The requirement for human responsibility in the use of force is not a new concept created for AI. It is governed by long-standing international humanitarian law and existing military policies. These foundational legal structures apply to all weapons, from bows to AI-drones, ensuring a commander is always accountable.

Counterintuitively, Anduril views AI and autonomy not as an ethical liability, but as a way to better adhere to the ancient principles of Just War Theory. The goal is to increase precision and discrimination, reducing collateral damage and removing humans from dangerous jobs, thereby making warfare *more* ethical.

Debates over systems like Israel's 'Lavender' often focus on the AI. However, the more critical issue may be the human-defined 'rules of engagement'—specifically, what level of algorithmic confidence (e.g., 55% accuracy) leadership deems acceptable to authorize a strike. This is a policy problem, not just a technology one.

To prevent a scenario where 'the algorithm did it,' the U.S. military relies on the legal principle of 'human responsibility for the use of force.' This ensures a specific commander is always accountable for deploying any weapon, autonomous or not, sidestepping the accountability gap that worries AI ethicists.

While fears focus on tactical "killer robots," the more plausible danger is automation bias at the strategic level. Senior leaders, lacking deep technical understanding, might overly trust AI-generated war plans, leading to catastrophic miscalculations about a war's ease or outcome.

We typically view an AI acting on its own values as 'misalignment' and a failure. However, this capability could be a crucial safeguard. Just as human soldiers have prevented atrocities by refusing immoral orders, an AI with a robust sense of morality could refuse to execute harmful commands, acting as a check on human power and preventing disasters.

Contrary to the 'killer robots' narrative, the military is cautious when integrating new AI. Because system failures can be lethal, testing and evaluation standards are far stricter than in the commercial sector. This conservatism is driven by warfighters who need tools to work flawlessly.

Countering the common narrative, Anduril views AI in defense as the next step in Just War Theory. The goal is to enhance accuracy, reduce collateral damage, and take soldiers out of harm's way. This continues a historical military trend away from indiscriminate lethality towards surgical precision.

The policy of keeping a human decision-maker 'in the loop' for military AI is a potential failure point. If the human operator is not meaningfully engaged and simply accepts AI-generated recommendations without critical oversight or due diligence, the system is de facto autonomous, creating a false sense of security and accountability.