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

2025-09-15

AI Summary

This paper identifies human oversight itself as a novel attack surface in AI safety: while serving as a critical safeguard against erroneous AI outputs, system failures, and rights violations, oversight mechanisms are vulnerable to exploitation via system vulnerabilities, communication hijacking, or social engineering—thereby undermining AI security, assurance, and accountability. Adopting a cybersecurity lens, we systematically classify three distinct threat vectors targeting (1) AI systems, (2) human-AI interaction channels, and (3) human supervisors. Integrating principles from cybersecurity theory and AI governance frameworks, we propose a comprehensive defense strategy. Central to this is the “oversight-as-infrastructure” paradigm, which formalizes risk taxonomy and mitigation pathways. Our work establishes both theoretical foundations and actionable guidelines for designing robust, attack-resilient human oversight mechanisms in AI systems. (149 words)

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Other Foundations of Human Computation & AI
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Security and Privacy: Security and privacy of machine learning and AI applications

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.

Problem

• Analyzing attack vectors threatening secure human oversight of AI
• Exploring cybersecurity risks in AI human oversight mechanisms
• Proposing hardening strategies to mitigate oversight security vulnerabilities

Innovation

• Analyzing attack vectors on oversight
• Hardening strategies for secure oversight
• Security perspective on human oversight