Nuclear command systems have confronted false alarm risks throughout their existence. The September 1983 Soviet early warning incident demonstrated these dangers when the Oko satellite system erroneously detected five American intercontinental ballistic missiles launching toward the Soviet Union. Lieutenant Colonel Stanislav Petrov determined the alert was spurious, preventing what could have escalated into catastrophic nuclear exchange. The Soviet system had mistaken sunlight reflecting off clouds for incoming missiles.
Artificial intelligence introduces novel vulnerabilities to nuclear stability beyond the widely discussed concern of autonomous launch authority. The 2022 Nuclear Posture Review affirmed that United States will maintain “human in the loop” for decisions involving nuclear weapons employment. President Biden and President Xi Jinping agreed in November 2024 that human beings should control nuclear weapons decisions rather than artificial intelligence. Yet AI poses different threats through its capacity to generate convincing false information—deepfakes—that could influence critical security assessments.
Synthetic Media and Strategic Decision-Making
Deepfake technologies have achieved concerning sophistication. In March 2022, a manipulated video showed Ukrainian President Volodymyr Zelensky apparently telling citizens to surrender weapons. Hackers uploaded the footage to Ukraine 24’s website and television news ticker. While this particular deepfake was poorly executed and quickly debunked, it demonstrated how synthetic media combined with compromised communications infrastructure could spread disinformation from seemingly authoritative sources.
Similar fabricated videos involving Russian President Vladimir Putin circulated during the conflict. Research indicates deepfakes undermine trust in authentic media, with some individuals falsely accusing genuine footage of manipulation. This erosion of information reliability creates particular dangers when time-pressured nuclear decisions require rapid verification.
Under current doctrines, both American and Russian forces maintain launch-on-warning capabilities, permitting deployment once hostile missiles are detected approaching. Such postures leave mere minutes for leadership to evaluate whether attacks have commenced. Officials must verify threats using classified intelligence sources alongside open information including satellite imagery, foreign leader statements, social media and news reports. Military personnel and advisers then determine which information reaches decision-makers and how data is presented.
AI-Enabled False Positives and Cognitive Biases
Artificial intelligence systems integrated into early warning infrastructure could hallucinate threats that do not exist, creating situations analogous to what Petrov faced decades ago. Because AI decision logic remains opaque, humans often cannot discern why systems reached particular conclusions. Research demonstrates people with moderate AI familiarity tend to defer to machine outputs rather than checking for biases or false positives, even regarding national security matters. Without extensive training and procedures accounting for AI weaknesses, White House advisers might assume or entertain possibilities that AI-generated content is accurate.
Deepfakes transmitted through open-source media present nearly equivalent dangers. An American leader viewing fabricated footage might misinterpret Russian missile tests as offensive strikes or mistake Chinese military exercises for attacks on allies. Synthetic media could establish pretexts for conflict, mobilize public support for military action, or generate confusion during crises.
Application Domains and Technical Limitations
AI technologies have demonstrated utility enhancing military efficiency. Machine learning facilitates maintenance scheduling for naval vessels. Autonomous munitions allow personnel to operate at safer distances from combat zones. Translation tools help intelligence officers process foreign information. AI could assist certain intelligence collection tasks such as identifying differences in bomber deployment patterns across sequential images.
However, certain domains should remain off-limits for AI integration due to risks outweighing potential benefits. Nuclear early warning systems and command structures lack comprehensive datasets because no nuclear attacks have occurred since Hiroshima and Nagasaki. Any AI detection system would require training on existing missile test data, space tracking information, and synthetic datasets. Engineers would need to program defenses against hallucinations and inaccurate confidence assessments—significant technical hurdles given current capabilities.
Removing critical human oversight from automated systems creates error risks. The Department of Defense requires meaningful human control over autonomous weapons platforms. Even higher standards should apply to nuclear early warning and intelligence technologies. AI data integration tools should not replace human operators reporting incoming ballistic missiles. Efforts confirming nuclear launch warnings from satellite or radar data should remain only partially automated.
Policy Recommendations and Risk Mitigation
Intelligence agencies must improve tracking of AI-derived information provenance and standardize how they communicate when data is augmented or synthetic. The National Geospatial-Intelligence Agency adds disclosure statements to reports containing machine-generated intelligence. Analysts, policymakers and staffs require training to apply additional skepticism toward content not immediately verifiable, similar to vigilance against cyber phishing attacks. Intelligence organizations need policymaker trust, as leaders might believe what their devices show them—accurate or false—rather than intelligence assessments.
Experts and technologists should continue developing methods to label and slow fraudulent information flowing through social media that influences policymakers. Given difficulties policing open-source information, classified intelligence accuracy becomes even more critical.
Nuclear weapons states should agree humans will make launch decisions. Then they should improve crisis communication channels. A hotline exists between Washington and Moscow but not between Washington and Beijing. Such mechanisms become more crucial as machine-generated misinformation proliferates.
United States nuclear policy has changed minimally since the 1980s when strategists worried about Soviet surprise attacks. Policymakers then could not anticipate misinformation volumes delivered to personal devices of officials controlling nuclear arsenals today. Both legislative and executive branches should reevaluate nuclear posture policies built for Cold War contexts. Congress might require future presidents to confer with congressional leaders before launching first strikes or mandate periods for intelligence professionals to validate decision information. Because the United States maintains capable second-strike options, accuracy should take precedence over speed.
Artificial intelligence already possesses potential to deceive key decision-makers and nuclear chain participants into perceiving attacks that are not occurring. Historically, only authentic dialogue and diplomacy averted misunderstandings among nuclear-armed states. Policies and practices must protect against pernicious information risks that could ultimately lead to catastrophic outcomes.
Original analysis by Erin D. Dumbacher for Foreign Affairs. Republished with additional research and verification by ThinkTanksMonitor.
