The ethics of facial recognition technologies, surveillance, and accountability in an age of artificial intelligence: a comparative analysis of US, EU, and UK regulatory frameworks

Abstract

The rapid development of facial recognition technologies (FRT) has led to complex ethical choices in terms of balancing individual privacy rights versus delivering societal safety. Within this space, increasingly commonplace use of these technologies by law enforcement agencies has presented a particular lens for probing this complex landscape, its application, and the acceptable extent of citizen surveillance. This analysis focuses on the regulatory contexts and recent case law in the United States (USA), United Kingdom (UK), and European Union (EU) in terms of the use and misuse of FRT by law enforcement agencies. In the case of the USA, it is one of the main global regions in which the technology is being rapidly evolved, and yet, it has a patchwork of legislation with less emphasis on data protection and privacy. Within the context of the EU and the UK, there has been a critical focus on the development of accountability requirements particularly when considered in the context of the EU’s General Data Protection Regulation (GDPR) and the legal focus on Privacy by Design (PbD). However, globally, there is no standardised human rights framework and regulatory requirements that can be easily applied to FRT rollout. This article contains a discursive discussion considering the complexity of the ethical and regulatory dimensions at play in these spaces including considering data protection and human rights frameworks. It concludes that data protection impact assessments (DPIA) and human rights impact assessments together with greater transparency, regulation, audit and explanation of FRT use, and application in individual contexts would improve FRT deployments. In addition, it sets out ten critical questions which it suggests need to be answered for the successful development and deployment of FRT and AI more broadly. It is suggested that these should be answered by lawmakers, policy makers, AI developers, and adopters.

Deep models of superficial face judgments

“…We argue that such methods (as well as their implementations and supporting data) should be made transparent from the start, such that the community can develop robust detection and defense protocols to accompany the technology, as they have done, for example, in developing highly accurate image forensics techniques to detect synthetic faces generated by SG2 ( 41 , 42 ). More generally, to the extent that improper use of the image manipulation techniques described here is not covered by existing defamation law ( 43 , 44 ), it is appropriate to consider ways to limit use of these technologies through regulatory frameworks proposed in the broader context of face-recognition technologies ( 45 , 46 ).…”

Artificial intelligence in education: Addressing ethical challenges in K-12 settings

“…We acknowledge that in centering this work within U.S. education, we highlight certain ethical issues that educators in other parts of the world may see as less prominent. For example, the European Union (EU) has highlighted ethical concerns and implications of AI, emphasized privacy protection, surveillance, and nondiscrimination as primary areas of interest, and provided guidelines on how trustworthy AI should be [3,15,23]. Finally, we reflect on future directions for educational and other research that could support K-12 teachers and students in reaping the benefits while mitigating the drawbacks of AI in education.…”

Proposed EU AI Act—Presidency compromise text: select overview and comment on the changes to the proposed regulation

“…Under Article 3 (12), these have been deemed not to have intended purpose within the meaning of AIA. What is the implication of this?…”