Pentagon Docs: US Wants to "Suppress Dissenting Arguments" Using AI Propaganda

Summary

The United States hopes to use machine learning to create and distribute propaganda overseas in a bid to “influence foreign target audiences” and “suppress dissenting arguments,” according to a U.S. Special Operations Command document reviewed by The Intercept. The document, a sort of special operations wishlist of near-future military technology, reveals new details about a broad variety of capabilities that SOCOM hopes to purchase within the next five to seven years, including state-of-the-art cameras, sensors, directed energy weapons, and other gadgets to help operators find and kill their quarry. Among the tech it wants to procure is machine-learning software that can be used for information warfare. To bolster its “Advanced Technology Augmentations to Military Information Support Operations” — also known as MISO — SOCOM is looking for a contractor that can “Provide a capability leveraging agentic Al or multi‐LLM agent systems with specialized roles to increase the scale of influence operations.” So-called “agentic” systems use machine-learning models purported to operate with minimal human instruction or oversight. These systems can be used in conjunction with large language models, or LLMs, like ChatGPT, which generate text based on user prompts. While much marketing hype orbits around these agentic systems and LLMs for their potential to execute mundane tasks like online shopping and booking tickets, SOCOM believes the techniques could be well suited for running an autonomous propaganda outfit. “The information environment moves too fast for military remembers [sic] to adequately engage and influence an audience on the internet,” the document notes. “Having a program built to support our objectives can enable us to control narratives and influence audiences in real time.” Laws and Pentagon policy generally prohibit military propaganda campaigns from targeting U.S. audiences, but the porous nature of the internet makes that difficult to ensure. In a statement,...