AI systems used for military targeting are highly susceptible to GIGO (Garbage In, Garbage Out). The accidental strike on a school in Iran, caused by an outdated DIA database, demonstrates that even sophisticated AI can produce catastrophic results if the underlying data is not meticulously and continuously vetted by humans.

Instead of automating decisions, the Pentagon's AI strategy focuses on synthesizing vast amounts of data—assets, weather, potential reactions—to expand a human operator's situational awareness, enabling them to make better, more informed choices.

The military doesn't need to invent safety protocols for AI from scratch. Its deeply ingrained culture of checks and balances, rigorous training, rules of engagement, and hierarchical approvals serve as powerful, pre-existing guardrails against the risks of imperfect autonomous systems.

Defense tech firm Smack Technologies clarifies the objective is not to remove humans entirely. Instead, AI should handle low-value tasks to free up personnel for critical, high-value decisions. This framework, 'intelligent autonomy,' orchestrates manned and unmanned systems while keeping humans in the loop.

Contrary to the perception of AI in warfare as a future concept, Anthropic's Claude AI is already integral to U.S. military operations. It was actively used for intelligence assessment, target identification, and battle simulations in the recent Middle East air strikes.

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.

Countering the idea that slow, manual processes add valuable friction to warfare decisions, the Pentagon's view is that AI maintains critical checks and balances (rules of engagement, approvals). It only removes the inefficient friction of "hunting and pecking" for data, leading to faster and better-informed decisions.

In operations, AI models like Anthropic's Claude are used for intelligence analysis, summarizing media chatter, and running simulations to aid commanders. They are not used for autonomous targeting; any outputs go through layers of human review before influencing battlefield decisions.