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AI-powered autonomous weapons, operating with little or no human supervision, offer speed, scale and lower costs, but they also raise hard questions about who stays in control.<\/p>\n
In this selection of Strategist articles, authors look at how autonomous systems are being used on the battlefield and in the Australian Defence Force and at how they might shape the future of warfare.<\/p>\n
Autonomous drones are already on the front lines of the Russia\u2013Ukraine war, and both sides are locked in an arms race to make them more capable, writes David Kirichenko<\/a>.<\/p>\n Ukraine is equipping its uncrewed ground vehicles with AI-powered targeting, letting them spot enemy forces from farther away and more accurately. Also, Ukraine\u2019s mid-range drones, such as the Hornet, Darts and RAM-2X, use autonomous terminal lock guidance, making them more resistant to electromagnetic warfare.<\/p>\n Russia is following suit. Its Geran Seeker and Molniya strike drones are equipped with mesh networking and onboard AI for autonomous terminal guidance, and they\u2019re already widely deployed. Now \u2018robot versus robot battles are common\u2019, Kirichenko says. Ukraine\u2019s response? More robots.<\/p>\n In the near future, Ukrainian military planners envision autonomous robots leading assaults by clearing enemy positions before troops advance. Soldiers would rapidly deploy drones at a moment\u2019s notice to hunt Russian targets. Naval drones would lie in wait at sea, activated remotely before autonomously striking their targets. In long-range strikes, AI would fuse battlefield data, identify targets and calculate optimal flight paths, increasing the success of deep strikes inside Russia.<\/p>\n We in the Indo-Pacific can learn from some of this, writes Malcolm Davis<\/a>.<\/p>\n Reflecting on a panel at ASPI\u2019s June Defence Conference, Davis argues that the ADF\u2019s reliance on small numbers of costly crewed platforms is \u2018out of step\u2019 with the rapid innovation cycles of uncrewed systems. Rather than full autonomy, he makes the case for semi-autonomous systems that, if bought \u2018at low cost, in volume and at a rapid pace\u2019, could help the ADF build combat mass across the region\u2019s vast distances.<\/p>\n To keep pace with fast-moving operations where communications could be cut, the ADF may need to shift from keeping humans \u2018in the loop\u2019 to keeping them \u2018on the loop\u2019. Rather than remotely piloting drones, operators would only oversee what the machines do, leaving more decisions to AI.<\/p>\n For AUKUS, autonomy is also heading underwater. Writing with Justin Bassi<\/a>, Davis says that a project announced by Australia, Britain and the United States in May will give autonomous submarines such as Anduril\u2019s Ghost Shark the sensors and weapons they need to navigate, detect and attack. If the partners meet their 2027 delivery target \u2013 \u2018a big if\u2019 \u2013 AUKUS Pillar Two will move from research to operational military capability.<\/p>\n And that capability is badly needed. Australia must protect its subsea critical infrastructure \u2013 such as the 15 cables that carry almost all of its internet traffic.<\/p>\n The best way to do this is to patrol submarine cables with swarms of uncrewed autonomous vessels, freeing up crewed submarines to operate forward in our maritime approaches and beyond.<\/p>\n But the ADF must be careful not to integrate AI faster than it can govern it. \u2018AI is now financed across almost every line of the Australian defence budget,\u2019 writes Aina Turillazzi<\/a>. \u2018It is not, however, governed across them.\u2019<\/p>\n \u2018AI integration needs to happen,\u2019 she says. But Canberra should build in pauses for human review at key escalation points, audit AI\u2019s role in high-stakes choices, and commit publicly that AI won\u2019t be given final authority over the most consequential decisions. Without these safeguards, the people meant to oversee AI systems risk becoming little more than a rubber stamp.<\/p>\n AI systems are probabilistic and often opaque, and operators working under pressure tend to defer to their outputs \u2013 a dynamic known as automation bias. The human role drifts from assessing evidence to confirming a recommendation. That tendency sits awkwardly against the legal requirement for informed human judgement in targeting \u2026 and is exacerbated by the operational pressure to take humans out of the loop in pursuit of speed.<\/p>\n