MIT EECS — Angle Undergraduate Research and Innovation Scholar
Towards Super-Human Decision Making: Improving Response to Decision Support Systems
Julie A. Shah
The goal of decision support systems (DSS’s) is to transcend the limits of human cognition and enable super-human decision making for operators in aviation, healthcare, emergency response, and more. But the harmonious combination of a human’s intuition and a machine’s computational power is hard to achieve, and DSS’s are often distrusted or mistrusted by their operators. Additionally, the segmented effort to improve DSS’s is hampered by the lack of an established terminology to discuss plans for improvement. The goal of this work is to synthesize existing insights from multiple domains, to develop a universal model of these systems, and to apply this model to propose design principles that will allow field experts to troubleshoot and devise plans for improving current systems.
I applied for the SuperUROP program because I was inspired by the work of the lab I have been UROPing with–the Interactive Robotics Group of CSAIL. My supervisors were kind enough to give me the opportunity to design my own research project, and the program was the perfect outlet for it. I hope to get an even better picture of the research world–both the highs and lows–and learn more about decision support systems.