Philip Resnik Receives NSF Grant to Develop Computational Models to Better Understand Human Decisions

Professor Philip Resnik received an NSF grant from the Division of Information and Intelligent Systems for his project titled “RI: Small: Modeling Co-Decisions: A Computational Framework Using Language and Metadata.” 

The funded project will develop computational models to help illuminate why and how individuals make similar or different choices, for example legislators in political contexts. The research focuses on going beyond previous factors like party and demographics to analyze similarities and differences in individuals' language, using techniques that identify interpretable, task-relevant language and incorporating recently developed methods for incorporating covariates into topic analysis.

“It is very standard to look independently at choices made by individuals, but a more complete scientific understanding of decision-making can be obtained by looking at the decision process in terms of whether individuals will make the same decision or not, taking into account what the individual deciders do and do not have in common,” explains Resnik. 

The project team plans to address more general use cases by applying the approach beyond the political domain, moving from modeling of co-voting to modeling co-decisions, where a decision is a generalized vote.

In addition to being an affiliate professor in computer science Resnik holds a joint appointment as Professor in the University of Maryland Institute for Advanced Computer Studies and the Department of Linguistics, UMD.