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AI and Big Data: A blueprint for a human rights, social and ethical impact assessment
Open accessAbstract
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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Cited by
Artificial Intelligence Regulation: A framework for governance
de Almeida, P. G. R., dos Santos, C. D., & Farias, J. S. (2021) · Ethics and Information Technology · doi:10.1007/s10676-021-09593-z · Cited by 395
Ali, O., Murray, P. A., Momin, M., Dwivedi, Y. K., & Malik, T. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2023.123076 · Cited by 317
Auditing large language models: a three-layered approach
Mökander, J., Schuett, J., Kirk, H. R., & Floridi, L. (2024) · AI and Ethics · doi:10.1007/s43681-023-00289-2 · Cited by 289
Akinrinola, O., Okoye, C. C., Ofodile, O. C., & Ugochukwu, C. E. (2024) · GSC Advanced Research and Reviews · doi:10.30574/gscarr.2024.18.3.0088 · Cited by 206
Algorithmic Impact Assessments and Accountability: The Co-construction of Impacts
Metcalf, J., Moss, E., Watkins, E. A., Singh, R., & Elish, M. C. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445935 · Cited by 195
Metadata
- Authors
- Mantelero, A.
- Venue
- Computer Law & Security Review
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 34
- Issue
- 4
- Pages
- 754-772
- ISSN
- 2212-473X (ISSN-L)
- OpenAlex
- W2884074583
- Cited by
- 305
- References
- 0
- FWCI
- 137.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- creativecommons.org/licenses/by-nc-nd/4.0/ (vor)
- Funders
- Horizon 2020 (732027)
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- Mantelero, A. (2018). AI and Big Data: A blueprint for a human rights, social and ethical impact assessment. Computer Law & Security Review. https://doi.org/10.1016/j.clsr.2018.05.017
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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