31. AI and the Evolution of Biological National Security Risks: Capabilities, Thresholds, and Interventions
- Author:
- Bill Drexel and Caleb Withers
- Publication Date:
- 08-2024
- Content Type:
- Special Report
- Institution:
- Center for a New American Security (CNAS)
- Abstract:
- Not long after COVID-19 gave the world a glimpse of the catastrophic potential of biological events, experts began warning that rapid advancements in artificial intelligence (AI) could augur a world of bioterrorism, unprecedented superviruses, and novel targeted bioweapons. These dire warnings have risen to the highest levels of industry and government, from the CEOs of the world's leading AI labs raising alarms about new technical capabilities for would-be bioterrorists, to Vice President Kamala Harris’s concern that AI-enabled bioweapons “could endanger the very existence of humanity.”1 If true, such developments would expose the United States to unprecedented catastrophic threats well beyond COVID-19’s scope of destruction. But assessing the degree to which these concerns are warranted—and what to do about them—requires weighing a range of complex factors, including: The history and current state of American biosecurity The diverse ways in which AI could alter existing biosecurity risks Which emerging technical AI capabilities would impact these risks Where interventions today are needed This report considers these factors to provide policymakers with a broad understanding of the evolving intersection of AI and biotechnology, along with actionable recommendations to curb the worst risks to national security from biological threats. The sources of catastrophic biological risks are varied. Historically, policymakers have underappreciated the risks posed by the routine activities of well-intentioned scientists, even as the number of high-risk biosecurity labs and the frequency of dangerous incidents—perhaps including COVID-19 itself—continue to grow. State actors have traditionally been a source of considerable biosecurity risk, not least the Soviet Union’s shockingly large bioweapons program. But the unwieldiness and imprecision of bioweapons has meant that states remain unlikely to field large-scale biological attacks in the near term, even though the U.S. State Department expresses concerns about the potential bioweapons capabilities of North Korea, Iran, Russia, and China. On the other hand, nonstate actors—including lone wolves, terrorists, and apocalyptic groups—have an unnerving track record of attempting biological attacks, but with limited success due to the intrinsic complexity of building and wielding such delicate capabilities. Today, fast-moving advancements in biotechnology—independent of AI developments—are changing many of these risks. A combination of new gene editing techniques, gene sequencing methods, and DNA synthesis tools is opening a new world of possibilities in synthetic biology for greater precision in genetic manipulation and, with it, a new world of risks from the development of powerful bioweapons and biological accidents alike. Cloud labs, which conduct experiments on others’ behalf, could enable nonstate actors by allowing them to outsource some of the experimental expertise that has historically acted as a barrier to dangerous uses. Though most cloud labs screen orders for malicious activity, not all do, and the constellation of existing bioweapons norms, conventions, and safeguards leaves open a range of pathways for bad actors to make significant progress in acquiring viable bioweapons. But experts’ opinions on the overall state of U.S. biosecurity range widely, especially with regard to fears of nonstate actors fielding bioweapons. Those less concerned contend that even if viable paths to building bioweapons exist, the practicalities of constructing, storing, and disseminating them are far more complex than most realize, with numerous potential points of failure that concerned parties either fail to recognize or underemphasize. They also point to a lack of a major bioattacks in recent decades, despite chronic warnings. A more pessimistic camp points to experiments that have demonstrated the seeming ease of successfully constructing powerful viruses using commercially available inputs, and seemingly diminishing barriers to the knowledge and technical capabilities needed to create bioweapons. Less controversial is the insufficiency of U.S. biodefenses to adequately address large-scale biological threats, whether naturally occurring, accidental, or deliberate. Despite COVID-19’s demonstration of the U.S. government’s inability to contain the effects of a major outbreak, the nation has made limited progress in mitigating the likelihood and potential harm of another, more dangerous biological catastrophe. New AI capabilities may reshape the risk landscape for biothreats in several ways. AI is enabling new capabilities that might, in theory, allow advanced actors to optimize bioweapons for more precise effects, such as targeting specific genetic groups or geographies. Though such capabilities remain speculative, if realized they would dramatically alter states’ incentives to use bioweapons for strategic ends. Instead of risking their own militaries’ or populations’ health with the unwieldy weapons, states could sabotage other nations’ food security or incapacitate enemies with public health crises from which they would be unlikely to rebound. Relatedly, the same techniques could create superviruses optimized for transmissibility and lethality, which may considerably expand the destructive potential of bioweapons. Tempering these fears, however, are several technical challenges that scientists would need to overcome—if they can be solved at all. The most pressing concern for biological risks related to AI stems from tools that may soon be able to accelerate the procurement of biological agents by nonstate actors. Recent studies have suggested that foundation models may soon be able to help accelerate bad actors’ ability to acquire weaponizable biological agents, even if the degree to which these AI tools can currently help them remains marginal.2 Of particular concern are AI systems’ budding abilities to help troubleshoot where experiments have gone wrong, speeding the design-build-test-learn feedback loop that is essential to developing working biological agents. If made more effective, emerging AI tools could provide a boon to would-be bioweapons creators by more dynamically providing some of the knowledge needed to produce and use bioweapons, though such actors would still face other significant hurdles to bioweapons development that are often underappreciated. AI could also impact biological risks in other ways. Technical faults in AI tools could fail to constrain foundation models from relaying hazardous biological information to potential bad actors, or inadvertently encourage researchers to pursue promising medicinal agents with unexpected negative side effects. Using AI to create more advanced automated labs could expose these labs to many of the risks of automation that have historically plagued other complex automated systems, and make it easier for nonspecialists to concoct biological agents (depending upon the safety mechanisms that automated labs institute). Finally, heavy investment in companies and nations seeking to capitalize on AI’s potential for biotechnology could be creating competition dynamics that prioritize speed over safety. These risks are particularly acute in relation to China, where a variety of other factors shaping the country’s biotech ecosystem also further escalate risks of costly accidents.
- Topic:
- Security, National Security, Biosecurity, Artificial Intelligence, and COVID-19
- Political Geography:
- Global Focus