We report the results of an experiment examining how an autonomous mobile robotpsilas disclosure of task versus affective information influences peoplepsilas feelings about a robot when working on a collaborative task. In a 3 times 2 experiment, we examined disclosure (task, affective and no disclosure) and the trigger that produced the disclosure (automatic vs. on-demand). We hypothesized that a robot disclosing task information would increase peoplepsilas sense of control because it provides awareness about the task situation, but that affective information would decrease peoplepsilas sense of control. We also predicted that people would like robots better when they disclose affective information. Our findings confirm that people both felt less in control and liked the robot more when the robot disclosed its affective state. We further found that providing people with the ability to control disclosure (on demand vs. automatic disclosure), increased their sense of control, but decreased their liking of the robot. This research suggests the need to weigh a potential tradeoff between designing robot collaborators that evoke perceptions of control versus liking. In the discussion, we explore design implications and how different combinations of disclosure types and triggers may optimize both feelings of control and liking in human-robot collaboration.

This study explores interruption patterns among software developers who program in pairs versus those who program solo. Ethnographic observations indicate that interruption length, content, type, occurrence time, and interrupter and interruptee strategies differed markedly for radically collocated pair programmers versus the programmers who primarily worked alone. After presenting an analysis of 242 interruptions drawn from more than 40 hours of observation data, we discuss how team configuration and work setting influenced how and when developers handled interruptions. We then suggest ways that CSCW systems might better support pair programming and, more broadly, provide interruption-handling support for workers in knowledge-intensive occupations.

This ethnographic study suggests that social structures such as the sex segregation of jobs may impact how different groups of workers make sense of robots in their work environment. Designers may need to take such structures into account if mobile autonomous robots are to operate successfully alongside humans in the workplace.