Professional writing skills are essential for crafting job application materials where applicants showcase their qualifications to recruiters and employers. Lettersmith is a digital tool that supports writing through scaffolded annotation, an instructional approach combining an expert-informed checklist, annotated examples, and self-tagging. We evaluated the efficacy of the instructional mechanisms that make up scaffolded annotation, as well as the use of ChatGPT, in facilitating writing cognitive processes and writing quality. Through a lab experiment with 146 first-year college students writing and revising a cover letter, we found that the combined mechanisms of scaffolded annotation within Lettersmith promoted a stronger understanding of the writing genre. Specifically, the use of a checklist combined with another writing support, like an example or self-tagging, was particularly effective for improving writing quality. Unstructured use of ChatGPT did not improve writing cognitive processes or writing quality more than Lettersmith.

Work is increasingly shifting away from traditional full-time jobs toward more fragmented ways of working, like gig work and part-time jobs. Yet, employment platforms like LinkedIn often privilege those with traditional credentials and work histories, presenting barriers to those who possess little experience translating informal experiences into a format that such tools expect. To address this gap, we propose a narrative-based approach that enables individuals to recognize transferable skills and practice articulating them verbally and in writing via a group discussion setting. Through a participatory design workshop held in a public housing community, we demonstrate how a cultural-probe and persona-inspired activity can elicit self-reflection, enabling individuals to communicate their strengths. While prior HCI research has highlighted the critical need for reflection in the job search process, little work has been done to facilitate this reflection and translation into employment profiles. Our work addresses this call and informs new design directions for employment technologies.

People share and encounter a range of posts on social media that depict different career experiences, such as one's successes or failures. In a continually shifting world of work, observing others' job experiences can be useful for navigating one's own career journey. The present study applies the possible selves theory to understand how viewing people's career experiences on social media might affect viewers' career-related expectations, hopes, and fears. From semi-structured interviews with 19 social media users with different career experiences, this study found that social media posts may facilitate functions of possible selves by 1) increasing people's awareness of new and diverse career paths and 2) motivating people in planning and preparing for a desired possible self. Across these functions, we found that videos were particularly beneficial for uncovering and learning about life in a career and that observing others' career experiences online often evoked social comparison. Through an affordances lens, findings also indicate that social media affordances of visibility and persistence were particularly relevant in developing and assessing career-related possible selves and sometimes strategically managed through leveraging platform algorithms. This paper brings forth empirical contributions to the possible selves theory in the digital age and highlights the significance of social media mechanisms for possible selves. This paper also provides design implications for social media platforms and recommendations for potential career counseling and mentoring strategies that may be useful for individuals navigating and exploring career possibilities.

Emotion AI, or AI that claims to infer emotional states from various data sources, is increasingly deployed in myriad contexts, including mental healthcare. While emotion AI is celebrated for its potential to improve care and diagnosis, we know little about the perceptions of data subjects most directly impacted by its integration into mental healthcare. In this paper, we qualitatively analyzed U.S. adults' open-ended survey responses (n = 395) to examine their perceptions of emotion AI use in mental healthcare and its potential impacts on them as data subjects. We identify various perceived impacts of emotion AI use in mental healthcare concerning 1) mental healthcare provisions; 2) data subjects' voices; 3) monitoring data subjects for potential harm; and 4) involved parties' understandings and uses of mental health inferences. Participants' remarks highlight ways emotion AI could address existing challenges data subjects may face by 1) improving mental healthcare assessments, diagnoses, and treatments; 2) facilitating data subjects' mental health information disclosures; 3) identifying potential data subject self-harm or harm posed to others; and 4) increasing involved parties' understanding of mental health. However, participants also described their perceptions of potential negative impacts of emotion AI use on data subjects such as 1) increasing inaccurate and biased assessments, diagnoses, and treatments; 2) reducing or removing data subjects' voices and interactions with providers in mental healthcare processes; 3) inaccurately identifying potential data subject self-harm or harm posed to others with negative implications for wellbeing; and 4) involved parties misusing emotion AI inferences with consequences to (quality) mental healthcare access and data subjects' privacy. We discuss how our findings suggest that emotion AI use in mental healthcare is an insufficient techno-solution that may exacerbate various mental healthcare challenges with implications for potential distributive, procedural, and interactional injustices and potentially disparate impacts on marginalized groups.

The workplace has experienced extensive digital transformation, in part due to artificial intelligence's commercial availability. Though still an emerging technology, emotional artificial intelligence (EAI) is increasingly incorporated into enterprise systems to augment and automate organizational decisions and to monitor and manage workers. EAI use is often celebrated for its potential to improve workers' wellbeing and performance as well as address organizational problems such as bias and safety. Workers subject to EAI in the workplace are data subjects whose data make EAI possible and who are most impacted by it. However, we lack empirical knowledge about data subjects' perspectives on EAI, including in the workplace. To this end, using a relational ethics lens, we qualitatively analyzed 395 U.S. adults' open-ended survey (partly representative) responses regarding the perceived benefits and risks they associate with being subjected to EAI in the workplace. While participants acknowledged potential benefits of being subject to EAI (e.g., employers using EAI to aid their wellbeing, enhance their work environment, reduce bias), a myriad of potential risks overshadowed perceptions of potential benefits. Participants expressed concerns regarding the potential for EAI use to harm their wellbeing, work environment and employment status, and create and amplify bias and stigma against them, especially the most marginalized (e.g., along dimensions of race, gender, mental health status, disability). Distrustful of EAI and its potential risks, participants anticipated conforming to (e.g., partaking in emotional labor) or refusing (e.g., quitting a job) EAI implementation in practice. We argue that EAI may magnify, rather than alleviate, existing challenges data subjects face in the workplace and suggest that some EAI-inflicted harms would persist even if concerns of EAI's accuracy and bias are addressed.

Major life events can cause great upheaval in one's life. Many people perceive their identities to change due to major life events. During identity shifts, impression management and self-presentation, online communities, and social media affordances can allow individuals to better facilitate their experiences. To examine how people perceive their identity to change during major events and how they use social media in the process, we interviewed 28 participants who recently experienced major life events. We found that many people perceived their identity to change through various avenues that they felt were important to their identity: mental processes, identity roles, and identity fulfillment. However, some people perceive their identity to be maintained rather than changed. During identity changes or maintenance, participants utilized impression management and self-presentation to curate their online presence. Participants also used online communities to build relationships with similar others or virtual friends and enable more connections via what we call the domino effect. Social media sites also provided the affordances of editability, visibility control, and spreadability, which can help ease life transition and identity change processes.

Some life transitions can be difficult to discuss on social media, especially with networks of known ties, due to challenges such as stigmatization. Separate online networks can provide alternative spaces to discuss life transitions. To understand why and how people turn to separate networks, we interviewed 28 participants who had recently experienced life transitions. While prior research tends to focus on one life transition in isolation, this work examines social media sharing behaviors across a wide variety of life transitions. We describe how people often turn to separate networks during life transitions due to challenges faced in networks of known ties, yet encounter new challenges such as difficulty locating these networks. We describe support from waiting contributors and virtual friends. Finally, we provide insight into how online separate networks can be better designed through enhancing search functionality, promoting contribution, and providing context-sensitive templates for sharing in online spaces.

Abstract When people experience major life changes, this often impacts their self‐presentation, networks, and online behavior in substantial ways. To effectively study major life transitions and events, we surveyed a large U.S. sample (n = 554) to create the Major Life Events Taxonomy, a list of 121 life events in 12 categories. We then applied this taxonomy to a second large U.S. survey sample (n = 775) to understand on average how much social readjustment each event required, how likely each event was to be shared on social media with different types of audiences, and how much online network separation each involved. We found that social readjustment is positively correlated with sharing on social media, with both broad audiences and close ties as well as in online spaces separate from one's network of known ties. Some life transitions involve high levels of sharing with both separate audiences and broad audiences on social media, providing evidence for what previous research has called social media as social transition machinery. Researchers can use the Major Life Events Taxonomy to examine how people's life transition experiences relate to their behaviors, technology use, and health and well‐being outcomes.

People often strive to present themselves authentically on social media, but this may not be possible for everyone. To understand how people view online authenticity, how it relates to social media sharing behaviors, and whether it is achievable, we interviewed 28 social media users who had recently experienced major life transitions. We found that to many participants, online authenticity required presenting a consistent, positive, and "true" self across online and offline contexts. Though most stated that they considered online authenticity achievable, their social media self-disclosure behaviors around life transitions revealed what we call the online authenticity paradox: people strive to achieve online authenticity, yet because doing so requires sharing negative experiences on social media, online authenticity is often unreachable, or is possible only at great personal cost - especially for those with marginalized identities and difficult life experiences.