Intermediate
What is a remote biometric identification system?
A remote biometric identification system is an AI system used to identify natural persons without their active involvement, typically at a distance. It compares a person's biometric data with biometric data stored in a reference database.
What is real-time remote biometric identification?
A real-time remote biometric identification system is a system in which biometric data capture, comparison, and identification occur without significant delay. The category includes instant identification as well as short delays intended to prevent circumvention.
What is an emotion recognition system?
An emotion recognition system is an AI system intended to identify or infer the emotions or intentions of natural persons, often from biometric data. Because such systems can affect privacy, autonomy, and fairness, they are subject to heightened scrutiny in governance and regulatory contexts.
What is biometric categorisation?
A biometric categorisation system is an AI system that assigns natural persons to specific categories on the basis of biometric data.
Why is facial recognition high risk?
Facial Recognition Technology (FRT) refers to automated systems that identify, verify, or categorize people by analyzing facial features from digital images or video. It is a biometric technology and may raise privacy, accuracy, and discrimination concerns depending on its use.
What are deepfakes in biometric AI?
Deepfakes are AI-generated or AI-manipulated images, audio, or video that make people, objects, places, entities, or events appear authentic when they are not.
Advanced
What is synthetic media?
Synthetic media is media content that is wholly or partly generated or manipulated by AI. It can include text, images, audio, video, avatars, voices, and other digital artifacts.
How can biometric AI harm fairness?
Fairness in AI refers to the principle that AI systems should treat individuals and groups equitably and avoid unjustified discrimination or harmful bias. It involves identifying and mitigating bias in data, models, deployment contexts, and decision processes.