The DUB Shorts format focuses on sharing a research paper in a 15 to 20-minute talk, similar to traditional conference presentations of a paper. Speakers will first present the paper, then participate in Q&A.
DUB shorts will be conducted using Zoom, via an invitation distributed to the DUB mailing list. Participants who are logged into Zoom using a UW account will be directly admitted, and participants who are not logged in to a UW account will be admitted using a Zoom waiting room.
My Team Will Go On: Differentiating High and Low Viability Teams through Team Interaction
Understanding team viability — a team’s capacity for sustained and future success — is essential for building effective teams. In this study, we aggregate features drawn from the organizational behavior literature to train a viability classification model over a dataset of 669 10-minute text conversations of online teams. We train classifiers to identify teams at the top decile (most viable teams), 50th percentile (above a median split), and bottom decile (least viable teams), then characterize the attributes of teams at each of these viability levels. We find that a lasso regression model achieves an accuracy of .74–.92 AUC ROC under different thresholds of classifying viability scores. From these models, we identify the use of exclusive language such as ‘but’ and ‘except’, and the use of second person pronouns, as the most predictive features for detecting the most viable teams, suggesting that active engagement with others’ ideas is a crucial signal of a viable team. Only a small fraction of the 10-minute discussion, as little as 70 seconds, is required for predicting the viability of team interaction. This work suggests opportunities for teams to assess, track, and visualize their own viability in real time as they collaborate.
Computer Science & Engineering
Metaphors for Human-Robot Interaction
“The word “robot” frequently conjures unrealistic expectations of utilitarian perfection: tireless, efficient, and flawless agents. However, real-world robots are far from perfect—they fail and make mistakes. Thus, roboticists should consider altering their current assumptions and cultivating new perspectives that account for a more complete range of robot roles, behaviors, and interactions. To encourage this, we explore the use of metaphors for generating novel ideas and reframing existing problems to elicit new perspectives of human-robot interaction. Our work makes two contributions. We (1) surface current assumptions that accompany the term “robots,” and (2) present a collection of alternative perspectives of interaction with robots through metaphors. By identifying assumptions, we provide a comprehensible list of aspects to reconsider regarding robots’ physicality, roles, and behaviors. Through metaphors, we propose new ways of examining how we can use, relate to, and co-exist with the robots that will share our future.”