The team aims to investigate theories and applications of building Artificial Intelligence (AI)-based decision makers who can make human trusted decisions in dynamic situations, where no right answers exist, and decisions need to be made quickly and effectively. Examples include disaster relief and emergency response. We will employ methods in human factors, stochastic optimization, and machine learning, to derive robust, automated algorithms for triaging and prioritizing tasks, by accommodating variations in human decision makers’ preferences. The research will produce preliminary results for seeking external grants from NSF, DoD and other agencies who value the fundamental science of building trust between human and machines in complex and dynamic scenarios.
Funding: $60K (2022)
Goal: To capture the key characteristics of expert human decision-making in dynamic settings and computationally representing that data in algorithmic decision-makers; to make trustworthy choices under difficult circumstances.
Token Investors: Siqian Shen, Xi Jessie Yang, Ruiwei Jiang, Cong Shi
Project ID: 1017