In 1983, relations between the Soviet Union and the United States became tense after U.S. President Ronald Reagan called the Soviet Union an "evil empire" and spoke harshly about it. On September 26, 1983, the Soviet early-warning system showed signs of an attack, but the officer on duty, Stanislav Petrov, judged it to be a false alarm and chose not to report it as a real attack. That one decision may have saved millions of lives. In this article, I am going to find out whether AI could make nuclear crises more dangerous or help human leaders make better decisions and prevent a nuclear war. Nuclear deterrence simply means countries keep nuclear weapons so that no one dares to attack first, because they know they will be hit back. It only works if each side is confident about what the other is doing, and a false alarm can destroy that confidence.
To better understand the context of the 1983 crisis, you should read my article.
Read More: Able Archer 83: Why Moscow Feared a NATO War Game Was a Nuclear Attack
The Stanislav Petrov Incident
During the Stanislav Petrov incident on September 26, 1983, in the Cold War era, the world faced the danger of nuclear war. Petrov was a Soviet air defense officer working in an early-warning centre to monitor a possible American nuclear missile attack. One night, the Soviet early-warning system showed American nuclear missiles heading toward the Soviet Union. Petrov did not trust the computer immediately. He observed that if the Americans attacked, there would not be only a few missiles, but many, and he knew that computers could make mistakes. The warning was later found to be false because the satellite system had mistaken sunlight reflecting off high clouds for signs of missile launches (Korducki, 2026).
How AI Could Change Nuclear Decision Making Today
AI is very important in the current era. It can help with military coordination, surveillance, and target recognition, and it can also help process large amounts of information. However, the problem is that conventional and nuclear forces often use the same satellites and communication systems. So when conventional weapons are connected with AI, an attack on those systems could be seen as a threat to nuclear deterrence. AI automation can create problems, but that also depends on how leaders interpret what the system tells them. The following are a few points that I would like to share with you (Chernavskikh & Palayer, 2025, pp. 5–11).
- AI can get threats wrong or read an opponent’s intentions the wrong way, which can make leaders think an attack is about to happen when it is not.
- AI can also speed up decisions too much and push leaders to go along with recommendations without checking them properly, which raises the risk of escalation.
- AI may still help with threat assessment, but its results should be cross-checked against several sources, and humans should keep the final say.
Herbert Lin gives a more balanced view of AI. He does not say AI is automatically dangerous. Instead, he says the risks depend on how it is used and on a country’s nuclear strategy. In his view, AI could help with keeping nuclear weapons working before parts fail and with improving security by spotting unusual patterns when checking who has access to nuclear facilities. He also says AI can “improve and enhance human control over nuclear weapons”. But Lin also points out a serious problem. It would be very hard to verify international agreements that try to limit military AI, because countries can hide what their software is really made to do (Lin, 2025; U.S. Department of State, 1979).
On 9 November 1979, NORAD had a serious false alarm. A training tape was accidentally loaded into an active military computer at Cheyenne Mountain, and it showed what looked like a Soviet missile attack. Some bomber crews even moved to their aircraft while the threat was checked. But satellite data and radar did not confirm any launch, and officials realized within six minutes that the warning was false. Herbert Lin use this case to show an important point about AI: if a system depends too much on bad data, it can also mistake a false warning for a real attack. That is why AI warnings must always be checked against other evidence, and why human judgement still matters in nuclear decisions (Lin, 2025; U.S. Department of State, 1979).
AI may make nuclear decisions faster, but faster is not the same as better. The Petrov incident in 1983 and the NORAD false alarm in 1979 both show how false information can quickly become dangerous when tensions are high. In both cases, people stopped the mistake by double-checking. AI can help spot threats and sort through huge amounts of data, but it becomes risky if leaders accept its advice without checking it. In the end, AI should help human judgement, not replace it, especially when the decision could lead to nuclear war.
References
Jenkins, P. (2021). The new struggle. In A global history of the Cold War, 1945–1991 (pp. 213–227). Palgrave Macmillan
Korducki, K. M. (2026, March 17). The man who helped avert nuclear Armageddon. HISTORY. https://www.history.com/articles/nuclear-attack-warning-cold-war-petrov
Chernavskikh, V., & Palayer, J. (2025, June). Impact of military artificial intelligence on nuclear escalation risk (SIPRI Insights on Peace and Security No. 2025/06). Stockholm International Peace Research Institute.
Lin, H. S. (2025). Artificial intelligence and nuclear weapons: A commonsense approach to understanding costs and benefits. Texas National Security Review, 8(3), 98–109. https://doi.org/10.26153/tsw/60739
Brown, H. (1979, November 20). Memorandum from Secretary of Defense Brown to President Carter: NORAD false alarm. Office of the Historian, U.S. Department of State. https://history.state.gov/historicaldocuments/frus1977-80v04/d167