Principles of Personal Data Processing: Functional Classification as a Basis for Differentiated Legal Regulation

This study focuses on the transformation of personal data processing principles under the influence of digital technologies. The subject of the research is the principles enshrined in Article 5 of the Federal Law of the Russian Federation No. 152-FZ of July 27, 2006, "On Personal Data," and their capacity to address the challenges posed by automated processing, profiling, and algorithmic decision-making. A key contradiction is identified: the universal model based on these principles fails to account for the functional heterogeneity of data. In the digital environment, the same information can assume different roles, generating risks such as loss of control over digital identity, covert behavioral influence, and the making of legally significant decisions based on opaque algorithmic models. The aim of the work is to develop a system of principles that facilitates a transition towards a differentiated, risk-oriented model of legal regulation. The research is directed at identifying the constitutional foundations for such differentiation and formulating guarantees for protecting the rights of persons in the context of digitalization and the deployment of artificial intelligence. The methodological framework comprises formal legal analysis, comparative legal analysis, systemic analysis, and the author's method of functional classification. A comparative analysis is conducted with the provisions of the GDPR and the EU Artificial Intelligence Act (AI Act) of 2024. The scientific novelty lies in substantiating five principles of personal data processing: functional differentiation, risk-orientation, algorithmic accountability and explainability, the presumption against discriminatory profiling, and the right to human review of status-determining decisions. The proposed hierarchical model of their interrelationship also possesses novelty: the first two principles serve as the foundation and the measure, while the subsequent three function as legal mechanisms protecting against the most risk-prone types of processing. Theoretical significance: the proposed system allows for the enrichment of the doctrine of constitutional and information law by considering data protection as a guarantee of personal autonomy, equality, and justice in the context of algorithmic decision-making. Practical significance is expressed in the formation of a conceptual basis for improving Federal Law No. 152-FZ of July 27, 2006, "On Personal Data," thereby creating a foundation for the differentiated application of principles depending on the functional role of the data. Consequently, the implementation of the proposed model becomes a necessary condition for the protection of constitutional rights in the context of digitalization, ensuring a balance between technological development and fundamental human rights.