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Facial Recognition

Facial recognition is a biometric technology that uses artificial intelligence to identify or verify individuals by analysing and comparing patterns in their facial features. The system captures an image of a face, maps key facial landmarks such as the distance between eyes, nose shape and jawline contours, and converts these measurements into a digital signature or template. This template is then compared against a database of stored faces to find a match or confirm identity. Facial recognition is deployed across multiple sectors, including law enforcement for suspect identification, border control for passport verification, banking for customer authentication, and consumer devices for unlocking smartphones. The technology has matured rapidly since the 2010s, driven by advances in deep learning, increased processing power and the availability of large image datasets. Accuracy rates have improved significantly, though performance can vary based on lighting conditions, image quality, age, ethnicity and the size of the reference database. Adoption has been particularly strong in China, where facial recognition is integrated into public surveillance networks, payment systems and social credit schemes. In Africa, governments in Nigeria, Kenya, Rwanda, Uganda and Ghana have procured facial recognition systems, often from Chinese and Israeli suppliers, for applications ranging from national identity programmes to urban surveillance. Civil liberties organisations have raised concerns about mass surveillance, algorithmic bias, lack of consent and the potential for misuse by authoritarian regimes. Several jurisdictions, including some cities in the United States and the European Union, have introduced moratoria or regulations to limit deployment in public spaces. The technology remains a focal point in debates over privacy, human rights and the governance of artificial intelligence.

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