Michael Dunn

Yilin Ning, Salinelat Teixayavong, Yuqing Shang et al.

The widespread use of ChatGPT and other emerging technology powered by generative artificial intelligence (GenAI) has drawn much attention to potential ethical issues, especially in high-stakes applications such as healthcare, but ethical discussions are yet to translate into operationalisable solutions. Furthermore, ongoing ethical discussions often neglect other types of GenAI that have been used to synthesise data (e.g., images) for research and practical purposes, which resolved some ethical issues and exposed others. We conduct a scoping review of ethical discussions on GenAI in healthcare to comprehensively analyse gaps in the current research, and further propose to reduce the gaps by developing a checklist for comprehensive assessment and transparent documentation of ethical discussions in GenAI research. The checklist can be readily integrated into the current peer review and publication system to enhance GenAI research, and may be used for ethics-related disclosures for GenAI-powered products, healthcare applications of such products and beyond.

Pyeonghwa Kim, Taylor Lewandowski, Michael Dunn et al.

We focus on occupational diversity in platform-mediated work to advance conceptual and empirical insight into the occupationally embedded nature of platform labor. We pursue this focus in response to a prevailing tendency to treat platform workers as a homogeneous group, overlooking the unique demands, constraints, and practices rooted in specific professions. Such generalizations hinder both understanding of platform work and the development of sociotechnical systems that support differentiated occupational realities. To address this gap, we present a longitudinal analysis of 108 online freelancers spanning five occupational categories. We show that occupational context structures workers' capacity to interpret and navigate platformic management, shaping distinct experiences across four dimensions of platform work: self-presentation, flexibility, skilling, and platform work sustainability. To articulate how digital labor platforms' managerial control interacts with occupational embeddedness, we introduce the concept of platformic occupational stratification and discuss four mechanisms that explain its logic and implications for platform-mediated work. These insights contribute to CSCW by informing occupation-sensitive research and design approaches that directly engage with the specific opportunities and challenges rooted in workers' situated occupational agency in platform-mediated work.