Locating Risk: Task Designers and the Challenge of Risk Disclosure in RAI Content Work
Authors: A Qian, R Shaw, L Dabbish, J Suh, H Shen
Published: 2025
Publication: arXiv preprint arXiv ..., 2025 - arxiv.org
The paper examines how task designers approach well-being risk disclosure in Responsible AI (RAI) content work, highlighting a need for better frameworks to communicate such risks effectively.
Methods: Interviews were conducted with 23 task designers from academic and industry sectors to gather insights on risk recognition, interpretation, and communication practices.
Key Findings: How task designers recognize, interpret, and communicate well-being risks in RAI content work.
Limitations: Lack of standard workflows or established guidelines for risk disclosure, which can lead to inconsistent application of consent flows, content warnings, and other protective measures for crowdworkers.
Institution: Carnegie Mellon University, University of Pittsburgh, University of Utah, Yale School of Medicine, Yale University
Research Area: Responsible AI, Content Moderation, Risk Disclosure,Worker Well-being in Human-Computer Interaction (HCI).
Discipline: Computational Social Science, Human-Computer Interaction (HCI)
Sample Size: 23 participants
Citations: 1