A critique of current approaches to privacy in machine learning

Guardado en:
Detalles Bibliográficos
Publicado en:Ethics and Information Technology vol. 27, no. 3 (Sep 2025), p. 32
Autor principal: van Daalen, Florian
Otros Autores: Jacquemin, Marine, van Soest, Johan, Stahl, Nina, Townend, David, Dekker, Andre, Bermejo, Inigo
Publicado:
Springer Nature B.V.
Materias:
Acceso en línea:Citation/Abstract
Full Text
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

MARC

LEADER 00000nab a2200000uu 4500
001 3222714713
003 UK-CbPIL
022 |a 1388-1957 
022 |a 1572-8439 
024 7 |a 10.1007/s10676-025-09843-4  |2 doi 
035 |a 3222714713 
045 2 |b d20250901  |b d20250930 
084 |a 53312  |2 nlm 
100 1 |a van Daalen, Florian  |u Maastricht University Medical Centre, Radiation Oncology (MAASTRO) GROW School for Oncology and Reproduction, Maastricht, Netherlands (GRID:grid.412966.e) (ISNI:0000 0004 0480 1382); Maastricht University, Department of Health Promotion, Care and Public Health Research Institute (CAPHRI), Maastricht, Netherlands (GRID:grid.5012.6) (ISNI:0000 0001 0481 6099) 
245 1 |a A critique of current approaches to privacy in machine learning 
260 |b Springer Nature B.V.  |c Sep 2025 
513 |a Journal Article 
520 3 |a Access to large datasets, the rise of the Internet of Things (IoT) and the ease of collecting personal data, have led to significant breakthroughs in machine learning. However, they have also raised new concerns about privacy data protection. Controversies like the Facebook-Cambridge Analytica scandal highlight unethical practices in today’s digital landscape. Historical privacy incidents have led to the development of technical and legal solutions to protect data subjects’ right to privacy. However, within machine learning, these problems have largely been approached from a mathematical point of view, ignoring the larger context in which privacy is relevant. This technical approach has benefited data-controllers and failed to protect individuals adequately. Moreover, it has aligned with Big Tech organizations’ interests and allowed them to further push the discussion in a direction that is favorable to their interests. This paper reflects on current privacy approaches in machine learning and explores how various big organizations guide the public discourse, and how this harms data subjects. It also critiques the current data protection regulations, as they allow superficial compliance without addressing deeper ethical issues. Finally, it argues that redefining privacy to focus on harm to data subjects rather than on data breaches would benefit data subjects as well as society at large. 
610 4 |a Euronews European Union 
651 4 |a United States--US 
651 4 |a California 
653 |a Public interest 
653 |a Machine learning 
653 |a Personal information 
653 |a Internet of Things 
653 |a Science 
653 |a Organizations 
653 |a Privacy 
653 |a Data processing 
653 |a Personal health 
653 |a General Data Protection Regulation 
653 |a Right of privacy 
653 |a Human rights 
653 |a Social sciences 
653 |a Ethics 
653 |a Breaches 
653 |a Internet 
653 |a Scandals 
653 |a Data 
653 |a Ethical dilemmas 
653 |a Regulation 
653 |a Protection 
653 |a Data integrity 
653 |a Social 
700 1 |a Jacquemin, Marine  |u Maastricht University Medical Centre, Radiation Oncology (MAASTRO) GROW School for Oncology and Reproduction, Maastricht, Netherlands (GRID:grid.412966.e) (ISNI:0000 0004 0480 1382) 
700 1 |a van Soest, Johan  |u Maastricht University Medical Centre, Radiation Oncology (MAASTRO) GROW School for Oncology and Reproduction, Maastricht, Netherlands (GRID:grid.412966.e) (ISNI:0000 0004 0480 1382); Maastricht University, Brightlands Institute for Smart Society (BISS), Faculty of Science and Engineering, Maastricht, Netherlands (GRID:grid.5012.6) (ISNI:0000 0001 0481 6099) 
700 1 |a Stahl, Nina  |u University Maastricht, Department of Health, Ethics and Society (HES), Faculty of Health, Maastricht, Netherlands (GRID:grid.5012.6) (ISNI:0000 0001 0481 6099) 
700 1 |a Townend, David  |u University of London, City Law School, London, United Kingdom (GRID:grid.4464.2) (ISNI:0000 0001 2161 2573); University Maastricht, Department of Health, Ethics and Society (HES), Faculty of Health, Maastricht, Netherlands (GRID:grid.5012.6) (ISNI:0000 0001 0481 6099) 
700 1 |a Dekker, Andre  |u Maastricht University Medical Centre, Radiation Oncology (MAASTRO) GROW School for Oncology and Reproduction, Maastricht, Netherlands (GRID:grid.412966.e) (ISNI:0000 0004 0480 1382) 
700 1 |a Bermejo, Inigo  |u Maastricht University Medical Centre, Radiation Oncology (MAASTRO) GROW School for Oncology and Reproduction, Maastricht, Netherlands (GRID:grid.412966.e) (ISNI:0000 0004 0480 1382); Hasselt University, Data Science Institute, Hasselt, Belgium (GRID:grid.12155.32) (ISNI:0000 0001 0604 5662) 
773 0 |t Ethics and Information Technology  |g vol. 27, no. 3 (Sep 2025), p. 32 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3222714713/abstract/embedded/160PP4OP4BJVV2EV?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3222714713/fulltext/embedded/160PP4OP4BJVV2EV?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3222714713/fulltextPDF/embedded/160PP4OP4BJVV2EV?source=fedsrch