Limitations of AI detector

The limitations of AI detector are mainly reflected in three aspects: technology, application scenarios, and ethics:
Technical limitations
Misclassification in complex scenarios: High passenger flow, extreme weather, or strong light interference may lead to false alarms/omissions, such as rain and fog affecting video clarity. ‌
Response time bottleneck: It takes at least 2 seconds from recognition to braking, making it difficult to completely avoid short distance sudden track jumps. ‌
Uneven technological coverage: There are many pilot projects in first tier cities (such as Hangzhou East Station), but the penetration rate of small and medium-sized stations is low. ‌
Limitations of application scenarios
Industrial testing errors: Psychological detectors are prone to misjudging interference data, and medical AI may weaken the correlation between clinical history. ‌
Lack of flexible services: scenarios such as hearing aid fitting that require consideration of users' psychological needs and wearing experience cannot completely replace manual labor. ‌
Legal trust issue: Medical device certification requires manual signature confirmation from third-party institutions, and AI conclusions still need to be supervised. ‌
Ethical controversy
Privacy risk: 24/7 monitoring may raise public concerns about privacy rights. ‌
Lack of psychological intervention: Only inhibiting behavior cannot solve the motivation for suicide, and psychological assistance is needed. ‌
The current technology is iterating towards multimodal perception fusion (voiceprint, thermal imaging) and lightweight devices, but cost reduction and popularization still need time. ‌