Recently, Department of Telecommunications (DoT), Ministry of Communications has developed an artificial-intelligence (AI)-based facial recognition tool — called Artificial Intelligence and Facial Recognition powered Solution for Telecom SIM Subscriber Verification (ASTR).ASTR, launched under Sanchar Saathi Initiative, is an AI powered tool to identify SIMs issued using fraudulent/forged documents.ASTR has capability of running checks on subscriber databases of telecom operators to deduce whether it contains multiple connections associated with the same person.

  ASTR identifies if more than eight SIM connections have been obtained in one person’s name, which is not allowed as per DoT rules.  In 2012, DoT had issued an order to all telecom operators to share their subscriber database including pictures of users with the department.   ASTR analyses this database subscriber images provided by telecom operators and put them into groups of similar-looking images using Facial Recognition Technology (FRT). 

About Sanchar Saathi Portal :

●Sanchar Saathi helps citizens to know the mobile connections issued in their name; report fraudulent or unrequired connections; block mobile phones which are stolen/lost and check IMEI genuineness before buying a mobile phone.

 ● It contains various modules like 

■ CEIR (Central Equipment Identity Register): For blocking stolen/lost mobiles. 

■Telecom Analytics for Fraud Management and Consumer Protection (TAFCOP): It facilitates a user to check the number of mobile connections taken in her/him name using paper-based documents.

 ■ ASTR: To identify fraudulent subscribers. 

■Know your mobile connections: To know mobile connections registered in your name.

About Facial Recognition Technology (FRT)

 ●FRT is a way of identifying or confirming an individual’s identity using their face. It can be used to identify people in photos, videos, or in real-time.

  ■ Computer algorithms map unique faciallandmarks such as shape of cheekbones, contours of lips etc. and convert these into a numerical code— termed a faceprint. 

☆ It relies on many of the processes and techniques associated with AI. 

■For verification or identification, system compares faceprint generated with a large existing database of faceprints.

Concerns associated with the use of Facial Recognition Technology 

●Privacy and Consent: Lack of control over storage, extent, and informed consent with respect to use of facial data by public and private players, resulting in privacy invasion.  

● Data protection law: In India, there is absence of FRT- specific regulatory set up and legal framework to govern data protection, storage and use especially in context of personal biometric data. 

■ Recently, the government also withdrew Personal Data Protection Bill, 2019. 

●In-accuracy: Technical errors due to occlusion (a partial or complete obstruction of the image), bad lighting, facial expression, ageing etc. leading to inaccurate identification.

 ●Under-representation: Errors in FRT occur due to lack of data pertaining to certain groups of people. 

 ■Disparity has been observed in identification of Indian men and women and accuracy rates fall starkly based on race, gender, skin colour etc. 

●Technological challenges: FRT is prone to digital attacks or the use of physical or digital portraits, 3D-Models, such as masks or deep-fakes etc. to bypass the system. 

Way forward 

● Legal framework: There is urgent need to regulate the use of FRT systems and a data protection law that would mandate necessary safeguards in the collection and storage of user data.

■There is need for clear regulation of CCTVs by public and private actors before a system like the Automated Facial Recognition System (AFRS) is implemented.

 ● Accountability: Clear mechanisms and bodies for oversight and accountability need to be established including requirements for audits and transparency reports. 

● Consent: Structures for consent that take into consideration passive data collection need to be defined for the use of FRT in criminal and non-criminal cases. 

● Capacity building: To ensure that end users of the technology are fully trained in both the technical and ethical dimensions of FRT, it is imperative that comprehensive training is provided to end users.

 ●Eliminate biasness: The FRT systems datasets and software interface needs to be constantly updated to ensure equality and minimize potential biases based on skin colour, geography, religion, caste, etc.  

Other types of biometric identification technology  

Biometric identification is the process of identifying individuals based on unique, distinguishable traits. Besides facial recognition, there are many other types of biometric identification: 

●Fingerprint verification: Fingerprint recognition software verifies an individual's identity by comparing their fingerprint against one or more fingerprints in a database. 

DNA matching: It identifies an individual by analysing segments from their DNA. Technology sequences the DNA in a lab and compares it with samples in a database. 

● Eye recognition: It analyzes features in the iris or patterns of the veins in the retina to determine a match and identify an individual.

 ● Hand geometry recognition: This identifies individuals through the geometric features of their hands, such as the length of the fingers and width of the hand. A camera captures a silhouette image of the hand and compares it against a database. 

● Voice recognition: It extracts the characteristics that distinguish an individual's speech from others. It creates a voiceprint that is similar to a fingerprint or faceprint and matches it to samples in a database. 
● Signature recognition: This use technology to analyze handwriting style or compare two scanned signatures using advanced algorithms. 



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