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In the digital era, biometric technologies such as facial recognition and fingerprint scanning have become essential for law enforcement, enabling rapid and accurate suspect identification while enhancing investigative efficiency. These technologies offer significant benefits, including crime reduction, minimization of human errors, and resource optimization. However, their use raises major challenges related to data privacy, cybersecurity, and the ethics of surveillance. European regulations, particularly the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (AI Act), impose strict restrictions on biometric data processing to prevent misuse and excessive surveillance. According to the European Data Protection Board (EDPB) recommendations, the use of facial recognition in public spaces must be justified and limited to exceptional situations. Although biometric technologies can significantly improve public safety, risks associated with algorithmic bias, which may lead to discrimination, as well as the potential misuse of collected data, remain pressing concerns. Therefore, their implementation must be transparent, ethical, and compliant with existing legislation. For the responsible use of these technologies, strict data protection measures, continuous monitoring and auditing of biometric systems, and the development of fairer algorithms are recommended. This approach ensures a balance between the operational efficiency of law enforcement agencies and the protection of fundamental rights of citizens.
ABSTRACT
In the digital era, biometric technologies such as facial recognition and fingerprint scanning have become essential for law enforcement, enabling rapid and accurate suspect identification while enhancing investigative efficiency. These technologies offer significant benefits, including crime reduction, minimization of human errors, and resource optimization. However, their use raises major challenges related to data privacy, cybersecurity, and the ethics of surveillance. European regulations, particularly the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (AI Act), impose strict restrictions on biometric data processing to prevent misuse and excessive surveillance. According to the European Data Protection Board (EDPB) recommendations, the use of facial recognition in public spaces must be justified and limited to exceptional situations. Although biometric technologies can significantly improve public safety, risks associated with algorithmic bias, which may lead to discrimination, as well as the potential misuse of collected data, remain pressing concerns. Therefore, their implementation must be transparent, ethical, and compliant with existing legislation. For the responsible use of these technologies, strict data protection measures, continuous monitoring and auditing of biometric systems, and the development of fairer algorithms are recommended. This approach ensures a balance between the operational efficiency of law enforcement agencies and the protection of fundamental rights of citizens.
KEYWORDS: artificial intelligence, biometric technologies, organized crime, public safety, law enforcement
1. Introduction
In the current digital era, biometric technologies such as facial recognition have become essential tools for law enforcement in identifying and preventing criminal activities.
These technologies enable the rapid and precise identification of individuals, facilitating prompt and effective interventions. For example, the use of realtime facial recognition can accelerate investigations and contribute to crime prevention. According to a 2021 survey conducted by the U.S. Government Accountability Office (GAO), "20 law enforcement agencies reported possessing facial recognition systems. Six agencies stated that they used them to identify individuals who broke the law during civil disturbances, protests, and riots following the death of George Floyd" (Unite Al, 2022).
However, the implementation of these systems raises significant concerns regarding privacy and data protection. According to the General Data Protection Regulation (GDPR), biometric data is considered a special category of data, and its processing requires strict security measures and legal compliance. Additionally, a Data Protection Impact Assessment (DPIA) is required when processing may pose a high risk to the rights and freedoms of individuals. "The implementation of GDPR has posed significant challenges for the use of facial recognition. Supervisory authorities in EU member states have raised concerns about the legality of using this technology without the explicit consent of individuals" (Grecu, 2024).
Furthermore, the widespread use of facial recognition in public spaces risks leading to mass surveillance, affecting individuals' right to privacy. Real-time facial recognition applications interfere with fundamental rights and freedoms to such an extent that they may call into question the very essence of these rights and freedoms. In this context, the European Data Protection Board (EDPB) and the European Data Protection Supervisor (EDPS) have called for a ban on the use of artificial intelligence for the automatic recognition of human features in publicly accessible spaces. In an official report, these institutions emphasized that "realtime facial recognition applications interfere with fundamental rights and freedoms to such an extent that they may call into question the very essence of these rights and freedoms" (EDPB, 2021).
Therefore, it is essential for law enforcement agencies to find a balance between the effective use of biometric technologies for public safety and the protection of fundamental citizens' rights. This balance can be achieved through the implementation of clear, transparent, and legally compliant policies, ensuring a responsible and ethical use of these technologies. In the context of globalization and new threats to public security, a precise regulatory framework is necessary to prevent abuses and maximize the benefits of these systems.
2. Main Biometric Systems Used by Law Enforcement
Law enforcement agencies worldwide have integrated biometric systems into their security and investigative strategies to enable rapid and accurate identification of individuals. These technologies use unique personal characteristics, such as facial features, fingerprints, voice, or even gait patterns, to facilitate suspect identification and crime prevention. Depending on their nature, biometric systems are classified into physiological biometrics (based on physical characteristics) and behavioral biometrics (focused on behavioral patterns).
2.1. Physiological Biometric Systems
These systems rely on unique physical characteristics of individuals that remain relatively stable throughout their lifetime. The most commonly used methods include:
* Fingerprint Recognition
Fingerprint identification is one of the oldest and most effective biometric identification methods. Since every individual has a unique fingerprint pattern, this system offers a high degree of accuracy in personal identification. Modern technologies have enabled the development of Automated Fingerprint Identification Systems (AFIS), which are widely used by law enforcement agencies to compare fingerprints collected from crime scenes with existing databases.
According to a report by the European Security Agency, "AFIS systems can quickly analyze and compare millions of fingerprints, allowing authorities to identify suspects within minutes" (European Security Agency, 2022, p. 47). In Romania, the MorphoTrak AFIS system is used by the General Inspectorate of the Romanian Police (IGPR) to facilitate suspect identification and manage fingerprint databases.
* Facial Recognition
Facial recognition has become one of the most widely used biometric technologies due to advancements in artificial intelligence (AI). This technology works by analyzing distinct facial features, such as the distance between the eyes, the shape of the nose, and the structure of the jawline, to create a unique digital profile of an individual.
Law enforcement agencies use this method in intelligent video surveillance systems, at airports, border checkpoints, and public spaces to identify wanted individuals. According to a study conducted by the Global Security Institute, "Facial recognition is used by law enforcement to identify individuals in crowds or video recordings, providing a significant operational advantage" (Global Security Institute, 2021, p. 32).
However, the use of facial recognition raises concerns regarding data privacy and the risk of false identification. In some cases, facial recognition algorithms have demonstrated racial bias, exhibiting lower accuracy in identifying individuals of certain ethnic backgrounds, leading to concerns about justice and fairness in law enforcement.
* Iris Recognition
Iris recognition is one of the most secure biometric methods, with a very low error rate. This technology involves a detailed scan of the unique iris pattern of each individual, a characteristic that remains stable throughout life.
This technology is primarily used in high-security environments, such as airport security checkpoints and government buildings' access systems. Unlike facial recognition, which can be affected by changes such as aging or facial expressions, the iris remains constant, making it an extremely reliable identification method.
2.2. Behavioral Biometric Systems
Unlike - physiological biometric methods, behavioral biometric systems rely on the unique action patterns of each individual. These methods are more difficult to forge and can be used for continuous authentication in advanced security systems:
* Voice Recognition
Voice recognition technologies analyze the unique characteristics of a person's voice, such as tone, frequency, and accent. This method is commonly used in telephone authentication systems and within secure virtual assistants.
A report by the European Digital Forensics Center states that "voice recognition is an effective method for remote identity verification, particularly used in police investigations and banking systems" (European Digital Forensics Center, 2023, p. 19).
Although voice recognition provides a convenient alternative to traditional authentication methods, its accuracy can be influenced by factors such as background noise or natural voice changes due to health conditions.
* Gait Analysis
Gait analysis is a lesser-known biometric method, but it is highly useful for remote video surveillance. It involves identifying an individual based on their walking pattern, as each person has a unique gait style influenced by genetic and biomechanical factors.
This technology is implemented in law enforcement surveillance systems and has been tested in several airports worldwide for detecting suspicious individuals. Studies indicate that "gait analysis can be used as a complementary method to facial recognition, allowing the identification of individuals even when their faces are not visible" (Journal of Forensic Biometrics, 2022, p. 55).
The integration of biometric systems in law enforcement has revolutionized suspect identification and crime prevention methods. Whether through fingerprint recognition, facial recognition, or gait analysis, these technologies offer a high level of accuracy and efficiency. However, their use must be properly regulated to ensure the protection of fundamental rights and freedoms of citizens.
3. Benefits of Using Biometric Technologies
The implementation of biometric technologies in law enforcement has marked a significant advancement in enhancing their ability to ensure public safety. These technologies offer multiple advantages, including increased efficiency in suspect identification, reduction of human errors, enhanced security, and improved resource management. In a society where public order threats are increasingly complex, the use of these systems has become a strategic necessity.
* Increased Efficiency in Suspect Identification
One of the most notable advantages of biometric technologies is their ability to quickly and accurately identify suspected individuals. Unlike traditional methods, which often involve time-consuming manual verifications, biometric systems allow for instant comparisons of unique personal characteristics with existing databases, reducing response times to just a few seconds.
A relevant example is the use of facial recognition in public area video surveillance. This technology has been adopted by the Metropolitan Police in London, which reported that "the use of real-time facial recognition has enabled law enforcement to identify suspects more quickly and accurately, reducing the time required for investigations" (Financial Times, 2024, p. 7). This advancement provides law enforcement agencies with a significant operational advantage, facilitating crime prevention and enforcement.
* Reduction of Human Errors
Human errors can significantly impact identification and investigative processes.
In this context, biometric technologies help minimize the risk of misidentification by eliminating subjective biases and reducing the possibility of document forgery.
For example, fingerprint identification through Automated Fingerprint Identification Systems (AFIS) provides a much higher level of accuracy than traditional methods. According to a report by the European Institute of Forensic Science, "AFIS systems have reduced human error rates by over 80%, ensuring the correct identification of individuals based on unique fingerprint characteristics" (Journal of Forensic Biometrics, 2023, p. 21).
This improvement not only enhances investigative processes but also reduces wrongful convictions, thereby protecting the fundamental rights of individuals.
* Enhanced Public Security
Biometric technologies serve as an essential tool for maintaining public order, enabling the early detection of suspects before they commit crimes. The implementation of facial recognition in airports, train stations, and other public spaces allows for the rapid identification of individuals wanted by authorities.
A concrete example is the use of facial recognition by the Chinese government, where "law enforcement agencies utilize advanced systems to identify and track suspects in real time, leading to a decrease in serious crimes in monitored areas" (Global Security Institute, 2022, p. 34).
In Europe, the use of facial recognition has been adopted with additional measures for the protection of personal data, yet the results achieved in public security are significant.
The integration of biometric technologies in law enforcement has revolutionized the way suspects are identified and crime is prevented. With the ability to enhance efficiency, reduce errors, and improve public security, these technologies provide law enforcement agencies with powerful investigative tools. However, their implementation must be carefully regulated to ensure the protection of fundamental human rights and ethical considerations.
* Optimization of Resource Utilization
Another major benefit of biometric technologies is their ability to automate identification processes, allowing law enforcement agencies to use their resources more efficiently. Manual document verification, suspect interrogation, and video footage analysis are tasks that require a significant amount of labor and time.
Thanks to biometric technologies, many of these tasks are now automated. A report by the European Security Agency states that "the implementation of biometric systems has reduced the time required for verifying a person's identity from several minutes to just a few seconds, thus improving the operational efficiency of law enforcement" (European Security Agency, 2023, p. 56).
This allows the police to focus their resources on strategic activities, such as crime prevention and rapid response interventions in critical situations.
* Acceptability and Ease of Use
An important aspect of using biometric technologies is their acceptability among the population and the ease with which they can be integrated into everyday life. Unlike other identification methods that require physical documents or passwords, biometrics utilize natural characteristics of the individual, eliminating the need to remember or carry documents.
For example, the use of facial recognition for access to government institutions or fingerprint verification at checkpoints is perceived by the public as a safer and more convenient method. According to a study conducted by the European Institute for Cybersecurity, "over 70% of respondents stated that they prefer biometric authentication over traditional passwords, considering it more secure and easier to use" (Cybersecurity Europe, 2024, p. 29).
This demonstrates that the adoption of biometric technologies not only enhances security but is also well received by the public, facilitating their integration into governmental and private sector systems.
The benefits of using biometric technologies in law enforcement are undeniable. From improving identification accuracy and reducing human errors to enhancing public security and optimizing resource utilization, these technologies have revolutionized how authorities combat crime. However, the use of biometrics must be accompanied by clear data protection measures to ensure compliance with the fundamental rights of citizens.
4. Challenges and Risks Associated with Biometric Technologies
Although biometric technologies provide numerous benefits in law enforcement, their use also involves significant challenges and risks that must be carefully managed. These include concerns related to data privacy, information security, system accuracy, and ethical implications.
* Privacy and Protection of Personal Data
Biometric technologies collect and process sensitive data, such as fingerprints, facial features, or iris scans. These pieces of information are intrinsically linked to individual identity and, once compromised, cannot be modified or replaced.
According to Guideline 05/2022 of the European Data Protection Board (EDPB), "the unique nature of biometric data makes it impossible for the data subject to modify them in case of a security breach" (EDPB, 2022, p. 17).
To address these risks, conducting a Data Protection Impact Assessment (DPIA) is essential before implementing any biometric system. This assessment helps identify and mitigate potential risks to individuals' rights and freedoms. Additionally, as stated in Article 35 of the GDPR, "a DPIA is required when the processing of personal data poses a high risk to individuals' rights and freedoms" (Grecu, 2023, р. 9).
* Information Security
The storage and management of biometric data require robust cybersecurity measures to prevent unauthorized access, data theft, or misuse. A security breach can have severe consequences, given that biometric data are permanent and cannot be changed.
According to Guideline 05/2022 of the EDPB, "the competent authority implementing and/or using facial recognition technology should pay special attention to the security of data processing" (EDPB, 2022, p. 23).
* Accuracy and Reliability of Biometric Systems
Although biometric technologies have significantly advanced, they are not infallible. Errors such as false positives or false negatives may occur, leading either to the wrong identification of an innocent person as a suspect or the failure to identify an actual criminal. These inaccuracies can be influenced by factors such as equipment quality, environmental conditions, or population diversity.
According to Guideline 05/2022 of the EDPB, "the level of necessary security measures depends on the magnitude of the risk posed by an Al system, which in turn depends on the system's capabilities" (EDPB, 2022, p. 19).
A concrete example of such errors was recorded in the United States, where facial recognition systems showed higher error rates in correctly identifying people of color and women. This has raised concerns about algorithmic bias and the possibility of incorrect and discriminatory identifications.
* Ethical and Social Implications
The widespread use of biometric technologies raises ethical concerns related to mass surveillance, discrimination, and privacy violations. There is a risk that these technologies could be misused to monitor populations without consent or target specific demographic groups, potentially leading to racial profiling and discrimination.
According to Guideline 05/2022 of the EDPB, "possible unintended applications of AI and its potential misuse by malicious actors should be considered; thus, measures should be adopted to prevent and mitigate such risks" (EDPB, 2022, p. 25).
Another critical aspect is the use of biometric data in authoritarian regimes for population surveillance and control. For example, in China, facial recognition systems are widely used for mass monitoring of citizens, raising concerns about individual freedom and the right to privacy.
Although biometric technologies offer powerful tools for law enforcement, their implementation must be accompanied by rigorous data protection measures, cybersecurity safeguards, and ethical considerations to ensure the protection of fundamental rights and public trust. Mass surveillance, algorithmic errors, and the potential for misuse are risks that must be carefully analyzed and properly managed.
5. Legislative Framework and Regulations on the Use of Biometric Technologies
The use of biometric technologies by law enforcement is regulated through a complex legislative framework at both the European and national levels, aiming to balance operational efficiency with the protection of fundamental citizens' rights. These regulations cover biometric data protection, the use of facial recognition systems, and the application of artificial intelligence in public security.
* European Legislative Framework
At the European Union level, the General Data Protection Regulation (GDPR), which came into effect in May 2018, sets strict standards for the processing of personal data, including biometric data. According to the GDPR, "biometric data is considered a special category of data, and its processing is only permitted under specific conditions, such as the explicit consent of the data subject or the necessity of processing for fulfilling legal obligations" (GDPR, 2018, Art. 9).
Additionally, the Artificial Intelligence Act (AI Act), adopted by the European Parliament in March 2024, introduces further regulations for AI systems used across various domains, including law enforcement.
This legislation aims to ensure safety and compliance with fundamental rights, imposing obligations based on the risks and potential impact of Al systems. For example, "the use of real-time biometric identification systems in public spaces by law enforcement authorities is subject to strict restrictions, being allowed only in specific situations and with appropriate safeguards" (European Parliament, 2024, р. 5).
* National Legislative Framework
In Romania, the use of biometric technologies is regulated through national legislation, which transposes and supplements European regulations. For example, Law No. 76/2023 on the Organization and Functioning of the National Signaling Information System and Romania's Participation in the Schengen Information System establishes the legal framework for the processing of biometric data in the context of international law enforcement cooperation. According to this law, "Romanian authorities may process biometric data for the identification and localization of wanted persons, in compliance with EU data protection legislation" (Law No. 76/2023, Art. 12).
Furthermore, the National Strategy on Artificial Intelligence (SN-IA) for 20242027, developed by the Ministry of Research, Innovation, and Digitalization, emphasizes the responsible use of Al technologies, including biometrics. The document states that "the implementation of facial recognition technologies must comply with ethical principles and respect the fundamental rights of citizens" (Ministry of Research, 2024, p. 8).
* Challenges and Perspectives
Although the current legislative framework provides a solid foundation for the use of biometric technologies by law enforcement, challenges remain regarding the uniform application of these regulations and their adaptation to rapid technological developments. A major challenge 1s personal data protection and the prevention of the misuse of biometric surveillance systems.
According to a report by the EU Agency for Fundamental Rights (FRA), "there is a risk that excessive use of biometric technologies by authorities could lead to mass surveillance and violations of the right to privacy" (FRA, 2023, p. 14). This concern is further amplified in countries where adequate data protection mechanisms are lacking, potentially resulting in discrimination and misuse.
Another crucial aspect is the harmonization of European legislation with national laws.
While the GDPR provides a general framework for biometric data protection, EU member states have the freedom to adopt additional rules, which may lead to significant differences in the use of these technologies across countries.
The use of biometric technologies in law enforcement is governed by a complex legislative framework designed to balance operational efficiency with the protection of fundamental rights.
European and national legislation provides mechanisms for the responsible use of these technologies, yet challenges related to data security, mass surveillance, and discrimination must be carefully addressed.
A responsible approach, compliant with existing regulations, is essential to ensure public trust and to fully leverage the potential of biometric technologies in serving society.
6. Future Perspectives and Recommendations
As biometric technologies continue to evolve, law enforcement agencies face significant opportunities as well as considerable challenges. To fully harness the potential of these technologies, a strategic and responsible approach is essential, taking into account current trends and expert recommendations.
* Developing Reliable Artificial Intelligence
A key aspect of using biometric technologies is ensuring the reliability of the artificial intelligence (AI) systems that support them. For these systems to be effectively used while complying with fundamental rights, they must meet criteria of transparency, accountability, and accuracy.
According to the European Union High-Level Expert Group on Artificial Intelligence, "reliable AI must be lawful, complying with all applicable laws and regulations; ethical, ensuring adherence to ethical principles and values; and robust, both from a technical and social perspective" (European Parliament, 2019, p. 8).
* Adopting an Adequate Ethical and Legal Framework
To successfully integrate biometric technologies into law enforcement activities, it is necessary to adopt a robust ethical and legal framework.
This framework should include clear rules on the collection, storage, and use of biometric data, as well as oversight and accountability mechanisms to prevent abuses and protect citizens' fundamental rights.
In the Artificial Intelligence Act (Al Act), adopted by the European Parliament in 2024, it is stated that "the use of biometric technologies in public spaces must comply with the principles of necessity and proportionality, being allowed only in exceptional cases and under strict control" (European Parliament, 2024, p. 5).
* Investing in Professional Training and Education
To ensure the efficient and ethical implementation of biometric technologies, it is crucial to properly train law enforcement personnel. This includes training in technology usage, understanding ethical and legal implications, and developing the necessary skills to responsibly manage sensitive data.
A report by the European Agency for Fundamental Rights (FRA) highlights that "the lack of training among personnel in the use of biometric systems can lead to the erroneous application of technology and violations of fundamental rights" (FRA, 2023, p. 12).
* Promoting Transparency and Public Engagement
Transparency in the use of biometric technologies is crucial for maintaining public trust. Engaging communities in the implementation process, through public consultations and open communication, can help identify concerns and develop solutions that meet societal needs.
According to the European Data Protection Board (EDPB), "any facial recognition system implemented y authorities must be accompanied by clear transparency measures, including informing citizens and allowing them to challenge the processing of biometric data" (EDPB, 2023, p. 9).
* Continuous Monitoring and Impact Assessment
It is important to establish monitoring mechanisms and impact assessments for the use of biometric technologies. These should include periodic evaluations of the efficiency and fairness of the systems, as well as analyses of their effects on individual rights and freedoms.
A report by the Council of Europe emphasizes that "regular assessments of the impact of biometric technologies on human rights are essential to ensure their use aligns with democratic principles" (Council of Europe, 2023, p. 18).
The integration of biometric technologies into law enforcement activities offers significant opportunities to enhance public security. However, it is essential that this integration is carried out responsibly, ensuring the protection of citizens' fundamental rights and promoting a fair and secure society.
The implementation of a clear legislative framework, investment in professional training, and the development of effective oversight mechanisms are essential measures to ensure the ethical and effective use of these technologies. Only through a transparent and balanced approach can we fully leverage the potential of biometrics while maintaining the protection of individual rights and freedoms.
7. Conclusions
The implementation of biometric technologies in law enforcement activities has brought significant progress in operational efficiency, public security, and suspect identification capabilities. However, the use of these technologies also presents major challenges related to personal data protection, cybersecurity, and ethical implications. For biometrics to be used effectively and responsibly, it is essential to maintain a balance between national security and fundamental citizen rights.
The benefits of biometric technologies are undeniable, facilitating the rapid and accurate identification of individuals, reducing crime, and optimizing law enforcement resources. Facial recognition, fingerprint identification, and behavioral analysis have allowed for "increased efficiency in criminal investigations and improved public safety" (Interpol, 2023, p. 6).
However, the use of these technologies raises concerns regarding data privacy, potential misuse, and technological errors.
According to a report by the EU Agency for Fundamental Rights, "biometric systems used by authorities must be subject to strong safeguards to prevent disproportionate use and excessive surveillance" (FRA, 2023, р. 11).
Another critical risk is algorithmic bias, which can lead to misidentifications and discrimination. Recent studies have shown that "biometric technologies have a higher error rate in identifying people of color and women, which can affect fairness in law enforcement" (European Commission, 2023, p. 9).
For biometric technology to be legally and ethically acceptable, authorities must find a balance between national security and the protection of fundamental rights.
The General Data Protection Regulation (GDPR) states that "the processing of biometric data must be Justified by a clear public interest, proportional to fundamental rights and freedoms" (GDPR, 2018, Art. 9).
This approach requires the adoption of oversight and transparency mechanisms, ensuring that biometric technology does not lead to systematic violations of privacy.
An example of a balanced regulation is the Artificial Intelligence Act (AI Act), Which imposes clear restrictions on the realtime use of facial recognition and establishes strict data protection criteria (European Parliament, 2024, p. 7).
To ensure the ethical and efficient use of biometric technology, several regulatory measures and best practices are necessary:
* Establishing clear data protection standards
Any use of biometric technology must comply with GDPR and the AI Act, and data processing must be proportional and justified. "Zaw enforcement agencies must implement specific measures to protect biometric data, including encryption and access restrictions" (EDPB, 2023, p.
* Monitoring and auditing biometric systems
The implementation of independent oversight mechanisms is essential to prevent the misuse of technology. According to the Council of Europe, "a framework for periodic audits and reporting is necessary to assess the impact of biometric technology on citizens' rights" (Council of Europe, 2023, p. 14).
* Increasing transparency and public engagement
Law enforcement agencies must adopt transparent policies, ensuring that the use of biometric technology is clearly understood by the public. "Informing citizens about the use of facial recognition and providing mechanisms to challenge automated decisions are essential for maintaining public trust" (FRA, 2023, p. 17).
* Developing more equitable and reliable algorithms
Reducing algorithmic bias is crucial to prevent discrimination and mis-identifications. "Biometric systems must undergo rigorous testing to ensure accuracy and eliminate technological biases" (European Commission, 2023, p. 12).
Biometric technologies have radically transformed identification methods and law enforcement operations, offering effective tools for combating crime and ensuring public safety. However, their use must be balanced to prevent abuses, excessive surveillance, or discrimination.
A responsible implementation, based on clear regulations, transparency, and data protection, will enable law enforcement agencies to leverage the benefits of biometrics without compromising fundamental citizen rights. As technology advances, it is crucial for society to remain vigilant and engaged to ensure that innovation is used for the benefit of all.
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