Governance & Social Justice
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Defence & Security
Science & Technology
- Why Facebook is shutting down its facial recognition system? Impact on 1 billion FB users
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- GS 3 || Science & Technology || Information and Communication Technology || Internet
Why in news?
Facebook shutting down Face recognition system
- Newly rebranded internet giant Meta Platforms Inc announced late Tuesday that it plans to shut down the Face Recognition system — a technology it had introduced back in 2010 — on its social media site Facebook.
What is a Face recognition system?
It’s a type of biometric technology that uses facial traits to identify and distinguish people. It has grown in numerous ways over nearly six decades, from looking at 3D features of a face to identifying skin patterns.
Working of Face recognition system:
- The facial recognition system captures the face and its features using a camera, and then reconstructs those traits using various types of software.
- The captured face, together with its features, is saved in a database that may be connected with any type of software for security, banking, and other applications.
- The Automated Facial Recognition System (AFRS) matches and identifies persons using a big database (which contains images and videos of people’s faces). For pattern-finding and matching, an image of an unidentified individual acquired from CCTV footage is compared to an existing database utilising Artificial Intelligence technology.
Uses of Face recognition system:
- Authentication: It has a success probability of over 75% when used for identification and authentication.
- The NCRB’s Crime and Criminal Tracking Network and Systems (CCTNS), for example, uses computerised facial recognition to identify offenders, missing people, and unexplained dead bodies, as well as for “crime prevention.”
- The goal of the project is to make it interoperable with other biometrics like iris and fingerprints. The police department’s crime investigation powers will be greatly enhanced by the integration of a fingerprint database, facial recognition software, and iris scans.
- Force Multiplier: This can operate as a force multiplier in India, where there are only 144 constables per 1 lakh citizens. It doesn’t necessitate a lot of manpower, and it doesn’t need to be upgraded on a regular basis. As a result, this technology, when combined with the existing personnel, has the potential to be a game-changer.
- It’s being used for everything these days, from unlocking phones to verifying identities, from auto-tagging digital photographs to locating missing people, and from targeted advertising to law enforcement.
- However, China’s reported use of facial recognition technology for surveillance in the Xinjiang area raises the risk of abuse, which is problematic in the absence of privacy and data protection.
- Infrastructure Costs: Artificial Intelligence and Big Data technologies are expensive to implement. The amount of data stored is enormous, necessitating massive network and data storage facilities, which are currently unavailable in India. International cloud servers are now used to store government data from the National Informatics Centre (NIC) and other agencies.
- Image Collection: It is necessary to know the sources from which photographs will be collected in order to construct a repository/database. Certain questions must also be addressed:
- Will data be gathered from social media profiles such as Twitter, Facebook, Instagram, and others?
- What type of relationships would it have with private companies and security agencies?
- How would that relationship be reflected in the terms and conditions, so that they are as transparent as possible, given that these photographs would be made available to law enforcement agencies?
- Database Security: In today’s age of cybercrime, it’s critical to put in place proper protections to ensure the integrity of the repository/database, so that information doesn’t leak out and isn’t privatised or monetized.
- In addition, both international and domestic accessibility concerns must be addressed.
- Expertise required: The data acquired from social media profiles, where anyone can post their image, puts the data’s legitimacy in jeopardy. As a result, specialists must check such details before storing them, and they must be properly trained to secure and prevent exploitation and misuse of the obtained data and database.
- Reliability & Authenticity: Because the information gathered may be used in a court of law throughout the course of a criminal trial, the data’s trustworthiness and admissibility, as well as the standards and procedures followed, will be taken into account. As a result, data authenticity is critical.
- Right to Privacy: While the government intends to address the issue of privacy through legislative frameworks such as the data privacy regime, the objectives it seeks to achieve with the employment of such technologies contradict with one another.
- Indian citizens are more vulnerable to privacy violations when there are no data protection rules in place. Because it is sensitive information, it has a high risk of being misused.
- As a result, the fundamental right to privacy must be protected in tandem with the nature of technology, addressing issues of invasion and surveillance.
- Inherent Challenges: The face may change with time, for example, if someone has grown a beard, or if their age has changed since the last photo was taken, or if someone has covered their face to avoid being filmed by CCTVs. This becomes one of the most difficult tasks to complete.
- However, it is stated that the software handles such issues, making it one of the most effective ways to detect a person.
In India, there have been a few instances of usage.
- On January 26, 2021, the government employed facial recognition technology to track out protestors who were present at the Red Fort.
- Trinetra is an AI-based facial recognition system used by the UP police. More than 1,100 arrests were made after police used this software to conduct surveillance on anti-CAA activists.
- Face recognition was used by the Central Board of Secondary Education (CBSE) to match admit card images on file with students logging in to take their board exams.
- According to the Internet Freedom Foundation (IFF), India presently has 42 active facial recognition projects, ranging from Maharashtra’s Automated Multimodal Biometric Identification System (AMBIS) to Tamil Nadu’s FaceTagr.
- At least 19 of these are being developed and deployed for the purpose of security and surveillance by state-level police departments and the NCRB.
Examples from throughout the world:
- England:Face recognition is used by police forces in England to combat violent violence. In one case, however, the Court of Appeal in the United Kingdom determined that South Wales’ use of face recognition technology was illegal due to a lack of clear standards.
- United States: Face recognition technology is used by the Federal Bureau of Investigation in the United States to track for prospective investigation leads. However, in 2020, the Senate sponsored the Facial Recognition and Biometric Technology Moratorium Act, which would outlaw biometric monitoring without statutory authorisation.
- China: In some circumstances, such as tracking Uighur Muslims, countries like China utilise facial recognition for racial profiling and widespread surveillance.
- Europe: European Union privacy watchdogs have advocated for a ban on facial recognition.
- Several international corporations: IBM’s facial recognition technology branch has been shuttered. For a year, Amazon has put a stop to the technology. Microsoft has stated that it will not sell its facial recognition technology to law enforcement agencies in areas where there is no federal regulation.
- Sufficient safeguards: Both the Information Technology Act of 2000 and the Personal Data Protection Bill of 2019 allow the government unrestricted monitoring powers. We need sufficient protections, such as sanctions, to ensure that police officers do not abuse facial recognition technology.
- Algorithmic Impact Assessment: Organizations wishing to implement these technologies should be compelled to do a rigorous algorithmic impact assessment (AIA). AIAs, which are modelled after impact-assessment frameworks for human rights, environmental protection, and data protection, assist governments in evaluating AI systems and ensuring public input.
- Legislation should be established requiring governmental entities to conduct a thorough evaluation of any facial recognition technologies for bias, privacy, and civil-rights issues.
- This is a compare-and-contrast tool for identifying things based on what you already know. Its use can help to speed up the identifying procedure. For example, a CCTV camera may be installed at a location where a crime has been committed. People waste time attempting to identify collected images of people; however, the programme can do it without human intervention, eliminating human error.
- This technology is critical for India if properly safeguarded. With the world’s largest IT workforce, India’s state-of-the-art technology might be a game-changer.
- The concept that more advanced technology equals higher efficiency must be examined seriously. Indian law enforcement organisations will benefit from a deliberate approach, as police departments throughout the world are realising that technology is not as effective in practise as it appears in theory.
- Following evidence of discrimination and inefficiency, police agencies in London are under pressure to completely phase out the use of facial recognition technologies.
- In addition, the city of San Francisco recently enacted a blanket ban on police use of facial recognition technology.
- As a result, while it is vital to employ such technology, it cannot serve as a panacea for all of the necessary police reforms.
Mains oriented question:
What is the role of social media in the present world? What are its pros and cons? (200 words)