AI Security Research Should Better Incentivize Defense Research

• URL: http://arxiv.org/abs/2605.23448v1
• Date: Fri, 22 May 2026 10:02:14 GMT
• Title: AI Security Research Should Better Incentivize Defense Research
• Abstract summary: This work examines an imbalance in artificial intelligence (AI) security research.<n>The field tends to produce more work on attacking AI systems than on defending them.<n>We argue that AI security research should better incentivize defense research.
• Score: 3.4567996484094086
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This work examines an imbalance in artificial intelligence (AI) security research: the field tends to produce more work on attacking AI systems than on defending them. Drawing on related academic papers, we find biased attack-to-defense ratios across subfields, including federated learning, speech recognition, membership inference, large language models, etc. The imbalance possibly means far beyond a simple count: attack papers are routinely evaluated under favorable conditions that make threats look more severe than they are in practice, while defenses are held to a stricter standard that few can meet. The result is a literature rich in demonstrated vulnerabilities and thin on usable and deployed protections. We thus argue that AI security research should better incentivize defense research.

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