Divya passes Thesis Proposal


Divya Srivastava, 5th year Mechanical Engineering student, successfully proposed her PhD thesis entitled ‘Transparency and Operator Performance in Human-Autonomy Teams.’


Human-autonomy teams aim to leverage the different strengths of humans and autonomous systems respectively to exceed the individual capabilities of each through collaboration. Highly effective human teams develop and utilize a shared mental model (SMM): a synchronized under- standing of the external world and of the tasks, responsibilities, capabilities, and limits of each team member. Recent works assert that the same should apply to human-autonomy teams; however, con- temporary AI commonly consists of “black box” systems, whose internal processes cannot easily be viewed or interpreted. Users can easily develop inaccurate mental models of such systems, impeding SMM development and thus team performance.

This thesis seeks to support the human’s side of Human-AI SMMs in the context of AI-advised Decision Making, a form of teaming in which an AI suggests a solution to a human operator, who is responsible for the final decision. This work focuses on improving shared situation awareness by providing more context to the AI’s internal processing, which should lead the human to a more accurate mental model of the task and the AI, and improved team performance. It will provide a validated implementation of how human mental models of AI can be elicited and measured by researchers and system designers, a quantitative link between factors that influence human mental models and human-autonomy team performance in the context of explainable AI, and finally, it will offer design guidance for increasing non-algorithmic transparency in human-autonomy teams based on empirical results, so that the guidance can be applied to other domains.

Author: swalsh40

Sarah is working toward her PhD in Robotics at Georgia Tech in Atlanta. Her research focuses on the development of shared mental models at the intersection of AI interpretability and human behavior analysis to improve human-AI collaboration in team decision-making tasks. Sarah grew up in Tuckerton, New Jersey. She received her BS in Mathematics from Stockton University and completed her BS in Mechanical Engineering at Rutgers University. After working at the Stevens Institute of Technology and Sandia National Laboratories, Sarah chose to continue her education at Georgia Tech. After graduation, Sarah plans to leverage her training and experience to begin her professional career as a research scientist driving innovation in the fields of artificial intelligence and user-experience.

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