Source: UN
President Donald J. Trump on Sept. 23rd pledged that the United States would lead a global effort to strengthen safeguards against biological weapons, telling the United Nations General Assembly that his administration would spearhead the creation of an artificial intelligence–based verification system to enforce the Biological Weapons Convention.
“My administration will lead an international effort to enforce the biological weapons convention,” Mr. Trump said. “We will do so by pioneering an AI verification system that everyone can trust.” His remarks reflected Washington’s ambition to harness cutting-edge technologies to confront the rising risk of engineered pathogens.
An American Tradition of Leadership
The United States has long sought to place itself at the forefront of biological arms control. In 1969, it formally renounced any offensive biological weapons program; in 1975, it helped bring the Biological Weapons Convention into force. Today, nearly 190 nations are parties to the treaty, and the U.S. has consistently pressed to adapt it to new scientific and technological challenges.
In August, this year, during the Sixth Session of the Working Group on Strengthening the Convention in Geneva, the U.S. again assumed a prominent role. American negotiators pushed for stronger verification, greater transparency, and deeper cooperation to confront emerging biotechnological threats. They backed legally binding compliance provisions, capacity-building initiatives, and expanded confidence-building measures (CBMs), all aimed at updating the treaty for contemporary biological risks. That leadership not only generated momentum toward consensus but also produced tangible steps to reinforce global security and public health amid rapid advances in synthetic biology and AI. Looking ahead, Mr. Trump’s AI initiative is expected to be a centerpiece of debate at the 2026 BWC Review Conference, where states parties will weigh its potential role in shaping the future of biological arms control.
AI Verification as a Safeguard
The risk landscape at the intersection of AI and synthetic biology is changing rapidly. Tools originally developed for protein engineering or drug discovery are increasingly able to model novel toxins or design pathogens, lowering barriers to misuse. With the aid of large language models, even individuals with little biological training could, in theory, create harmful agents or evade conventional biosecurity measures. Such possibilities highlight the vulnerabilities that legitimate research faces in monitoring immune evasion, gene editing, and transmissibility.
Against this backdrop, the system outlined by Mr. Trump represents a shift from traditional state-centered inspections toward a networked, data-driven model. By leveraging artificial intelligence to analyze research data, genetic sequences, and biotechnology transactions, the platform is designed to detect suspicious activity that might indicate the development or stockpiling of biological weapons. In practice, it would operate as a cloud-based network, integrating existing biosurveillance databases and research registries, and using machine learning to flag anomalies in real time.
The U.S. Defense Threat Reduction Agency’s Biosurveillance Ecosystem (BSVE) offers a preview of how such a system could function globally. For example, when an unusual spike in respiratory illness appears in a metropolitan area, BSVE enables analysts to quickly identify outbreak patterns, assess severity, and coordinate responses with local health authorities. It does so by ingesting diverse data streams—from social media posts and news reports to diagnostic results and historical outbreak records—and applying machine learning and natural language processing to detect anomalies. Those insights are then visualized on an analyst dashboard, providing an opportunity for early intervention before localized outbreaks spiral into full epidemics.