Smart cities and privacy: comparative analysis of Japan and China on the use of facial recognition technology in public spaces

Facial recognition technology (FRT) offers police a fast, efficient, and accurate way of identifying criminals. However, as with any new technology, the public is often sceptical about how the police will use this technology and how it may impinge on the public’s privacy and security. Subsequently, if police use of FRT is perceived as illegitimate, police-citizen relationships may deteriorate – this is especially concerning given the current lack of trust and confidence in police as expressed in the Black Lives Matter movement and other protests against police actions. This paper takes a novel approach to examining public opinions and attitudes about the use of FRT by police. To do this, we thematically analysed 609 public commentary posts published on 71 YouTube clips about police use of FRT. We found that the public in this sample expressed mostly negative sentiments about the use of FRT by police, identifying three main concerns: authority and power, technology, rights and freedoms. However, we also found some support for police using FRT. These findings are discussed in terms of the theoretical concept of the new regulatory state; in particular steering (government policy) and rowing (implementation). These findings suggest that if police authorities and policy makers address these specific concerns by being transparent in their practices and educate the public about misinformation, then policing agencies may have an increase support for the use of FRT by police and, moreover, build trust and confidence in police.

Live automated facial recognition technology, rolled out in public spaces and cities across the world, is transforming the nature of modern policing. R (on the application of Bridges) v Chief Constable of South Wales Police, decided in August 2020, is the first successful legal challenge to automated facial recognition technology in the world. In Bridges, the United Kingdom’s Court of Appeal held that the South Wales Police force’s use of automated facial recognition technology was unlawful. This landmark ruling could influence future policy on facial recognition in many countries. The Bridges decision imposes some limits on the police’s previously unconstrained discretion to decide whom to target and where to deploy the technology. Yet, while the decision requires that the police adopt a clearer legal framework to limit this discretion, it does not, in principle, prevent the use of facial recognition technology for mass-surveillance in public places, nor for monitoring political protests. On the contrary, the Court held that the use of automated facial recognition in public spaces – even to identify and track the movement of very large numbers of people – was an acceptable means for achieving law enforcement goals. Thus, the Court dismissed the wider impact and significant risks posed by using facial recognition technology in public spaces. It underplayed the heavy burden this technology can place on democratic participation and freedoms of expression and association, which require collective action in public spaces. The Court neither demanded transparency about the technologies used by the police force, which is often shielded behind the “trade secrets” of the corporations who produce them, nor did it act to prevent inconsistency between local police forces’ rules and regulations on automated facial recognition technology. Thus, while the Bridges decision is reassuring and demands change in the discretionary approaches of U.K. police in the short term, its long-term impact in burning the “bridges” between the expanding public space surveillance infrastructure and the modern state is unlikely. In fact, the decision legitimizes such an expansion.

From Digital Platforms to Facial Recognition Technologies: Structural Challenges to Women’s Activism

When a crime is captured on video, law enforcement agencies increasingly have used facial recognition technology (FRT) to generate suspects to investigate. However, there are increasing examples of people who have been wrongfully arrested based because of the inaccurate results returned from these artificial intelligence-assisted searches of facial databases, despite very low error rates in the accuracy of these systems. We discuss the reliability of the evidence provided by a match returned by FRT, propose a framework for identifying potential problems with the use of FRT in criminal investigations, and review the research on the general trauma that comes from justice system involvement, trauma that is compounded by wrongful arrest and conviction. We also provide an analysis of how database size affects the evidentiary value of the matches returned by FRT. Variables like facial database size, race of the culprit, and quality of the probe photo can increase the likelihood that FRT systems will return false positive matches. The use of FRT for developing suspects in criminal investigations is likely to exacerbate the already profound racial disparities in the outcomes produced by the criminal legal system and increase trauma experienced by those who are wrongfully arrested or convicted. We recommend extreme caution surrounding its use. In addition, we call for more research on the trauma associated with wrongful arrest, which is likely to occur with the current use of FRT. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

This article analyses the use of facial recognition technology (FRT) in (semi-)public spaces with a focus in the Brazilian context. Therefore, the operation of the FRT processing chain is addressed, as well as the juridical nature of the facial signature, focusing mainly in the Brazilian data protection framework. FRT has been used in everyday life for several purposes, such as security, digital ranking, targeted marketing and health protection. However, the indiscriminate use of FRT poses high risks to privacy and data protection. In this perspective, to avoid harms such as inaccuracy, normalisation of cyber-surveillance and lack of transparency, safeguards were identified to guarantee individual rights, such as soft law, oversight, international standards and regulatory sandboxes.

PurposeBig Data has become crucial for fulfilling the vision of smart cities; however, there are several challenges associated with its use. This study aims to provide a holistic view of challenges of using Big Data in smart cities and the solutions to deal with them by systematically selecting, reviewing and synthesizing the literature in this area.Design/methodology/approachA systematic literature review was conducted by following a rigorous search protocol that identified a total of 310 peer-reviewed academic research papers. These papers were subsequently filtered and finally 38 relevant papers were selected.FindingsA number of major challenges (human dynamics, privacy, security, volume, velocity, variety, veracity and value) associated with Big Data in a smart city and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing Big Data in smart cities.Practical implicationsThe study provides valuable information to the Big Data practitioners by illustrating the process of effective management of Big Data in smart cities. This study further provides the directions to the future researchers.Originality/valueThe study is original and is based on the existing literature and its interpretation.

The Facial Recognition Technology (FRT) is used to match a photo of a person's face through a database that contains picture, name, and other records of someone that are already in the database. This technology uses biometric data with other available information and provides precise and accurate information about a person and his behaviour. FRT has positioned itself significantly advanced among all biometric-based technologies. The use of FRT by government agencies and commercial organisation comes under scrutiny as many of them use the technology in violation of right to privacy where the data subjects are either not informed of data collection or not consented for the data collection, use or storage of their data. Privation of regulatory measures allows government agencies and commercial organisations to operate with no real legal restraint and only under limited self-regulation in many common law countries. The research focuses on suitability of the existing law to regulate the use of FRT by analysing the criminal law and the civil law including the privacy laws in few common law countries. The analysis of the laws shows that passing of appropriate laws is inevitable as the existing laws are inadequate to regulate the use of FRT by government and commercial organisations.

The use of facial recognition technology has given rise to much debate relating to issues concerning privacy infringements, bias and inaccuracies of data and outputs, possibilities of covert use, the lack of data security and the problem of function creep. Certain states and jurisdictions have called for bans and moratoria on the use of facial recognition technology. This article argues that a blanket ban on facial recognition technology would be overly precautionary without fully considering the wide range of uses and benefits of the innovation. To promote its acceptance, trust in facial recognition technology should be developed in a calibrated fashion taking into account the relative risks and benefits, risk mitigation measures and safeguards based on legal and ethical considerations. This article recommends some guidelines for a calibrated trust-based approach.

In the era of the rapid development of big data, facial recognition biometric technology, which identifies and confirms the identity of persons by their face, is gradually becoming an object of public attention. Developing facial recognition technology has become an indispensable means of collecting information for government and commercial organizations. Facial recognition technology can be used to quickly identify individuals and improve efficiency and accuracy. However, there are two sides to everything, and the widespread use of facial recognition technology has affected the traditional system of protecting the citizen’s right to a facial image, and the relevant laws should be improved in connection with the leakage and misuse of facial images. Only under the double safeguard, both the advancement of facial recognition technology and the improvement of laws can further protect the citizen’s right to a facial image. This article analyzes the use of facial recognition technology and the risks associated with it, explains the legislative framework and its shortcomings in China, and makes appropriate proposals for further protection of the generated facial image information in facial recognition technology.

Facial Recognition: Why We Should Worry About the Use of Big Tech for Law Enforcement

This article examines the human rights challenges of police use of facial recognition technology from a European perspective. Based on both international human rights law, the European Convention on Human Rights and EU law, the article argues that the technology challenges human rights. The focus of the article is on the right to privacy and data protection, as this right is fundamentally at risk by the technology. Acknowledging that other rights and guarantees are also negatively impacted by the use of facial recognition technology, the article makes reference to the risk of discrimination, and the unregulated cooperation between State and the surveillance technology industry. However, a central point in the article is that irrespective of whether the technology can be refined to eliminate risk of discrimination, and even if sufficient safeguards for cooperation between State and the industry are put in place, fundamental challenges remain in relation to the right to privacy and data protection. The technology captures the unique facial features of an individual known as biometric data which is highly sensitive data and creates an interference with the right to privacy and data protection. By allowing facial recognition, society allows for an entirely new type of intensive surveillance. The use of the technology also entails a risk of chilling effect on e.g. freedom of assembly which furthers negative implications on human rights. The article concludes that when it comes to police use of facial recognition technologies, States should tread carefully and ensure that a sufficient human rights-based regulatory framework and adequate safeguards are in place before considering using the technology.

Facial recognition technology (FRT) is a tool used to identify individuals by scanning their face and comparing it to a database of facial images. In the last decade, the use of FRT has rapidly increased and is now used all around the world. This has resulted in many ethical issues caused by taking an individual’s images without consent to train FRT programs, FRT misidentifying individuals, and using FRT to classify individuals as part of specific groups based on appearance alone. Because of these issues, a new code of ethics is proposed to provide a guideline for the creation and use of FRT. The code of ethics will prevent images of individuals from being taken and used without their consent and prevent FRT from being used unethically.

In this contribution, we provide insight into the complex interplay between criminal procedure law and data protection law when it comes to regulating police use of facial recognition technology. By analysing the Dutch ‘Police Deployment Framework for Facial Recognition Technology’, we show that data protection law and criminal procedure do not interact with each other to a sufficient degree in relation to facial recognition technology. We identify several barriers standing in the way of their cooperation, resulting in notable gaps in the system of checks and balances: (1) a different underlying mindset (maximum versus minimum use of data); (2) a different assessment of the required legal basis (proportionality versus strict necessity); and (3) an ineffective web of supervision. We suggest several ideas for filling these gaps and bridging the disconnection: following the approach in existing Dutch law used for the processing of ANPR and DNA data, encoding the less ‘muddy’ rules of data protection law into digital technology itself, and further research on the feasibility of effective supervision by the Dutch Data Protection Authority. Our contribution shows that in order to properly regulate facial recognition technology, scholars need to look beyond the edges of their own fields of law.

Esports (‘competitive video games’ or ‘electronic sports’) have rapidly developed. Currently, the esports industry is composed of many esports stakeholders and becomes one of the worldwide economic markets. Due to such rapid growth, however, the esports society has faced many problems, such as doping, match-fixing, physical and mental health issues, and sexual harassment against vulnerable esports players etc. In this situation, some states enact national legislation on video games to protect children against negative consequences, such as violent scenes, images of sexual expression, gaming addiction and disorders. National legislation has created an age limitation for children to play competitive video games. Despite this, children still have access to esports activities because their parents or other adult give them prohibited video games. Therefore, it is difficult for states to restrict children’s access to competitive video games. In this situation, this chapter considers whether esports society should use facial recognition technology to protect youth esports players. To answer this main question, this chapter will examine the following research questions: (1) How has facial recognition technology been used in esports society?; (2) What human rights risks can be identified due to the use of facial recognition technology?; and (3) How should the esports society strike a balance between youth protection in esports and human rights risks caused by the use of facial recognition technology? Through this research, it may clarify how esports publishers and esports event/league organisers may evaluate the impact on fundamental human rights by using facial recognition technology in the esports society.

Employing facial recognition technology implicates anti-discrimination law under Title VII of the Civil Rights Act when used as a factor in employment decisions. The very technological breakthroughs that made facial recognition technology commercially viable—data compression and artificial intelligence— also contribute to making facial recognition technology discriminatory in its effect on members of classes protected by Title VII. This Article first explains how facial recognition technology works and its application in employee background checks. Then, it analyzes whether the use of facial recognition technology in background checks violates Title VII under the disparate impact theory of liability due to the known issue of skewed data sets and disproportionate inaccuracy on some populations. The Article concludes by calling on the Equal Employment Opportunity Commission to issue specific guidance warning employers of impending liability under Title VII, including class action liability, due to the use of facial recognition technology, and to use its enforcement authority to file lawsuits against employers who continue to use the technology.