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This argument is compatible and complimentary with a strong arms-control approach to the development and fielding of military AI, carving out a space of what more-responsible AI development looks like, to contrast with how military AI is at present. internationalpolicy.org/publications...

Davit Khachatryan is thorough on what coding for international humanitarian law will require, and the piece offers concrete recommendations for how to mandate accountability in military AI, rather than using it as a shield to obfuscate responsibility.

We can mandate higher standards for such AI use.

"Embedding the humane minimum into AI means that in every training run, whether through curated historical cases or artificially generated edge scenarios, the option that aligns with humane treatment under uncertainty must be given decisive weight."

"The way those objectives are weighted in the reward function is decisive. If mission success is rewarded heavily and civilian harm only lightly penalized, the AI will statistically favor the course of action that maximizes mission success, even if that means accepting higher risks to civilians."

"Left uncorrected, the AI may treat those lawful restraint decisions as statistical noise, unlikely to be repeated in practice."

internationalpolicy.org/publications...

Training machines to hesistate and hold fire when the laws of war demand it might be more a question of will than tech. As Davit Khachatryan argues, both imitation and reinforcement learning could oversample situations that mandate restraint.

internationalpolicy.org/publications...

Really happy to publish @wesinjapan.bsky.social at @cipolicy.bsky.social on the history and future of disaster response internationalpolicy.org/publications...

@w2t2impact.bsky.social reveals how the 1122 Program funneled over $100 million in military-style equipment and surveillance software to law enforcement at federal discounts, with minimal transparency or accountability.🔻

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