mlsanityData to 13 Oct 2026

Effective Automation to Support the Human Infrastructure in AI Red Teaming

arXiv 2503.22116 ↗First posted 28 Mar 2025cs.CY cs.HCcited by 3

Not on the map. Why?

Abstract (arXiv)

As artificial intelligence (AI) systems become increasingly embedded in critical societal functions, the need for robust red teaming methodologies continues to grow. In this forum piece, we examine emerging approaches to automating AI red teaming, with a particular focus on how the application of automated methods affects human-driven efforts. We discuss the role of labor in automated red teaming processes, the benefits and limitations of automation, and its broader implications for AI safety and labor practices. Drawing on existing frameworks and case studies, we argue for a balanced approach that combines human expertise with automated tools to strengthen AI risk assessment. Finally, we highlight key challenges in scaling automated red teaming, including considerations around worker proficiency, agency, and context-awareness.

Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). First posted on arXiv 28 Mar 2025.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2024AI red-teaming is a sociotechnical problem: on values, labor, and harms
  2. 2024The Human Factor in AI Red Teaming: Perspectives from Social and Collaborative Computing
  3. 2025Organization Matters: A Qualitative Study of Organizational Dynamics in Red Teaming Practices for Generative AI
  4. 2025OpenAI's Approach to External Red Teaming for AI Models and Systems
  5. 2025Red Teaming AI Red Teaming
  6. 2025The Automation Advantage in AI Red Teaming
  7. 2024Red-Teaming for Generative AI: Silver Bullet or Security Theater?
  8. 2026Governing Execution Risk in Agentic AI Systems: A Trajectory-Guided Framework for Red Teaming