Secure Human Oversight of AI: Exploring the Attack Surface of Human Oversight

• URL: http://arxiv.org/abs/2509.12290v1
• Date: Mon, 15 Sep 2025 08:22:11 GMT
• Title: Secure Human Oversight of AI: Exploring the Attack Surface of Human Oversight
• Authors: Jonas C. Ditz, Veronika Lazar, Elmar Lichtmeß, Carola Plesch, Matthias Heck, Kevin Baum, Markus Langer,
• Abstract summary: We argue that human oversight creates a new attack surface within the safety, security, and accountability architecture of AI operations.<n>We provide an overview of attack vectors and hardening strategies to enable secure human oversight of AI.
• Score: 1.0847216718640382
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Human oversight of AI is promoted as a safeguard against risks such as inaccurate outputs, system malfunctions, or violations of fundamental rights, and is mandated in regulation like the European AI Act. Yet debates on human oversight have largely focused on its effectiveness, while overlooking a critical dimension: the security of human oversight. We argue that human oversight creates a new attack surface within the safety, security, and accountability architecture of AI operations. Drawing on cybersecurity perspectives, we analyze attack vectors that threaten the requirements of effective human oversight, thereby undermining the safety of AI operations. Such attacks may target the AI system, its communication with oversight personnel, or the personnel themselves. We then outline hardening strategies to mitigate these risks. Our contributions are: (1) introducing a security perspective on human oversight, and (2) providing an overview of attack vectors and hardening strategies to enable secure human oversight of AI.

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