Key Findings
- Chinese military scholars portray cognitive warfare as an effort to control enemy beliefs across wartime and peacetime, involving warfighters and civilian populations through selective messaging.
- The article finds that PRC-linked scholarship treats algorithms as transformative because they can analyze users, shape recommendation environments, and deliver tendentious messaging without targets recognizing manipulation.
- A cited framework divides algorithmic cognitive operations into stages that identify audiences, attract attention, suggest references, induce reactions, intervene in group dynamics, and measure gratification.
- The article argues that individualized influence requires comprehensive personal data, including psychological states, social relationships, travel habits, shopping history, and other hidden correlations.
- PRC discussions of the Russia-Ukraine war emphasize social media and algorithmic amplification as a turning point in public opinion warfare, with lessons the article connects to Taiwan narratives and election influence tactics described by researchers in Taiwan in 2024 during the island’s elections.
Overview
This article examines how Chinese military and political scholars conceptualize “algorithmic cognitive warfare,” a form of information warfare that uses AI and platform recommendation algorithms to analyze, target, influence, and divide foreign populations. It bases its analysis on Chinese scholarly works and editorials by authors affiliated with the PLA, defense-focused institutions, military-affiliated outlets, or national-security research grants that explicitly discuss algorithmic cognitive warfare or algorithm-enhanced cognitive operations. The article cautions that PLA doctrine and capabilities may diverge, and that it is unclear whether the PLA can fully execute the proposed techniques. It describes cognitive warfare as selective messaging aimed at enemy beliefs, then traces how social media, LLMs, deepfakes, AR/VR, IoT data, and other technologies are viewed as future attack surfaces. A central finding is that the concept depends on granular personal data, enabling user portraits, tailored content delivery, social regrouping, and feedback on target reactions. The article also links PRC discussions of the Russia-Ukraine war and Taiwan narratives to evolving influence approaches. It recommends that U.S. policymakers improve intelligence collection and analysis, create faster public warning mechanisms, strengthen truthful strategic communications, share findings with allies, and expand protections for U.S. personal data.
At the heart of algorithmic cognitive warfare’s success lies the granular, comprehensive data about target populations needed to conduct individualized warfare.
SCSP
Recommendations
- Increase focus on PRC influence capabilities and educate policymakers. U.S. intelligence and homeland security agencies should increase their focus on PRC influence capabilities and educate policymakers about how…
- Develop more rapid warning mechanisms for the public. The U.S. Intelligence Community must work to speed up, systematize, and potentially even automate the warnings it provides to policymakers and the…
- Advance our own strategic messaging across traditional and digital channels. Policymakers need to actively promote truthful, accurate messaging that aligns with our own strategic goals and reinvigorate strategic communications…
- Protect and shield U.S. citizens' privacy data. Protecting U.S. privacy data is essential because Chinese algorithmic cognitive warfare is designed to acquire and exploit the private information of…
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Published by the Special Competitive Studies Project. Co-publishers and external authors, where they exist, are credited in the byline above.