Erosion by Standardisation

Christofi, Athena; Dewitte, Pierre; Ducuing, Charlotte; Valcke, Peggy

doi:10.4018/978-1-5225-9489-5.ch008

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…As explained by Christofi et al (2021) , important differences exist between the conceptions of rights as intended by the GDPR (see Jones, 2017 ), and their enactments through instruments of co-regulation, usually shaped by private and semi-public actors such as the standards organizations and enacted as managerialism ( Waldman, 2021 ). Following this, the problem can now be articulated in terms of two different ontologies.…”

Section: Discussion: Shifting Boundaries Of Techno-regulationmentioning

confidence: 99%

Privacy engineering and the techno-regulatory imaginary

Rommetveit

Dijk

2022

Soc Stud Sci

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The European Union’s General Data Protection Regulation (GDPR), in force since 2018, has introduced design-based approaches to data protection and the governance of privacy. In this article we describe the emergence of the professional field of privacy engineering to enact this shift in digital governance. We argue that privacy engineering forms part of a broader techno-regulatory imaginary through which (fundamental) rights protections become increasingly future-oriented and anticipatory. The techno-regulatory imaginary is described in terms of three distinct privacy articulations, implemented in technologies, organizations, and standardizations. We pose two interrelated questions: What happens to rights as they become implemented and enacted in new sites, through new instruments and professional practices? And, focusing on shifts to the nature of boundary work, we ask: What forms of legitimation can be discerned as privacy engineering is mobilized for the making of future digital markets and infrastructures?

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Section: Discussion: Shifting Boundaries Of Techno-regulationmentioning

confidence: 99%

Privacy engineering and the techno-regulatory imaginary

Rommetveit

Dijk

2022

Soc Stud Sci

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Modeling ecosystems of reference frameworks for assurance: a case on privacy impact assessment regulation and guidelines

et al. 2022

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To assure certain critical quality properties (e.g., safety, security, or privacy), supervisory authorities and industrial associations provide reference frameworks such as standards or guidelines that in some cases are enforced (e.g., regulations). Given the pace at which both technical advancements and risks appear, there is an increase in the number of reference frameworks. As several frameworks might apply for same systems, certain overlaps appear (e.g., regulations for different countries where the system will operate, or generic standards in conjunction with more concrete standards for a given industrial sector or system type). We propose the use of modelling for alleviating the complexity of these reference frameworks ecosystems, and we provide a tool-supported method to create them for the benefit of different stakeholders. The case study is based on privacy data protection, and more concretely on privacy impact assessment processes. The European GDPR regulates the movement and processing of personal data, and, contrary to available software engineering privacy guidelines, articles in legal texts are usually difficult to translate to the underlying processes, artefacts and roles that they refer to. To facilitate the mutual comprehension of legal experts and engineers, in this work we investigate how mappings can be created between these two domains of expertise. Notably, we rely on modelling as a central point. We modelled the legal requirements of the GDPR on data protection impact assessments, and then, we selected the ISO/IEC 29134, a mainstream engineering guideline for privacy impact assessment, and, taking a concrete sector as example, the EU Smart Grid Data Protection Impact Assessment template. The OpenCert tool was used for providing technical support to both the modelling and the creation of the mapping models in a systematic way. We provide a qualitative evaluation from legal experts and privacy engineering practitioners to report on the benefits and limitations of this approach.

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Normative Challenges of Risk Regulation of Artificial Intelligence

Orwat,

Bareis,

Folberth

et al. 2024

Nanoethics

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Approaches aimed at regulating artificial intelligence (AI) include a particular form of risk regulation, i.e. a risk-based approach. The most prominent example is the European Union’s Artificial Intelligence Act (AI Act). This article addresses the challenges for adequate risk regulation that arise primarily from the specific type of risks involved, i.e. risks to the protection of fundamental rights and fundamental societal values. This is mainly due to the normative ambiguity of such rights and societal values when attempts are made to select, interpret, specify or operationalise them for the purposes of risk assessments and risk mitigation. This is exemplified by (1) human dignity, (2) informational self-determination, data protection and privacy, (3) anti-discrimination, fairness and justice, and (4) the common good. Normative ambiguities require normative choices, which are assigned to different actors under the regime of the AI Act. Particularly critical normative choices include selecting normative concepts by which to operationalise and specify risks, aggregating and quantifying risks (including the use of metrics), balancing value conflicts, setting levels of acceptable risks, and standardisation. To ensure that these normative choices do not lack democratic legitimacy and to avoid legal uncertainty, further political processes and scientific debates are suggested.

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Erosion by Standardisation

Cited by 4 publications

References 17 publications

Privacy engineering and the techno-regulatory imaginary

Privacy engineering and the techno-regulatory imaginary

Modeling ecosystems of reference frameworks for assurance: a case on privacy impact assessment regulation and guidelines

Normative Challenges of Risk Regulation of Artificial Intelligence

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