AURA: Amplifying Understanding, Resilience, and Awareness for Responsible AI Content Work
November 03, 2024 Β· Declared Dead Β· π 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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