Measuring the Mental Health of Content Reviewers, a Systematic Review

A Gonzalez, JN Matias - arxiv preprint arxiv:2502.00244, 2025 - arxiv.org
Artificial intelligence and social computing rely on hundreds of thousands of content
reviewers to classify high volumes of harmful and forbidden content. Many workers report …

Responsible Crowdsourcing for Responsible Generative AI: Engaging Crowds in AI Auditing and Evaluation

WH Deng, M Yurrita, M Díaz, J Suh, N Judd… - Proceedings of the …, 2024 - ojs.aaai.org
With the rise of generative AI (GenAI), there has been an increased need for participation by
large and diverse user bases in AI evaluation and auditing. GenAI developers are …

Relationships That Matter: Four Perspectives on AI, Work, and Organizations

D Narayan, B Shestakofsky - The Journal of Applied …, 2024 - journals.sagepub.com
The past decade has witnessed a surge of interest in how AI will transform work and
organizations, presenting scholars with the difficult task of studying emergent technologies …

Provocation: Who benefits from" inclusion" in Generative AI?

S Dalal, SM Hall, N Johnson - arxiv preprint arxiv:2411.09102, 2024 - arxiv.org
The demands for accurate and representative generative AI systems means there is an
increased demand on participatory evaluation structures. While these participatory …

Exploring Empty Spaces: Human-in-the-Loop Data Augmentation

C Yeh, D Ren, Y Assogba, D Moritz… - arxiv preprint arxiv …, 2024 - arxiv.org
Data augmentation is crucial to make machine learning models more robust and safe.
However, augmenting data can be challenging as it requires generating diverse data points …