Background: Modern privacy regulations, such as the General Data Protection Regulation (GDPR), address privacy in software systems in a technologically agnostic way by mentioning general "technical measures" for data privacy compliance rather than dictating how these should be implemented. An understanding of the concept of technical measures and how exactly these can be handled in practice, however, is not trivial due to its interdisciplinary nature and the necessary technical-legal interactions.Aims: We aim to investigate how the concept of technical measures for data privacy compliance is understood in practice as well as the technical-legal interaction intrinsic to the process of implementing those technical measures.Methods: We follow a research design that is 1) exploratory in nature, 2) qualitative, and 3) interview-based, with 16 selected privacy professionals in the technical and legal domains.Results: Our results suggest that there is no clear mutual understanding and commonly accepted approach to handling technical measures. Both technical and legal roles are involved in the implementation of such measures. While they still often operate in separate spheres, a predominant opinion amongst the interviewees is to promote more interdisciplinary collaboration.Conclusions: Our empirical findings confirm the need for better interaction between legal and engineering teams when implementing technical measures for data privacy. We posit that interdisciplinary collaboration is paramount to a more complete understanding of technical measures, which currently lacks a mutually accepted notion. Yet, as strongly suggested by our results, there is still a lack of systematic approaches to such interaction. Therefore, the results strengthen our confidence in the need for further investigations into the technical-legal dynamic of data privacy compliance.
Issues of environmental security, fuel and energy independence have been forming political and economic territories for several centuries. Current events in Ukraine have become a litmus test, which clearly highlights the dangers of resource monopolies and the transfer of economic benefits. The issue of ensuring the energy system in climate neutrality became relevant even before the aggression by Russia. However, today, there is no country, it has not recognized that there is the urgent need to develop and implement effective tools for economic development in a sustainable environment. The modern cost-oriented model of knowledge of economic processes has led not only to the irrational use of natural potential. Large-scale use of natural resources and the irrational organization of production (including agricultural) disrupt the process of their reproduction, which, in turn, leads to the depletion of bioresources and, as a consequence, can lead humanity to ecological catastrophe. Certain solutions have been proposed to address these issues. To ensure the efficient use of the resources of the agricultural sector and the reliable reflection of biological processes, it is proposed to recognize the biological form of capital as self-growing and self-reproducing value, which, in the process of biological transformation, allows obtaining an additional unit of benefits. The study examines, in detail, the promising areas of the transformation of the agricultural sector in the framework of a technologically integrated European Green Deal in the EU. In this study, to determine the potential opportunities for the ecological transformation of agriculture, discrete analytical models of the assessment of the agro-industrial complex of Ukraine were used. Representative data use statistical indicators of Ukraine and, to illustrate potential opportunities, present a comparison of export data to EU countries. In addition, it reveals the realized and potential opportunities of Ukraine’s entry into the European market through the prism of the implementation programs of EU environmental policy. The place and significance of assimilation potential for a reduction in the anthropogenic impact on the environment, and providing the self-restoration of natural resources, are substantiated. It is determined that one of the most effective tools for low-cost reduction in greenhouse-gas emissions is the national-level implementation of environmental-quota trade and the development of organic production. The study includes an analytical assessment of the expected emission reductions from environmental initiatives’ implementation. Prospects for further research are the development of an effective mechanism for the systematic management of the biological potential reproduction of the agricultural sector while reducing anthropogenic impact on the environment.
As the tide of Big Data continues to influence the landscape of Natural Language Processing (NLP), the utilization of modern NLP methods has grounded itself in this data, in order to tackle a variety of text-based tasks. These methods without a doubt can include private or otherwise personally identifiable information. As such, the question of privacy in NLP has gained fervor in recent years, coinciding with the development of new Privacy-Enhancing Technologies (PETs). Among these PETs, Differential Privacy boasts several desirable qualities in the conversation surrounding data privacy. Naturally, the question becomes whether Differential Privacy is applicable in the largely unstructured realm of NLP. This topic has sparked novel research, which is unified in one basic goal: how can one adapt Differential Privacy to NLP methods? This paper aims to summarize the vulnerabilities addressed by Differential Privacy, the current thinking, and above all, the crucial next steps that must be considered.
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