Micro-expressions are very brief facial movements, often lasting only a fraction of a second, that may hint at emotion such as surprise, discomfort, or hesitation. In security and “emotional AI” systems, they are treated as weak signals for inference, not as proof of what a person truly feels. Because they are subtle and context-dependent, they are easy to misread and can produce false confidence.
In cyber security, micro-expressions matter because they can be collected and analyzed in surveillance, customer-service, and video-based interaction systems. Attackers may try to use them to gauge stress, resistance, or trust during social engineering or scam calls, while defenders should be cautious about any model that claims to infer intent from faces alone. Good practice includes informed consent, strict data minimization, clear purpose limits, and human review for decisions that affect users. Treating micro-expressions as low-confidence input helps prevent manipulation and overreach.