1. INTRODUCTION:

1.1.Overview of facial recognition technology:

A facial recognition system is a piece of technology that has the potential to compare a database of faces with a digital image or video frame that shows a human face. Typically used to verify users’ identities through ID verification services, this device locates and measures face features from an image. Once limited to science fiction, facial recognition technology has become a commonplace feature in many aspects of our lives, such as smartphone unlocking and airport security checks.

Since their creation, facial recognition systems have been used more widely in robotics and other forms of technology as well as on smartphones. Facial recognition software is within the biometrics category since it uses computerized facial recognition to measure the physiological traits of humans.

 Although facial recognition has many uses, the technology’s explosive growth has sparked grave worries about individual rights and privacy.

1.2. Significance of privacy laws:

Concerns about Face Recognition Privacy have been causing a lot of people distress lately. This is mostly because of privacy concerns. Institutions worldwide have responded to these concerns by enacting stringent laws to safeguard individuals’ biometric information.

The General Data Protection Regulation (GDPR) in Europe is one example. According to Europe’s GDPR, individuals have a right to privacy and any infringement will have negative repercussions. These privacy concerns are not unfounded. Individuals dislike feeling like they are being observed or that someone might divulge sensitive information about them.

Furthermore, there’s the matter of what occurs to the faces that the camera records. Law enforcement organizations can benefit from Face Recognition, as previously indicated, although police can only view Face Recognition footage with the owner of the camera’s consent.

This is where the importance of privacy laws rises. The risk of data loss and confidentiality breaches is higher than ever before. Laws pertaining to data privacy are intended to safeguard vulnerable groups, deter criminality, and ensure reliable digital performance.

1.3. Thesis Statement:

The fine line that exists between individual rights and technical progress is best shown by the interaction between privacy regulations with facial recognition technologies. As facial recognition technology becomes more widely used, worries about invasions of privacy and individual rights grow. This essay covers the development of facial recognition, looks at international regulatory frameworks, analyzes ethical issues, looks closely at the roles played by the public and commercial sectors, and suggests a balanced approach. The aim is to shed light on the path toward responsible innovation by negotiating this challenging terrain and finding a harmonic balance between the advancement of technology and the protection of fundamental human rights.

2. EVOLUTION OF FACIAL RECOGNITION TECHNOLOGY:

2.1. Historical context and development:

Woody Bledsoe, Helen Chan Wolf, and Charles Bisson were the pioneers of automated facial recognition in the 1960s, with their work centered on teaching computers to recognize human faces. Their initial attempt at facial recognition was called “man-machine” because, for a computer to recognize facial features in a picture, a human had to first determine the coordinates of those features.  Twenty different distances were computed using the coordinates.

Takeo Kanade was the first to present a face-matching system to the public in 1970. It was able to identify anatomical features like the chin and determine the distance between facial features without the need for human assistance. Subsequent testing showed that facial feature recognition was not always reliable. Still, curiosity over the topic rose, and Kanade released the first comprehensive book on facial recognition technology in 1977.

In 1993, the Army Research Laboratory (ARL) and the Defence Advanced Research Project Agency (DARPA) launched the Face Recognition Technology Programme (FERET) to create “automatic face recognition capabilities” that could be used in a practical setting “to assist security, intelligence, and law enforcement personnel in the performance of their duties.” A few of the currently available techniques could be used to successfully identify faces in still photos captured in a controlled setting, according to the results of the FERET tests, which assessed face recognition systems that had been tested in research labs. The Department of Motor Vehicles offices brought automated face recognition technology to US people as a common form of identification, making them one of the first significant marketplaces for it.

In the 1990s, Alex Pentland and Matthew Turk of the Massachusetts Institute of Technology (MIT) presented the first successful example of facial recognition technology, which uses the statistical Principal component analysis (PCA) method.

 In 2005, The Face Recognition Grand Challenge (FRGC) was launched to encourage and develop face recognition technology.

Eventually, it got accepted, and thereby in 2014 Facebook introduced Facial Recognition in its internal algorithm.

Today, this technology has encouraged multiple investments in commercial, industrial, legal, and governmental applications and is still being used widely.

2.2. Current Applications and Advancements:

Face Recognition Technology is being used widely in social media, healthcare, education, Government services, retail stores, etc.

1. Healthcare:

Patient identification, diagnosing genetic disorders, preventing the spread of COVID-19, facilitating mental therapy, etc, are some major uses of Facial Recognition Technology in the healthcare sector. With the introduction of this fantastic technology doctors and medical experts are now capable of diagnosing some diseases using specific features of the FRT(Face Recognition Technology). These developed datasets are used to identify genetic abnormalities just based on facial dimensional differences.

Face2Gene is not the first app that relies on facial recognition to diagnose rare diseases; it is one of the most popular ones. According to the app’s developers, 250,000 people have been evaluated with its aid, and 7,000 conditions have been found.

• Retail Stores:

From checking out free software solutions, and loyalty programs, to personalized shopping experiences, everything is possible with FRT(Face Recognition Technology).

The US firm 3VR, now Identiv, is an example of a vendor that began offering facial recognition systems and services to retailers as early as 2007.Benefits like facial surveillance analytics to facilitate personalized customer greetings by employees, “dwell and queue line analytics” to decrease customer wait times, and the capacity to create loyalty programs by combining Point of Scale(POS) data with facial recognition were among those promoted by the company in 2012.

After the lockdowns that happened due to COVID-19, when stores started to work, people were reluctant to shop offline and wary of excessive touch and interactions. That’s when retailers turned to FRT enabling contactless payments to lure customers back in. Countries like China and the US have already incorporated face-recognition-based checkouts.

One of the first US businesses to implement a facial recognition loyalty program was Cali Group. They outfitted their eateries with AI-driven self-service kiosks that recognize patrons who have registered and instantly activate their loyalty accounts upon approaching the kiosk. Customers may be prompted to order their favorite meals via the kiosk’s software. Payments are handled via facial recognition as well.

Moreover, Facial Recognition Systems have been able to prevent shoplifting to some extent, research shows. Those are usually targeted at identifying repeat offenders whose photos are already stored in their database. In 2019, facial recognition to prevent theft was in use at Sydney’s Star Casino and was also deployed at gaming venues in New Zealand.^[1]

• Education:

FRT is used in the educational sector for purposes like campus security, attendance monitoring, increased learning engagement, etc. With the increase in incidents like shootings in campus areas and such seen in some countries, school administrators are prompted to take more advanced precautionary measures to prevent tragedies. The deployment of Facial Recognition Systems across schools helps establish the identity of faces of people entering or leaving school premises. Additional characteristics of modern facial recognition solutions include object detection, which is used to recognize things with a gun-like shape. Facial Recognition Applications also offer a faster and non-disruptive way of tracking students’ attendance thereby saving time. These smart-attendance tracking solutions have started gaining attention in major countries. Moreover, these AI-powered FRSs can help professors understand students’ moods by analyzing microexpressions and increase learning engagement by adjusting the curriculum to better reflect student preferences and provide a more tailored learning experience.

        The applications of Facial Recognition Technology are ever-growing and limitless across industries globally. The examples above are only a few of the many applications these FRTs provide.

2.3. Increasing Prevalence:

With the widespread application of Facial Recognition Technology across sectors, it has become deeply integrated into modern life. From social media to law enforcement, its influence prevails.

1. Social Media:

Photo Tagging and User Authentication are mainly done by this Facial Recognition System on platforms like Facebook and Instagram. Users can unlock their devices, access accounts, and tag friends all using facial biometrics, enhancing user experience and engagement.

• Commerce and Technology:

To provide a convenient and swift user experience, smartphones and various other devices have now employed facial recognition as a secure method for unlocking devices and it’s also being integrated into payment systems, allowing users to authorize transactions with a facial scan.

• Law Enforcement:

Face Recognition Technology is utilized by law enforcement agencies for identifying and tracking criminals. Some cities use this technology to enhance public safety by monitoring and identifying potential threats.

Striking a balance between this technological innovation and safeguarding individual rights remains a crucial challenge for society.

      3. LEGAL FRAMEWORKS GOVERNING FACIAL RECOGNITION:

3.1. Overview of Existing Privacy Laws in India;

Before the Digital Personal Data Protection Act, there was no general data protection law in the country. The Indian Data Protection landscape previously comprised only these concerning sensitive personal data:

1. The Right to privacy was included under Article 21 of the Indian Constitution after the landmark judgment of Justice K.S. Puttaswamy(Retd.) v. Union Of India.^[2] The DPDP(Digital Personal Data Protection) Act itself, along with a plethora of Jurisprudence on data protection in India emanates from this decision. A nine-judge panel was assembled in this instance to decide whether or not there is a basic right to privacy. The SC unanimously held the right to privacy to be an intrinsic element of the Right to life and personal liberty protected under Article 21 of the Indian Constitution.
2. Under the IT Act,2000 “Biometric data” is considered sensitive personal data, and contains rules for the collection, disclosure, and sharing of such information that is related to the privacy of an individual. In any event of a violation, recourse can be taken under Section 42A of the Act. However, the major loophole with that is that it only applies to corporate bodies and leaves scope for misuse by the government.
3. The Aadhaar Act was the first in India that specifically dealt with the collection, storage, and processing of biometric data. The Aadhaar Act makes it a requirement to seek authentication of the UID of an individual for biometric information disclosure or usage. The violation of the provisions of the Act may result in imprisonment that may extend up to 3 years as well as a penalty.

The Digital Personal Data Protection Act,2023:

(The Act received presidential assent in August 2023 but is not effective to date. Once implemented, it will be the only governing law on personal data protection in the country.)

This Act will be the primary statute governing individuals’ digital personal data. Currently, there are no rules or guidelines issued under the Act. But certain provisions such as notice obligations, consent manager’s duties, data breaching reporting, collection of verifiable parental consent, etc, are expected to be out as per government instructions. The Act also provides for the establishment of a Board to have multiple roles like maintaining a register of consent managers, conducting inquiries, issuing directions, and enforcement. All the powers, duties, and liabilities of the Board are also specified in the Act.

The Act primarily provides for a consent-centric approach to processing data. Consent must be freely given, informed, explicit, unconditional, unambiguous, with a clear affirmative action, able to be revoked, for a defined purpose, and restricted to the personal information required for that specific purpose for it to be considered legitimate. Other than consent,  processing will be done only for certain legitimate users. The Board may also impose penalties for non-compliance with the Act.

3.2. Global Perspectives and Variations:

The regulation varies from country to country, reflecting diverse cultural, legal, and ethical perspectives. Listed down are some commonalities and variations in various countries regarding Facial Recognition Technology:

S.NO	COUNTRY	VARIATIONS	COMMONALITIES
	United States	Lacks a comprehensive law addressing FRTs; with states adopting their measures.	There’s a need for uniform guidelines because of increasing privacy concerns.
	European Union	The General Data Protection Regulation(GDPR) provides the framework for the protection of personal data, including biometrics.	Emphasis on the right to privacy and the importance of obtaining informed consent for biometric data processing.
	Canada	The Personal Information Protection and Electronic Documents Act(PIPEDA) regulates the collection, use, and disclosure of personal information including biometrics.	Canadian regulations emphasize the importance of consent, accountability, and transparency in the handling of biometric data.

      4. ETHICAL CONSIDERATIONS:

4.1. Privacy Concerns and Individual Rights:

There are substantial legal and ethical issues with the deployment of FRTs in India. There are concerns about privacy, data protection, justice, and prejudice, with the development and use of FRTs widely. The market for FRTs is rapidly increasing with its usage in every industry. The several privacy and security issues that come up with this technology are as follows:

1. Lack of consent: ‘FRTs identify individuals without their consent’; is one of the most significant privacy implications of  FRT. This includes real-time public surveillance or an aggregation of databases that are not lawfully constructed.
2. Unencrypted faces: Data breaches involving facial recognition data increase the potential for identity theft stalking, and harassment as it’s easier to capture faces and store them.
3. Lack of transparency: Since biometrics are unique to each individual, using FRT to identify someone without their knowledge or consent creates privacy problems. It also raises additional difficulties because facial scans can easily, remotely, and covertly be acquired, in contrast to conventional biometrics (such as fingerprints).
4. Technical Vulnerabilities: With FRT, images or three-dimensional (3D) masks made from victim imagery might be used to spoof a system or masquerade as a victim. Furthermore, presentation attacks and the deployment of tangible or digital spoofs, like masks or deepfakes, can both be a risk to FRT.

4.2. Technological Innovation and Ethical Responsibilities in Balance:

For facial recognition systems to function properly, people should have control over their personal data.

People must be furnished with unambiguous opt-out alternatives to preserve their independence and discretion.

Systems and techniques for facial recognition should be transparent and explained. Clear rules and regulations must be in place for facial recognition technology to be utilized morally and without discrimination.

Given that face recognition systems retain private biometric data, they could be targets of cyberattacks. Strict security procedures and guidelines are needed to reduce data breaches while preserving the confidentiality and integrity of your facial data.

The creation of frameworks, standards, and norms by governmental and regulatory organizations has made it possible to guarantee the moral application of facial recognition technology. These frameworks ought to take into account things like permission, privacy, data security, and equitable algorithms for all. Furthermore, in order to promote knowledge and responsible usage, user education regarding the capabilities, possible risks, and privacy implications of the technology must be prioritized. It is possible to implement facial recognition technology in a way that is both ethical and balanced by combining technological, legal, and pedagogical approaches.

      5. FUTURE OUTLOOKS:

5.1. Emerging Trends in Facial Recognition Technology:

The facial recognition industry is growing Artificial intelligence (AI) applications, safety and monitoring, and even more individualized commercial interactions are just a few of the industries that have the potential to significantly transform.

In the past several years, facial recognition technology has been employed far more frequently, and new goods and applications are constantly being developed and released into the market. This once-fantastical and quickly growing sector of the economy has arrived

 Currently, it is more crucial to think about how face recognition will impact future generations than what the technology will look like in the future. Some upcoming FRT Trends include

1. Lie Detection and Age Verification
2. Payment and Crypto Currency
3. More intelligent Personal Assistants
4. AI Enhanced Facial Capabilities
5. Driver Monitoring, etc.

5.2. The Role of Public and Private Sectors:

1. Public Sector: Governments must enact and enforce regulations that balance technological innovation with privacy protection. Transparent policymaking processes are essential to address concerns related to surveillance and bias, fostering public trust.
2. Private Sector: Companies and developers must prioritize ethics, ensuring the privacy of the individuals. Transparent communication, self-regulation, and collaboration with regulators demonstrate a commitment to responsible innovation.

           Moreover, public-private collaboration fosters adaptive regulations, considering technological advancements and societal values. Partnerships enable the exchange of expertise, leading to effective governance frameworks aligned with public safety and individual rights.

      6. CONCLUSION:

6.1. Recap of Key Points:

Important conclusions are drawn from an analysis of the complexities of facial recognition technology. The complexity is shown by the progression from simple patterns to AI-driven algorithms, a wide range of applications, and international regulatory environments. The necessity of careful use is highlighted by ethical issues. A careful balancing act between privacy and creativity is revealed by looking at employment in the public and private sectors. To shape technology’s future and ensure a harmonic integration with society’s values, ethical considerations, transparent policies, and collaborative approaches must be taken into account.

6.2. Call for Action:

A shared obligation arises while navigating the face recognition technology of the future. There is a resounding cry for a responsible and impartial attitude. Together, individuals, IT developers, and policymakers must create flexible policies that safeguard individual liberties in addition to innovation. The cornerstones of responsible deployment become openness, morality, and public dialogue. To protect privacy in the digital era and conform to cultural values, this call to action calls for a concerted effort to shape the trajectory of facial recognition technology.

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^{[1] Mayhew, Stephen (March 17, 2019). “Casinos down under deploy facial recognition tech to spot offenders, problem gamblers | Biometric Update”}

^{[2] KS Puttaswamy v. Union of India, (2017) 10 SCC 641}

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Author: Annliya Anil

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