Although the metaverse workspace has the potential to solve some of the drawbacks of remote work while maintaining its benefits, there are few real-world cases of adopting the metaverse as a legitimate workspace and fewer subsequent studies on how to design and operate the metaverse workspace. Thus, questions exist about the organizational or sociotechnical challenges that may emerge and how decisions are made when adopting and operating the metaverse workspace in a real-world setting. To answer such questions, we scrutinized the startup company Zigbang, which has completely replaced their physical office with Soma— a metaverse platform they developed where thousands of people work and other cooperative companies have moved in as tenants. By conducting field observations and semi-structured interviews with various workers and Zigbang’s stakeholders, we identify essential design challenges and decisions when adopting a metaverse workspace and highlight the key takeaways learned from the company’s trials and errors.
doi.org/10.1145/3613904.3641972
The early stages of video editing present many cognitively demanding tasks that require editors to remember and structure large amounts of video. In our formative work we learned that editors break down the editing process into smaller parts by labeling and organizing footage around central themes. Using current video editing tools, this process is slow and largely manual. We present a system called ChunkyEdit for helping editors group video interview clips into thematically coherent chunks, which can then be exported to existing video editing tools and composed into an edited narrative. By focusing on this intermediate step, we leverage computation to do tedious organizational tasks, while preserving the editor's ability to control the primary storytelling decisions. We explore four different topic modeling approaches to creating video chunks. We then evaluate our tool with eight professional video editors to learn how a chunking-based approach could be incorporated into video editing workflows.
doi.org/10.1145/3613904.3642667
The research centers on examining the utilization of instant messaging (IM) in remote work interactions between supervisors and subordinates. Through a series of one-on-one in-depth interviews (n = 12), our findings unveil distinct nuances in how subordinates and supervisors perceive and engage with IM, encompassing aspects such as response strategies, interaction frequency, and interaction nature. Notably, a significant finding emerged concerning the practice of self-censorship in IM, acting as a strategy for impression management, predominantly adopted by subordinates in their interactions with supervisors. Additionally, our investigation sheds light on a contrasting viewpoint regarding the social use of IM. While supervisor participants acknowledged its potential to bolster work-related collaboration, this perspective appeared less pronounced among subordinate participants. Our study concludes by delving into the design implications for IM application design, offering insights that can shape collaborative dynamics within remote work environments.
doi.org/10.1145/3613904.3642913
Large language models (LLMs) like ChatGPT have been widely adopted in work contexts. We explore the impact of ChatGPT on young professionals' perception of productivity and sense of accomplishment. We collected LLMs' main use cases in knowledge work through a preliminary study, which served as the basis for a two-week diary study with 21 young professionals reflecting on their ChatGPT use. Findings indicate that ChatGPT enhanced some participants' perceptions of productivity and accomplishment by enabling greater creative output and satisfaction from efficient tool utilization. Others experienced decreased perceived productivity and accomplishment, driven by a diminished sense of ownership, perceived lack of challenge, and mediocre results. We found that the suitability of task delegation to ChatGPT varies strongly depending on the task nature. It's especially suitable for comprehending broad subject domains, generating creative solutions, and uncovering new information. It's less suitable for research tasks due to hallucinations, which necessitate extensive validation.
doi.org/10.1145/3613904.3641964
The literature has shown that combining a few non-Personal Identifiable Information (non-PII) is enough to make a user unique in a dataset including millions of users. This work demonstrates that a combination of a few non-PII items can be activated to nanotarget users. We demonstrate that the combination of the location and 5 rare (13 random) skills in a LinkedIn profile is enough to become unique in a user base of ∼970M users with a probability of 75%. The novelty is that these attributes are publicly accessible to anyone registered on LinkedIn and can be activated through advertising campaigns. We ran an experiment configuring ad campaigns using the location and skills of three of the paper's authors, demonstrating how all the ads using >13 skills were delivered exclusively to the targeted user. We reported this vulnerability to LinkedIn, which initially ignored the problem, but fixed it as of November 2023.
doi.org/10.1145/3613904.3642107