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AI and the New World of Spying and Fighting

The world’s intelligence agencies and militaries are, not surprisingly, the furthest ahead in developing artificial intelligence (AI) – spending vast sums of money attempting to better understand how and why intelligent machines end up operating the way they do. In spite (or perhaps, because of) the dramatic progress that is being made by integrating AI into the realm of government, and the degree to which AI is having an impact on such a broad range of industries and sectors, some practitioners and thought leaders worry about its future implications.

AI will probably never possess the type of nuance, intuition, and gut instinct necessary to be a good intelligence analyst, so perhaps those working in the intelligence community can rest easier than those in manufacturing and other industries, but the truth is, the jury will essentially be out on that question until AI has been sufficiently developed to determine whether it is indeed capable of acting based on gut instinct and intuition.

An equally vexing concern is whether AI is being deployed with sufficient vigor to keep pace with a given country’s adversaries are doing the same. For example, China and Russia have had a free hand to apply the technology unburdened by concerns about privacy, civil rights, or degrees of presumed acceptability. China has excelled at developing AI via a vast number of well-trained computer engineers who program machines using an unrivaled amount of data, produced by the country’s 1.4 billion people. Russia has little hesitation about what kinds of instruments of war it connects to AI, including the military’s development of armed and unmanned vehicles (similar to a ground-based drones) – something the US has hesitated to pursue.

The US sees AI principally as a national security tool to be employed on the battlefield or to thwart terrorist attacks, and trails both countries in some aspects of the development of deployable machines. The manner in which it allocates and spends defense dollars tends to be slow and cumbersome – not conducive to speed or efficiency. That has hobbled the US from reacting swiftly, effectively, or proactively in response to cyberattacks, and has generally thwarted the development of cutting edge AI tools.

That said, US researchers have trained Deep Learning algorithms to identify Chinese surface-to-air missile sites hundreds of times faster than their human counterparts. The algorithms proved capable of assisting individuals with no prior imagery analysis experience find the missile sites scattered across nearly 90,000 square kilometers of southeastern China. The neural network that was used matched the 90% accuracy of expert human imagery analysts in locating the missile sites while helping humans reduce the time needed to analyze potential missile sites from 60 hours to just 42 minutes. This comes at a time when satellite imagery analysts are drowning in a deluge of Big Data.

Although it is not in doubt that AI is going to be part of the future of militaries around the world, the landscape is changing quickly and in potentially disruptive ways. Given the challenge of feeding machines with knowledge and expert-based behaviors, as well as limitations in perception sensors, it will be many years before AI will be able to truly approximate human intelligence in high-uncertainty settings – as epitomized by the fog of war.

AI and robotics — the forces that are ushering in the era of “hyperwar” — already allow for asymmetric responses that are inexpensive, resilient, and globally scalable. AI technologies such as natural language-based dialog systems consume enormous amounts of information to augment human operators in non-combat situations, such as for maintenance and the remediation of equipment. Such capabilities will eventually be augmented by reality-based information-delivery technologies in combat scenarios.

At the operational level, commanders will be able to “sense,” “see,” and engage enemy formations far more quickly by applying machine learning algorithms to collection and analysis of huge quantities of information and directing swarms of complex, autonomous systems to simultaneously attack the enemy. At the strategic level, the commander supported by this capacity “sees” the strategic environment through sensors operating across the entire operational theater. The strategic commander’s capacity to ingest petabytes of information and conduct near-instantaneous analysis – ranging from national technical means to tactical systems – provides a qualitatively unsurpassed level of situational awareness and understanding previously unavailable to strategic commanders.

Although the “big three” nations – China, Russia, and US – are clearly the leaders in the development of AI for intelligence and military applications, there are real contrasts between how each use and deploy AI. The US is believed to have a substantial lead in the application of AI in both arenas, but both China and Russia are investing heavily in the space, with the ambition to become the global leaders. China has already declared its intention to be the world leader in AI by 2030.

America’s adversaries have been betting that a new wave of weapons will negate technologies and tactics at the heart of US military might, among them aircraft carriers and high-altitude missile Russia’s interest is already well established, with the Russian military having deployed AI capable of conducting independent military operations in Syria. Russia is preparing to fight on a roboticized battlefield in the near term, wielding anti-tank weapons, grenade launchers, and assault rifles.

Russia is clearly well advanced on the path toward developing the next generation of autonomous military weapons, and China is following a similar path, aggressively testing hypersonic weapons, unmanned aircraft, and advanced submarine detection, among other capabilities. China has built up a significant satellite manufacturing industry and has managed to develop quantum communications spacecraft with advanced encryption features. China will have major advantages in translating private sector gains in the AI arena into national security applications, given the heavy integration of government in all aspects of the Chinese economy.

The intelligence community’s challenge is to improve source collection across platforms and domains without becoming overwhelmed. Likewise, the military’s challenge is to exercise the same type of restraint it exercised in the US vis-à-vis the development of bioweaponry as it leaps further into the development of the next generation of AI-powered weapons. It is perhaps too fanciful to imagine that other nations would pursue their AI-driven ambitions in a similarly responsible manner, but the world would certainly be better off in the long-term if they did.