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BRAIN. Broad Research in Artificial Intelligence and Neuroscience
Volume: 16 | Issue: 3 |

Combating Disinformation with Neurocognitive AI: A Hybrid Model for Crisis Communication

Ioanna Georgia Eskiadi - Aristotle University of Thessaloniki (GR), Prodromos Monastiridis - National and Kapodistrian University of Athens (GR),

Abstract
Crisis situations are fertile grounds for disinformation, which can amplify confusion, fear, and mistrust. Traditional AI methods used to combat disinformation often neglect human cognitive responses and emotional triggers. This paper proposes a hybrid system integrating neuroscience-informed AI, including attention tracking, emotion analysis, and behavioural prediction, to enhance crisis communication strategies. By leveraging neurocognitive insights, our model identifies the disinformation's impact on public sentiment and cognition, enabling tailored, effective responses. We combine real-time social media monitoring with neuro-symbolic processing to map patterns of disinformation spread and its emotional resonance. Preliminary evaluations suggest improved accuracy and timeliness in detecting and countering disinformation, especially in high-stakes, fast-evolving crisis contexts.

Keywords: neurocognitive AI, disinformation, crisis communication,
attention tracking, emotion analysis, behavioural prediction,
hybrid AI systems.

DOI: http://dx.doi.org/10.70594/brain/16.3/14