The Human Factor in AI Red Teaming: Perspectives from Social and Collaborative Computing
On the map: LLM safety and security → Prompt injection and agent security
Abstract (arXiv)
Rapid progress in general-purpose AI has sparked significant interest in "red teaming," a practice of adversarial testing originating in military and cybersecurity applications. AI red teaming raises many questions about the human factor, such as how red teamers are selected, biases and blindspots in how tests are conducted, and harmful content's psychological effects on red teamers. A growing body of HCI and CSCW literature examines related practices-including data labeling, content moderation, and algorithmic auditing. However, few, if any have investigated red teaming itself. Future studies may explore topics ranging from fairness to mental health and other areas of potential harm. We aim to facilitate a community of researchers and practitioners who can begin to meet these challenges with creativity, innovation, and thoughtful reflection.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Placed in Prompt injection and agent security, one of 12 directions in LLM safety and security. Builds on 3 of its 25 references that are in the map. First posted on arXiv 10 Jul 2024.
Builds on
3 of 25 references.
References · 3
Built on by
Citing papers per year: 2024: 4; 2025: 2; 2026: 2.
8 papers.
- 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Surveycited by 15
- 2024Exploring Empty Spaces: Human-in-the-Loop Data Augmentationcited by 6
- 2024Provocation: Who benefits from "inclusion" in Generative AI?cited by 3
- 2025From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teamingcited by 2
- 2024AI red-teaming is a sociotechnical problem: on values, labor, and harmscited by 0
- 2025A Conceptual Framework for AI Capability Evaluationscited by 0
- 2026Red Teaming LLMs as Socio-Technical Practice: From Exploration and Data Creation to Evaluationcited by 0
- 2026Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safetycited by 0
- 2026Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety9 Jun 2026
- 2026Red Teaming LLMs as Socio-Technical Practice: From Exploration and Data Creation to Evaluation10 Feb 2026
- 2025From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teaming14 Sep 2025
- 2025A Conceptual Framework for AI Capability Evaluations23 Jun 2025
- 2024AI red-teaming is a sociotechnical problem: on values, labor, and harms12 Dec 2024
- 2024Provocation: Who benefits from "inclusion" in Generative AI?14 Nov 2024
- 2024Exploring Empty Spaces: Human-in-the-Loop Data Augmentation1 Oct 2024
- 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Survey11 Jul 2024