As Generative AI (GenAI) becomes increasingly embedded in the workplace, managers are beginning to create Manager Clone Agents—AI-powered digital surrogates trained on their work communications and decision patterns to perform managerial tasks on their behalf. To investigate this emerging phenomenon, we conducted six design fiction workshops (n = 23) with managers and workers, in which participants co-created speculative scenarios and discussed how Manager Clone Agents might transform collaborative work. We identified four potential roles that participants envisioned for Manager Clone Agents: proxy presence, informational conveyor, productivity engine, and leadership amplifier, while highlighting concerns spanning individual, interpersonal, and organizational levels. We provide design recommendations envisioned by both parties for integrating Manager Clone Agents responsibly into the future workplace, emphasizing the need to prioritize workers’ perspectives and nurture interpersonal bonds while also anticipating alternative futures that may disrupt managerial hierarchies.
In difficult workplace email conversations, such as layoffs or resource negotiations, the absence of nonverbal cues can exacerbate negative emotions experienced by recipients. While existing tools support senders in refining tone, there is little support for processing emotionally intensive content from the receivers' side. This study investigated the use of large language models that added positive or neutral reframings, written in either first or third person, to original emails, with the aim of helping recipients view difficult conversations in a different light. In a controlled study with 132 participants, positive reframing reduced receivers' negative emotions and was rated as more helpful than neutral reframing, regardless of narrative perspective. Although reframing type did not significantly change conflict management behaviors, positive reframing led to fewer power-related words in interpretations of the email. These findings highlight opportunities and challenges for designing AI as a social buffer to facilitate difficult conversations online.
Modern cities across the globe increasingly rely on ridehail services for on-demand transportation and mobility. But for drivers, such marketed affordances give rise to hidden burdens and vulnerabilities that evade the oversight of consumers and regulators. To effectively advance worker protections and motivate more socially responsible practices, consumers must understand the realistic labor, logistics and costs involved with ridehail driving. Through nine workshops with 19 drivers and 15 passengers, we explore the potential for gamified in-ride interactions to facilitate engagement with real (and lived) driver experiences, surfacing passenger knowledge gaps around latent ridehail conditions, prompting reflection and shifts in perception of their relative power and consumption behaviors, highlighting drivers' preferences for creating more immersive and contextualized service experiences, and identifying design opportunities for safe and appropriate passenger-driver interactions that motivate solidarity. In sum, we advance conceptual understandings of in-ride social and managerial relations, demonstrate potential for citizen-led advocacy in algorithmically-managed labor, and offer design guidelines for more human-centered workplace technologies.
The integration of mobile technology in education raises concerns about teachers’ work-life boundaries. Most studies examine boundary issues from a Western, individualistic perspective, prompting the question: How might work-life balance be understood within the context of a collectivist culture? This study examines how Chinese teachers manage boundaries on the all-in-one app WeChat. A survey of 108 teachers shows most view WeChat positively for work, while interviews with 18 teachers reveal that while teachers experience fatigue from blurred boundaries and constant availability, they also view WeChat as indispensable for managing fragmented responsibilities, sustaining relationships, and coordinating collective tasks. Teachers employ workarounds to negotiate expectations of accessibility. These practices highlight what we describe as expected permeability, a relationally constructed rhythm of accessibility shaped by obligations and tie-specific norms, while foregrounding relational agency as a stronger lens for rethinking both platform design and work-life balance theory beyond individualistic framings.
Generative AI (GenAI) is reshaping work, but adoption remains largely individual and experimental rather than coordinated into collaborative work. Whether GenAI can move from individual use to collaborative work is a critical question for future organizations. Journalism offers a compelling site to examine this shift: individual journalists have already been disrupted by GenAI tools; yet newswork is inherently collaborative relying on shared norms and coordinated workflows. We conducted 27 interviews with newsroom managers, editors and front-line journalists in China. We found that journalists frequently used GenAI to support daily tasks, but value alignment was safeguarded mainly through individual discretion. At the organizational level, GenAI use remained disconnected from team workflows, hindered by structural barriers and cultural reluctance to share practices. These findings underscore the gap between individual and collaborative work, pointing to the need to account for organizational structures, cultural norms, and workflow when coordinating GenAI for collaborative work.
Gender microaggressions are subtle yet persistent forms of discrimination in workplace interactions. While LLMs can detect them in written texts, it remains poorly understood how their interpretations align or diverge from human perspectives and experiences. We present a mixed-method study comparing how LLMs and humans differing in gender identity and lived experience, interpret gender microaggressions in the workplace. Using short dialogues adapted from real-world accounts, we asked 141 participants to rate the likelihood that a scenario contains a microaggression and provide a rationale for their answers. The same tasks were completed by 7 different LLM models. Our analysis reveals significant differences in how humans and LLMs interpret microaggressions, captured in both ratings and rationales, and more interestingly, the effect of gender and lived experience on human interpretations. These findings highlight the need for systems detecting microaggressions to embrace interpretive plurality, and support reflection and awareness while accounting for ambiguity.
Eight of the ten largest American companies now use employee tracking software, which has raised concerns about invasive monitoring. Metaverse platforms then emerged as a potential alternative to restore natural workplace visibility without keystroke logging or screen capture. While most metaverse workplace implementations were abandoned quickly, Zigbang, a South Korean company operating entirely through its metaverse platform since 2022, stands as a notable exception. Through our mixed-method analysis of employee experiences and stakeholder perspectives, we identify three factors that undermine metaverse workplace sustainability: the persistence of surveillance proxies over meaningful performance assessment, design choices that prioritize realism over digital innovation, and the absence of governance frameworks specific to metaverse workplaces. Our findings reveal that metaverse workplaces often perpetuate and amplify problematic management paradigms rather than transcend them. Using these insights, we propose frameworks for task-specific monitoring, digital-first design, and governance guidelines to aid development of ethical and sustainable metaverse workplaces.