Information Sharing for Collective Sensemaking
Abstract
Group decision tasks that require pooling of information to reach the best decision have been studied across a variety of disciplines over the past thirty years. The crucial question of what makes these tasks so difficult, however remains unanswered. Various hypotheses include inefficiency in sharing information leading to decisions based on incomplete information or cognitive inefficiencies in processing and storing information arriving in a piecemeal fashion. The present study attacks this problem from two directions. Human experiments are used to compare decisions between groups manipulated to receive and share information in raw and aggregated forms and mixed groups comprised of humans and software agents. To shed light on cognitive limitations that may affect performance, an ACT-R cognitive model of group members was constructed and its results compared to human data.
BibTeX
@conference{Tang-2016-5480,author = {Yuqing Tang and Christian Lebiere and Katia Sycara and Don Morrison and Michael Lewis and Paul Smart},
title = {Information Sharing for Collective Sensemaking},
booktitle = {Proceedings of 49th Hawaii International Conference on System Sciences (HICSS '16)},
year = {2016},
month = {January},
pages = {377 - 385},
}