AURA: Amplifying Understanding, Resilience, and Awareness for Responsible AI Content Work

November 03, 2024 Β· Declared Dead Β· πŸ› Proc. ACM Hum. Comput. Interact.

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Authors Alice Qian Zhang, Judith Amores, Mary L. Gray, Mary Czerwinski, Jina Suh arXiv ID 2411.01426 Category cs.HC: Human-Computer Interaction Cross-listed cs.CY Citations 9 Venue Proc. ACM Hum. Comput. Interact. Last Checked 4 months ago
Abstract
Behind the scenes of maintaining the safety of technology products from harmful and illegal digital content lies unrecognized human labor. The recent rise in the use of generative AI technologies and the accelerating demands to meet responsible AI (RAI) aims necessitates an increased focus on the labor behind such efforts in the age of AI. This study investigates the nature and challenges of content work that supports RAI efforts, or "RAI content work," that span content moderation, data labeling, and red teaming -- through the lived experiences of content workers. We conduct a formative survey and semi-structured interview studies to develop a conceptualization of RAI content work and a subsequent framework of recommendations for providing holistic support for content workers. We validate our recommendations through a series of workshops with content workers and derive considerations for and examples of implementing such recommendations. We discuss how our framework may guide future innovation to support the well-being and professional development of the RAI content workforce.
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