Advances in artificial intelligence (AI) and machine learning (ML) are ushering in a new era of misinformation and disinformation. The ability to create highly realistic, believable information, events, documents, pictures, and video makes it increasingly difficult to distinguish between fact and fiction. Within this context, what are the most promising technical defensive measures for identifying, flagging, and mitigating the threat of Generative Adversarial Networks (GANs) and other synthetic media generation tools? Beyond technical detection, what AI/ML-enabled capabilities can promote cognitive resistance to disinformation, and how can the military services and their partners develop systemic resiliency to adversarial messaging that utilizes these techniques? Ultimately, what training, education, and software tools are required to protect U.S. forces, partners, and allies from the rapid spread of high-fidelity synthetic media?
- Keohane, Maj. Christopher M., "Arguing with the Dragon: Taiwan's Counter Disinformation Campaigns and Deterring Conflict," AFGC thesis, 2025, 54 pgs.
- Keohane answers this by examining China's evolving tactics, noting that the Chinese use advanced algorithms and AI to generate a continuous, coordinated stream of disinformation designed to overwhelm Taiwanese fact-checkers. To counter this, Keohane highlights how Taiwan promotes resistance by partnering with local media to train journalists on using AI, image search, and video analysis technologies to identify AI-generated fakes. This collaborative use of technology allows Taiwan to amplify its fact-checking network and keep pace with the speed of Chinese AI-enhanced information warfare.
- Grimm, Capt. Chris, "Staying Inside the Adversarial Loop" SOS AUAR paper, 2019, 7 pgs.
- Thomas, Prof. M. A., SAASS "Time for a Counter-AI Strategy" Spring 2020 Strategic Studies Quarterly article.