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ARTIFICIAL INTELLIGENCE, AUTONOMY, AND THE RISK OF CATALYTIC NUCLEAR WAR

ARTIFICIAL INTELLIGENCE, AUTONOMY, AND THE RISK OF CATALYTIC NUCLEAR WAR, Modern War Institute, 

James Johnson | 03.18.21    Editor’s note: The following is based on an article by the author recently published in the Journal of Strategic Studies, entitled “‘Catalytic Nuclear War’ in the Age of Artificial Intelligence & Autonomy: Emerging Military Technology and Escalation Risk between Nuclear-Armed States.”

In 2016, the AWD News site reported that Israel had threatened to attack Pakistan with nuclear weapons if Islamabad interfered in Syria. In response, Pakistani Defense Minister Khawaja Muhammad Asif issued a thinly veiled threat. On Twitter he warned Israel to remember that Pakistan—like Israel—is a nuclear-armed state. Luckily, the report was false, and it was subsequently debunked as fictitious by the Israeli Ministry of Defense.

This incident puts a modern, and alarming, spin on the concept of “catalytic nuclear war”—in which third-party (a state or nonstate actor) actions provoke a nuclear war between two nuclear-armed powers—and demonstrates the potentially severe damage caused by the misinformation and manipulation of information by a third party. During the Cold War, the main concern about “catalytic nuclear war” centered on the fear that a small or new nuclear power would deliberately set a major exchange in motion between the United States and the Soviet Union. As its name suggests, the concept was inspired by chemical reactions where the catalyzing agent (a third-party actor) would remain unscathed by its initiated process. As we know, however, a catalytic nuclear war never occurred.

In the digital era, the catalyzing chain of reaction and counter-retaliation dynamics set in motion by a third-party actor’s deliberate action is fast becoming a more plausible scenario. The concept of catalytic nuclear war—considered by many as unlikely given the low probability of a terrorist group gaining access to nuclear weapons—should be revisited in light of recent technological change and improved understanding of human psychology. Specifically, the human propensity for making fast, intuitive, reflexive, and heuristic judgments (known as “System I” thinking), which is exacerbated when information overload and unfamiliar technologies are more prominent features of decision making. In short, emerging technologies—most notably cyber, AI technology, and drones—are rapidly creating new (and exacerbating old) low-cost and relatively easy means for state and nonstate actors to fulfill their nefarious goals. This is compounded by the exponential rise in data emerging from today’s information ecosystem—and in the speed with which it does so—which will create novel attack pathways to manipulate and propagate misinformation and disinformation during crisis times.

Emerging Technology and Nuclear Stability……………….

Risk of Catalytic Nuclear War in the Digital Age

Three features of the digital age—information complexity; greater automation of nuclear command, control, and communication systems; and mis- and disinformation—make nuclear crisis management more difficult than in the past. These variables do not, however, constitute mutually exclusive risk scenarios. Rather, the interplay between these conditions might allow them to feed into one another with uncertain and potentially self-reinforcing effects. In short, these conditions are a function of the confusion and uncertainty created by the sociotechnical complexity generated in the digital age.        

Information Complexity

As nuclear states (notably the United States, Russia, and China) modernize and overhaul their outdated nuclear command-and-control systems there are a multitude of challenges to consider, including information warfare, information manipulation, comingled nuclear and conventional weapons systems, and the risks posed by cyberattacks.…………..https://mwi.usma.edu/artificial-intelligence-autonomy-and-the-risk-of-catalytic-nuclear-war/

March 29, 2021 - Posted by Christina Macpherson | Uncategorized