Considerations Influencing Offense-Defense Dynamics From Artificial Intelligence

TL;DR

This paper explores how AI's dual role in enhancing security and enabling threats impacts societal safety, proposing a taxonomy to understand the factors influencing whether AI acts as a protector or a threat.

Contribution

It introduces a taxonomy and shared terminology for analyzing offense-defense dynamics of AI, aiding future research and policy discussions.

Findings

Developed a taxonomy for AI offense-defense dynamics

Established a shared conceptual framework for analysis

Facilitated understanding of AI's dual societal roles

Abstract

The rapid advancement of artificial intelligence (AI) technologies presents profound challenges to societal safety. As AI systems become more capable, accessible, and integrated into critical services, the dual nature of their potential is increasingly clear. While AI can enhance defensive capabilities in areas like threat detection, risk assessment, and automated security operations, it also presents avenues for malicious exploitation and large-scale societal harm, for example through automated influence operations and cyber attacks. Understanding the dynamics that shape AI's capacity to both cause harm and enhance protective measures is essential for informed decision-making regarding the deployment, use, and integration of advanced AI systems. This paper builds on recent work on offense-defense dynamics within the realm of AI, proposing a taxonomy to map and examine the key factors that influence whether AI systems predominantly pose threats or offer protective benefits to society. By establishing a shared terminology and conceptual foundation for analyzing these interactions, this work seeks to facilitate further research and discourse in this critical area.