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Despite debates about emotion artificial intelligence's (EAI) validity, legality, and social consequences, EAI is increasingly present in the high stakes context of hiring, with potential to shape the future of work and the workforce. The values laden in technology play a significant role in its societal impact.We conducted qualitative content analysis on the public-facing websites (N=229) of EAI hiring services. We identify the organizational problems that EAI hiring services claim to solve and reveal the values emerging in desired EAI uses as promoted by EAI hiring services to solve organizational problems. Our findings show that EAI hiring services market their technologies as technosolutions to three purported organizational hiring problems: 1) hiring (in)accuracy, 2) hiring (mis)fit, and 3) hiring (in)authenticity. We unpack these problems to expose how these desired uses of EAI are legitimized by the corporate ideals of data-driven decision making, continuous improvement, precision, loyalty, and stability. We identify the unfair and deceptive mechanisms by which EAI hiring services claim to solve the purported organizational hiring problems, suggesting that they unfairly exclude and exploit job candidates through EAI's creation, extraction, and affective commodification of a candidate's affective value through pseudoscientific approaches. Lastly, we interrogate EAI hiring service claims to reveal the core values that underpin their stated desired use: techno-omnipresence, techno-omnipotence, and techno-omniscience. We show how EAI hiring services position desired use of their technology as a moral imperative for hiring organizations with supreme capabilities to solve organizational hiring problems, then discuss implications for fairness, ethics, and policy in EAI-enabled hiring within the US policy landscape. 

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.