Big Data: concepts, signs and challenges (criminal legal aspect)

Abstract

The article examines the content and features of the Big Data phenomenon, the concept of which is currently undergoing dynamic development. The author analyzes such features as an unprecedentedly large amount of information without any data loss, hidden potential for repeated value, transition to correlations instead of causality, etc. The sources of Big Data are reviewed. The author emphasizes the effect of combining data from different sources in order to improve the quality of the information itself and the efficiency of its processing. It is argued that due to the large amount of information, the prerogative of decision-making is gradually shifting from a person to an algorithm which acquires the characteristics of a subject of legal relations. The author analyzes the correlation between the right to be forgotten and its opposite, “permanent memory”, as well as the conflict between the right to be forgotten and the ideology of Big Data. It is proved that the ability to monitor an individual is now built into virtually all algorithms, software and hardware, the technological nature of which allows data to be exchanged with the manufacturer, operator and/or other interested parties without requiring intervention by their owner or user.The author considers the options for informed consent in case of changing the purpose of personal data use. It is proved that in some cases personal data arise as a side effect of the functioning of a complex of integrated components of a cybernetic system. It is argued that with the advent of Big Data, such privacy strategies as informed consent, differential privacy, opt-out and anonymization are gradually losing their effectiveness.The author proposes to consider a personal data subject as a point of intersection of information flows and as a set of social ties, and therefore, to obtain comprehensive information about him or her, it is sufficient to analyze and systematize all available peripheral non-personal data. It is proved that the removal of certain information from a dataset may be equal to its presence. Certain types of criminal offenses in the field of Big Data and means of counteracting them are investigated. The author formulates the types of challenges that may arise in connection with the use of Big Data, in particular, violation of privacy, confidentiality and deanonymization, replacement of causality with correlation in the legal sphere.