operators (novice flight medics) and AI pilots in autonomous aerial vehicles during medical evacuation situations. The primary objective is to evaluate how changes in workload and cognitive biases influence the fluency of human-AI interaction and overall mission effectiveness. Through simulated medical evaluation scenarios, this research seeks to assess […]
ONR – Interactive Machine Learning
We are interested in machines that can learn new things from people who are not Machine Learning (ML) experts. We propose a research agenda framed around the human factors (HF) and ML research questions of teaching an agent via demonstration and critique. Ultimately, we will develop a training simulation game with several nonplayer characters, all […]
ONR STTR – Designing Contextual Decision Support Systems
Support improved decision making under high stress, uncertain operational conditions through the development of proactive, context-based decision support aids. The objective of this project is to create a scientifically-principled design specification and prototype concepts for a set of decision aids capable of supporting decision making and judgment across multi-faceted mission with dynamic tasking requirements. The […]
ONR – Overall Decision Making Process Simulation
Decision makers are consistently asked to make decisions about the course of action required to achieve mission success regardless of the time pressure and the quantity and quality of information available. To be successful, they will adapt their decision strategies to the environment and even use heuristics, simple rules that use little information and can […]