Law. Human. Environment (May 2025)
Balancing public safety and civil rights: Successes and challenges of AI-based video surveillance systems
Abstract
In contemporary society, security has acquired exceptional importance, prompting increasing interest in intelligent video surveillance. The aim of this study was to conduct a systematic analysis of current approaches to AI-powered video analytics, encompassing technological algorithms, legal constraints, and the social implications of their application. The methodology employed an interdisciplinary approach combining systems analysis, legal and comparative methods, analytical review, and case study analysis. The research examined the functional capabilities of intelligent video systems based on machine learning and deep learning. It revealed that although modern AI video analytics systems are highly effective in enhancing security (e.g., threat detection and behavioural analysis), they also generate significant ethical and legal risks – particularly with respect to privacy violations and algorithmic discrimination. A comparative legal analysis highlighted marked differences in regulatory models across jurisdictions: European systems emphasise privacy protection, while the Chinese approach prioritises threat prevention. AI-powered video analytics has had a profound impact on the right to privacy, particularly due to the mass collection of biometric data and automated profiling, sparking debate over compliance with international standards such as the General Data Protection Regulation and the Convention for the Protection of Human Rights. The comparative analysis demonstrated divergent approaches: in the EU, privacy protection is paramount (e.g., the ban on facial recognition in France), whereas China and the United States focus more on security – often at the expense of civil liberties. Regulatory challenges include the misalignment of national laws with international norms, especially regarding data retention and algorithmic bias. To strike a balance, the study proposed clear legal frameworks, limitations on data storage periods, independent oversight, and “ethical passports” for algorithms – measures that would combine technological efficacy with the safeguarding of human rights. The study recommends harmonising standards that take into account both technical capacities and ethical-legal norms. The practical value lies in the potential use of the findings to design balanced AI video analytics systems
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