The U.S. military enlisted natural language processing to combat disinformation.

What’s new: Primer, a San Francisco startup, is developing a system for the Department of Defense that sifts through news, social media, research, and reports to spot propaganda campaigns. The system is scheduled for deployment in June 2021. The company specializes in NLP models like the multi-document summarizer illustrated above.

How it works: The disinformation detector uses a modified XLNet to classify nouns in a given article as people, places, organizations, or miscellaneous. The model was trained on CoNLL-2003, a dataset of named entities in several languages, and fine-tuned on a proprietary corpus of defense, finance, news, and science documents. It reads Chinese, English, and Russian.

  • The system indexes the nouns it has classified in a knowledge graph so that other, more-specialized models can analyze them. Human analysts then use those models’ output to find patterns in vast troves of text. “We are not making a truth detector,” John Bohannon, the company’s director of science, told The Batch. “We are building a sensor array that analysts need to see patterns on a larger scale than humans can comprehend.”
  • In a demonstration for Wired, Primer analyzed over 3,000 news stories about the recent fighting between Azerbaijan and Armenia in the disputed region of Nagorno-Karabakh. It determined that Russian media outlets were attempting to persuade the public that Turkey, Russia’s geopolitical rival, was supplying troops to Azerbaijan. Only Russian sites have reported such involvement.

Why it matters: Human analysts can’t keep up with the flood of information — and disinformation — that bloats the internet. AI may help discover signals amid the noise.

We’re thinking: Technology is making it cheaper and easier to create disinformation. Better detection could benefit not only national security but also disaster response, public health, and the democratic process.

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