Affiliation:
1. University of Vienna, Austria
Abstract
Recital 33 GDPR has often been interpreted as referring to ‘broad consent’. This version of informed consent was intended to allow data subjects to provide their consent for certain areas of research, or parts of research projects, conditional to the research being in line with ‘recognised ethical standards’. In this article, we argue that broad consent is applicable in the emerging field of Computational Social Science (CSS), which lies at the intersection of data science and social science. However, the lack of recognised ethical standards specific to CSS poses a practical barrier to the use of broad consent in this field and other fields that lack recognised ethical standards. Upon examining existing research ethics standards in social science and data science, we argue that they are insufficient for CSS. We further contend that the fragmentation of European Union (EU) law and research ethics sources makes it challenging to establish universally recognised ethical standards for scientific research. As a result, CSS researchers and other researchers in emerging fields that lack recognised ethical standards are left without sufficient guidance on the use of broad consent as provided for in the GDPR. We conclude that responsible EU bodies should provide additional guidance to facilitate the use of broad consent in CSS research.
Funder
the Austrian Federal Ministry of Education, Science and Research
Reference69 articles.
1. AI HILEG (2019) Ethics guidelines for trustworthy AI. European Commission. Available at: https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai. (accessed 15 February 2024).
2. The SAGE Handbook of Social Research Methods
3. The Jewish Chronic Disease Hospital Case
4. Article 29 Data Protection Working Party (2011) Opinion 15/2011 on the definition of consent. Available at: https://ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2011/wp187_en.pdf.