Data Subjects' Perspectives on Emotion Artificial Intelligence Use in the Workplace: A Relational Ethics Lens
Data Subjects' Perspectives on Emotion Artificial Intelligence Use in the Workplace: A Relational Ethics Lens
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数据主体对工作场所情感人工智能使用的看法：关系伦理视角
DOI：
10.1145/3579600
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发表时间：
2023
影响因子：
--
通讯作者：
Andalibi, Nazanin
中科院分区：
文献类型：
--
作者：
Corvite, Shanley;Roemmich, Kat;Rosenberg, Tillie Ilana;Andalibi, Nazanin
工作场所经历了广泛的数字化转型，部分原因是人工智能的商业可用性。虽然情感人工智能(EAI)仍然是一项新兴技术，但它越来越多地被纳入企业系统，以增强组织决策并使其自动化，并监控和管理员工。EAI的使用经常因其在改善员工福祉和绩效以及解决偏见和安全等组织问题方面的潜力而受到称赞。在工作场所受到EAI影响的员工是数据主体，他们的数据使EAI成为可能，也是受其影响最大的群体。然而，我们缺乏关于数据主体对EAI的看法的实证知识，包括在工作场所。为此，我们使用关系伦理学的视角，定性地分析了395名美国成年人的开放式调查(部分具有代表性)的回复，这些回复涉及他们在工作场所受到EAI影响所感受到的好处和风险。虽然参与者承认接受EAI的潜在好处(例如，雇主使用EAI来帮助他们的福祉、改善他们的工作环境、减少偏见)，但无数的潜在风险盖过了对潜在好处的看法。与会者对使用EAI可能损害他们的福祉、工作环境和就业状况表示关切，并制造和放大了对他们的偏见和污名，特别是对最边缘化的人(例如，在种族、性别、心理健康状况、残疾方面)。由于不信任EAI及其潜在的风险，参与者期望在实践中遵守(例如，参与情绪劳动)或拒绝(例如，辞去一份工作)EAI实施。我们认为，EAI可能会放大而不是缓解数据主体在工作场所面临的现有挑战，并建议即使解决了对EAI准确性和偏见的担忧，EAI造成的一些危害也将持续存在。
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.
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