arXiv:2606.11150v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly acquiring capabilities relevant to biological research, from literature synthesis to interpretation of experimental data. Increasingly, LLM agents can also perform in silico biology tasks that previously required experienced human biologists. These emerging AI capabilities offer new opportunities for scientific discovery and biomedical advances, but they also shift the landscape of biosecurity risks. To address this, we introduce the Agentic Bio-Capabilities Benchmark (ABC-Bench), a suite of tasks to measu
The rapid advancement in large language model capabilities necessitates new benchmarks to assess emergent risks, especially in sensitive domains like biological research.
This benchmark highlights the critical need to evaluate and mitigate biosecurity risks posed by increasingly capable AI agents, which can perform complex biological tasks.
The introduction of ABC-Bench provides a structured way to measure and monitor the bio-capabilities of AI agents, shifting biosecurity from reactive measures to proactive assessment.
- · Biosecurity researchers
- · AI safety institutions
- · Governing bodies
- · Hostile state actors
- · Non-state actors (bioterrorism)
- · Unregulated AI development
ABC-Bench will enable more systematic evaluation and mitigation of AI-driven biosecurity risks.
Increased scrutiny and regulation on AI models with biological capabilities could lead to more controlled development environments.
The benchmark could become a global standard, influencing international policy on AI and biological research.
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Read at arXiv cs.AI