Opportunities and Challenges of Dynamic Consent in Commercial Big Data Analytics - Privacy and Identity Management. Data for Better Living: AI and Privacy
Conference Papers Year : 2020

Opportunities and Challenges of Dynamic Consent in Commercial Big Data Analytics

Abstract

In the context of big data analytics, the possibilities and demands of online data services may change rapidly, and with it change scenarios related to the processing of personal data. Such changes may pose challenges with respect to legal requirements such as a transparency and consent, and therefore call for novel methods to address the legal and conceptual issues that arise in its course. We define the concept of ‘dynamic consent’ as a means to meet the challenge of acquiring consent in a commercial use case that faces change with respect to re-purposing the processing of personal data with the goal to implement new data services. We present a prototypical implementation that facilitates incremental consent forms based on dynamic consent. We report the results gained via two focus groups which we used to evaluate our design, and derive from our findings implications for future directions.
Fichier principal
Vignette du fichier
496005_1_En_3_Chapter.pdf (292.22 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03378972 , version 1 (14-10-2021)

Licence

Identifiers

Cite

Eva Schlehahn, Patrick Murmann, Farzaneh Karegar, Simone Fischer-Hübner. Opportunities and Challenges of Dynamic Consent in Commercial Big Data Analytics. 14th IFIP International Summer School on Privacy and Identity Management (Privacy and Identity), Aug 2019, Windisch, Switzerland. pp.29-44, ⟨10.1007/978-3-030-42504-3_3⟩. ⟨hal-03378972⟩
80 View
56 Download

Altmetric

Share

More