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MANy TASKS ARE trivial for humans but continue to challenge even the most sophisticated computer programs. Traditional computational approaches to solving such problems focus on improving artificialintelligence algorithms. Here, we advocate a different approach: the constructive channeling of human brainpower through computer games. Toward this goal, we present general design principles for the development and evaluation of a class of games we call "games with a purpose," or GWAPs, in which people, as a side effect of playing, perform tasks computers are unable to perform.The Entertainment Software Association (www. theesa.com/facts/gamer_data.php) has reported that more than 200 million hours are spent each day playing computer and video games in the U.S. Indeed, by age 21, the average American has spent more than 10,000 hours playing such games 15 -equivalent to five years of working a full-time job 40 hours per week.

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Software algorithms are changing how people work in an ever-growing number of fields, managing distributed human workers at a large scale. In these work settings, human jobs are assigned, optimized, and evaluated through algorithms and tracked data. We explored the impact of this algorithmic, data-driven management on human workers and work practices in the context of Uber and Lyft, new ridesharing services. Our findings from a qualitative study describe how drivers responded when algorithms assigned work, provided informational support, and evaluated their performance, and how drivers used online forums to socially make sense of the algorithm features. Implications and future work are discussed.

Online communities have the potential to be supportive, cruel, or anywhere in between. The development of positive norms for interaction can help users build bonds, grow, and learn. Using millions of messages sent in Twitch chatrooms, we explore the effectiveness of methods for encouraging and discouraging specific behaviors, including taking advantage of imitation effects through setting positive examples and using moderation tools to discourage antisocial behaviors. Consistent with aspects of imitation theory and deterrence theory, users imitated examples of behavior that they saw, and more so for behaviors from high status users. Proactive moderation tools, such as chat modes which restricted the ability to post certain content, proved effective at discouraging spam behaviors, while reactive bans were able to discourage a wider variety of behaviors. This work considers the intersection of tools, authority, and types of behaviors, offering a new frame through which to consider the development of moderation strategies.

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The present work explores the social dynamics of expressive biosignals: leveraging wearable technologies to introduce sensed physiological data as a means of clarifying the emotional or psychological processes underlying our subjective experiences. We developed an Android application that linked to a wearable heart rate sensor and allowed for the direct sharing and real-time broadcasting of users’ heart rate via text messaging. We deployed this application in a two-week field study to investigate the contextual triggers, perceptions, and consequences of users’ sharing behaviors. The study (N=13) utilized a combination of Experience Sampling Methodology (ESM) and qualitative interviews to discover the situations in which users were more or less likely to share their heart rate with contacts, and the subsequent interactions that occurred after sharing. The results revealed that participants used heart rate sharing as a means to express emotions and provide daily updates, as well as simply a novel and playful form of communication. They reported a variety of communicative consequences of their sharing as well as specific logistical and psychological barriers to sharing. The implications of these results for the design of expressive biosignal sharing systems for supporting positive social interactions are discussed.

Open source software projects often rely on code contributions from a wide variety of developers to extend the capabilities of their software. Project members evaluate these contributions and often engage in extended discussions to decide whether to integrate changes. These discussions have important implications for project management regarding new contributors and evolution of project requirements and direction. We present a study of how developers in open work environments evaluate and discuss pull requests, a primary method of contribution in GitHub, analyzing a sample of extended discussions around pull requests and interviews with GitHub developers. We found that developers raised issues around contributions over both the appropriateness of the problem that the submitter attempted to solve and the correctness of the implemented solution. Both core project members and third-party stakeholders discussed and sometimes implemented alternative solutions to address these issues. Different stakeholders also influenced the outcome of the evaluation by eliciting support from different communities such as dependent projects or even companies. We also found that evaluation outcomes may be more complex than simply acceptance or rejection. In some cases, although a submitter's contribution was rejected, the core team fulfilled the submitter's technical goals by implementing an alternative solution. We found that the level of a submitter's prior interaction on a project changed how politely developers discussed the contribution and the nature of proposed alternative solutions.