Recent advances in deep generative neural networks have made it possible for artificial intelligence to actively collaborate with human beings in co-creating novel content (e.g. music, art). While substantial research focuses on (individual) human-AI collaborations, comparatively less research examines how AI can play a role in human-human collaborations during co-creation. In a qualitative lab study, we observed 30 participants (15 pairs) compose a musical phrase in pairs, both with and without AI. Our findings reveal that AI may play important roles in influencing human social dynamics during creativity, including: 1) implicitly seeding a common ground at the start of collaboration, 2) acting as a psychological safety net in creative risk-taking, 3) providing a force for group progress, 4) mitigating interpersonal stalling and friction, and 5) altering users’ collaborative and creative roles. This work contributes to the future of generative AI in social creativity by providing implications for how AI could enrich, impede, or alter creative social dynamics in the years to come.

The process of settling in a new country can be extremely challenging, entailing various information needs to cope with rapid changes and adjustments to a new environment. Through interviews with 16 Korean immigrants in the United States, we explored their information behaviors in the settlement process. In line with prior work (Shoham & Strauss, 2008), we found that Korean immigrants needed various types of information: housing, work, banking, transportation, law, school, health, and language. Out of these information types, the Korean immigrants prioritized information for education and struggled to seek health and legal information. We further uncovered that various information needs are closely intertwined and found an additional type of information need: to build a new social network after migration. They often used Information and Communication Technologies (ICTs) as information sources while adapting the ICT infrastructures of the U.S. into their information practices. ICTs enabled them to build and maintain “local” and “global” identity; however, they may struggle to assess user‐generated content in the new context. We noted that their strong use of ICTs for intraethnic interaction might slow down their integration into the host society. We discuss implications for future work to support immigrants' settlement in the host country.

Although Collaborative Information-Seeking (CIS) is becoming prevalent as people engage in shared decision-making, interface components adopted in the most commonly used information seeking tools (e.g., search, filter, select, and sort) are designed for individual use. To deepen our understanding of (1) how such single-user designs affect people's consensus building processes in CIS and (2) how to devise an alternative design to improve current practices, we conducted two 4-week diary studies and observed how groups seek out places together. Our studies focus on social event coordination as a case where CIS is necessary and important. In Study 1, we examined the major challenges people encounter when performing CIS using their preferred tools. These challenges include difficulties in capturing mutual preferences, high communication cost, and disparity of work depending on a group member's perceived role as an organizer or invitee. We discovered that improving a group's shared understanding of the target information they seek (e.g., places, products) could potentially address the challenges. In Study 2, we designed, deployed, and evaluated ComeTogether, a novel system that supports a group's social event coordination. ComeTogether adopts Collaborative Dynamic Queries (C-DQ), an interface designed to allow a group to share their preferences regarding potential destinations. Study 2 results indicate that using C-DQ increased users' awareness of other group members' preferences in performing CIS, making their coordination more transparent, more inviting, and fairer than what their current practice allows. Meanwhile, ComeTogether improved communication efficiency of groups while presenting opportunities to learn about others and to discover new places. We provide implications for design that explain considerations for adopting C-DQ and identify future research directions.

Communication is critical in small group decision-making processes during which each member must be able to express preferences to reach consensus. Finding consensus can be difficult when each member in a group has a perspective that potentially conflicts with those of others. To support groups attempting to harmonize diverse preferences, we propose Collaborative Dynamic Queries (C-DQ), a UI component that enables a group to filter queries over decision criteria while being aware of others' preferences. To understand how C-DQ affects a group's behavior and perception in the decision-making process, we conducted 2 studies with groups who were prompted to make decisions together on mobile devices in a dispersed and synchronous situation. In Study 1, we found showing group preferences with C-DQ helped groups to communicate more efficiently and effectively. In Study 2, we found filtering candidates based on each member's own filter range further improved a groups' communication efficiency and effectiveness.

Mobile videochat use has been growing, especially for teens. To better understand teens' videochat practices, we conducted a two-week photo diary study with 16 teens. We found that most often, teens videochat with their closest friends from their bedrooms when they feel lonely or bored. Teens turned to videochat when understimulated but also felt understimulated during videochat. In order to manage this, they multitasked -teens moved from active chatting to co-presence while engaged in separate activities like scrolling social feeds or playing games. We uncovered social norms of reciprocity of attention, where teens match the attention level of the other and give leeway to briefly divert attention. Digital notifications did not feel disruptive to the videochat but family members' interruptions felt disruptive as teens' domestic context intruded into their virtual peer setting. We discuss these findings and their implications for research and design of videochat systems.

Despite the prevalence of theories and interventions related to behavior change, our knowledge on how intention for a target, or planned behavior, changes over time remains limited. This hinders our ability to consider the temporal aspect in our designs to support behavior change. To understand the effect of temporal distances on planned behaviors, we conducted two studies, building on the Theory of Planned Behavior and Constual Level Theory. We found that attitude about the target is more salient the further away the event, as people focus on the why of a behavior. On the other hand, perceived behavior control can influence intention in both near and far future. When the target is in the near future, people generally focus on the feasibility, or the how of the behavior. In the far future, people may also consider factors related to behavior control, if they are motivated to do so (i.e., hold a strong attitude towards the action). Findings help advance the Theory of Planned Behavior and offer strategies for designers and event organizers to motivate planned behaviors that are in the near and far future.

E-petitioning has become one of the most important and popular forms of online activism. Although e-petition success is driven by user behavior, users have received relatively little study by HCI and social computing researchers. Drawing from theoretical and empirical work in analogous social computing systems, we identify two potentially competing theories about the trajectories of users in e-petition platforms: (1) "power" users in social computing systems are born, not made; and (2) users mature into "power" users. In a quantitative analysis of data from Change.org, one of the largest online e-petition platforms, we test and find support for both theories. A follow-up qualitative analysis shows that not only do users learn from their experience, systems also "learn" from users to make better recommendations. In this sense, we find that although power users are "born," they are also "made" through both processes of personal growth and improved support from the system.