Computer law & security review · 2018 · 282 citations · 1 references
ComputingInformation SystemsInformation TechnologyArtificial IntelligenceData EthicsHuman RightsData GovernanceData PrivacyData ProtectionData SecurityBig Data ArchitectureBig Data EthicsData RightsData-intensive ComputingEthical Use Of DataHuman Rights MechanismsSocial Impact
Algorithms and data‑intensive technologies demand a broader data protection impact assessment that considers the effects of data processing on fundamental rights and collective social and ethical values. The article proposes the Human Rights, Ethical and Social Impact Assessment (HRESIA) model to embed a human‑rights perspective into data protection assessments and to overcome the narrow focus or excessive complexity of existing models. HRESIA comprises a self‑assessment questionnaire and an ad hoc expert committee, and this paper outlines its architecture and challenges, with detailed questionnaire content to follow in future work.
The use of algorithms in modern data processing techniques, as well as data-intensive technological trends, suggests the adoption of a broader view of the data protection impact assessment. This will force data controllers to go beyond the traditional focus on data quality and security, and consider the impact of data processing on fundamental rights and collective social and ethical values. Building on studies of the collective dimension of data protection, this article sets out to embed this new perspective in an assessment model centred on human rights (Human Rights, Ethical and Social Impact Assessment-HRESIA). This self-assessment model intends to overcome the limitations of the existing assessment models, which are either too closely focused on data processing or have an extent and granularity that make them too complicated to evaluate the consequences of a given use of data. In terms of architecture, the HRESIA has two main elements: a self-assessment questionnaire and an ad hoc expert committee. As a blueprint, this contribution focuses mainly on the nature of the proposed model, its architecture and its challenges; a more detailed description of the model and the content of the questionnaire will be discussed in a future publication drawing on the ongoing research.
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Artificial Intelligence, Ethics, and Enhanced Data Stewardship
Martin Abrams, John Abrams, Peter Cullen et al. · IEEE Security & Privacy · 2019 · 26 citations