Browsing by Author "Seiling, Lukas"

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Beware: Processing of Personal Data—Informed Consent Through Risk Communication
(2024) Seiling, Lukas; Gsenger, Rita; Mulugeta, Filmona; Henningsen, Marte; Mischau, Lena; Schirmbeck, Marie
The General Data Protection Regulation (GDPR) has been applicable since May 2018 and aims to further harmonize data protection law in the European Union. Processing personal data based on individuals’ consent is lawful under the GDPR only if such consent meets certain requirements and is “informed,” in particular. However, complex privacy notice design and individual cognitive limitations challenge data subjects’ ability to make elaborate consent decisions. Risk-based communication may address these issues. **Literature review:** Most research focuses on isolated aspects of risk in processing personal data, such as the actors involved, specific events leading to risk formation, or distinctive (context-dependent) consequences. We propose a model combining these approaches as the basis for context-independent risk communication. **Research questions:** 1. What are relevant information categories for risk communication in the processing of personal data online? 2. Which potentially adverse consequences can arise from specific events in the processing of personal data online? 3. How can consequences in the processing of personal data be avoided or mitigated? **Research methodology:** The GDPR was examined through a systematic qualitative content analysis. The results inform the analysis of 32 interviews with privacy, data protection, and information security experts from academia, Non-Governmental Organizations, the public, and the private sector. **Results:** Risk-relevant information categories, specific consequences, and relations between them are identified, along with strategies for risk mitigation. The study concludes with a specified framework for perceived risk in processing personal data. **Conclusion:** The results provide controllers, regulatory bodies, data subjects, and experts in the field of professional communication with information on risk formation in personal data processing. Based on our analysis, we propose information categories for risk communication, which expand the current regulatory information requirements.
Regulating Digital Platforms in Times of Democratic Crisis – What is Next for Germany and the EU?
(Weizenbaum Institute, 2025-02) Iglesias Keller, Clara; Ohme, Jakob; Seiling, Lukas; Neuberger, Christoph
This paper examines recent changes in the content moderation practices of major social media companies. Digital platforms have become a defining feature of contemporary societies. As their infrastructures increasingly mediate commercial activity, political organization, cultural life, and more, the retraction of measures meant to uphold standards and trust in their influence over online speech raises significant concerns. This paper briefly analyzes these developments in the context of ongoing processes of democratic erosion, particularly in the U.S. The goal is to foster future research and public debate by offering key insights into the implications of the current scenario for Germany and the European Union.
Response to the Consultation on the Delegated Regulation on Data Access provided for in the Digital Services Act
(Weizenbaum Institute, 2024) Seiling, Lukas; Ohme, Jakob; Klinger, Ulrike
This response provides feedback on the Delegated Regulation on Data Access provided for in the Digital Services Act. It is informed by a variety of exchanges with empirical platform researchers across Germany and Europe. The first section highlights clarifications and proposed procedures for non-public data access which are practical, workable or welcomed by scientists for other reasons. The second section outlines further opportunities for clarification, additions, or modifications to the draft text, particularly regarding the data access procedure, the data access portal, the types of data, as well as the documentation and modalities of data access.
Supplemental material for “Beware: Processing of Personal Data—Informed Consent Through Risk Communication”
(2024) Seiling, Lukas; Gsenger, Rita; Mulugeta, Filmona; Henningsen, Marte; Mischau, Lena; Schirmbeck, Marie
Appendix A: GDPR content analysis Appendix B: Expert interview questions Appendix C: Results of the systematic qualitative content analysis of expert interviews
The Love of Large Numbers Revisited: A Coherence Model of the Popularity Bias
(2020) Heck, Daniel W.; Seiling, Lukas; Bröder, Arndt
Preferences are often based on social information such as experiences and recommendations of other people. The reliance on social information is especially relevant in the case of online shopping, where buying decisions for products may often be based on online reviews by other customers. Recently, Powell, Yu, DeWolf, and Holyoak (2017, Psychological Science, 28, 1432-1442) showed that, when deciding between two products, people do not consider the number of product reviews in a statistically appropriate way as predicted by a Bayesian model but rather exhibit a bias for popular products (i.e., products with many reviews). In the present work, we propose a coherence model of the cognitive mechanism underlying this empirical phenomenon. The new model assumes that people strive for a coherent representation of the available information (i.e., the average review score and the number of reviews). To test this theoretical account, we reanalyzed the data of Powell and colleagues and ran an online study with 244 participants using a wider range of stimulus material than in the original study. Besides replicating the popularity bias, the study provided clear evidence for the predicted coherence effect, that is, decisions became more confident and faster when the available information about popularity and quality was congruent.