技术工作者如何应对生成式人工智能中类人特性的潜在风险 (How Tech Workers Contend with Hazards of Humanlikeness in Generative AI)

Generative AI's humanlike qualities are driving its rapid adoption in professional domains. However, this anthropomorphic appeal raises concerns from HCI and responsible AI scholars about potential hazards and harms, such as overtrust in system outputs. To investigate how technology workers navigate these humanlike qualities and anticipate emergent harms, we conducted focus groups with 30 professionals across six job functions (ML engineering, product policy, UX research and design, product management, technology writing, and communications). Our findings reveal an unsettled knowledge environment surrounding humanlike generative AI, where workers' varying perspectives illuminate a range of potential risks for individuals, knowledge work fields, and society. We argue that workers require comprehensive support, including clearer conceptions of ``humanlikeness'' to effectively mitigate these risks. To aid in mitigation strategies, we provide a conceptual map articulating the identified hazards and their connection to conflated notions of ``humanlikeness.''

翻译：生成式人工智能的类人特性正推动其在专业领域的快速应用。然而，这种拟人化吸引力引发了人机交互与负责任人工智能领域学者对潜在危险与危害的担忧，例如对系统输出的过度信任。为探究技术工作者如何应对这些类人特性并预见新兴危害，我们组织了焦点小组，涵盖六大职能（机器学习工程、产品政策、用户体验研究与设计、产品管理、技术写作及传播）的30名专业人士参与研究。我们的研究揭示了一个围绕类人生成式人工智能的不稳定认知环境，工作者们不同的观点阐明了对个人、知识工作领域及社会的一系列潜在风险。我们认为，工作者需要全面的支持，包括更清晰的"类人性"概念，以有效缓解这些风险。为协助制定缓解策略，我们提供了一个概念图谱，阐明了已识别的危害及其与"类人性"混淆概念间的关联。