MSc Thesis Supervision
Below are open topics for MSc thesis projects supervised by myself and Asia Biega. These topics are for the Summer 2025 semester, and you must be enrolled at Ruhr University Bochum. Please contact me at lin.kyi@mpi-sp.org if these sound interesting to you, or if you have further questions.
Topic 1: User acceptance of alternative forms of data collection
Motivation: Consent notices have been proven to be ineffective at informing users about how their data is collected, and for collecting consent itself [1, 2]. Additionally, consent notices are unable to keep up with advances in AI technologies, such as generative AI, where the data inputs are unknown and difficult to trace [3]. Therefore, we need another way of responsibly collecting data that doesn’t rely on consent notices.
Research problem: In this MSc thesis project, the student will be conducting a user study to gauge users’ acceptance and perceptions or various forms of non-consent based data collection, such as basic defaults, data collectives, etc. The student will investigate how different forms of responsible data collection are perceived by users, and come up with suggestions for improving data collection based on these insights.
Requirements: Experience with, or knowledge of, survey techniques, or be open to learning
The student should have experience (or be open to learning) conducting quantitative surveys with users
Additionally, experience with the user study pipeline (participant recruitment, forming interview/survey questions, and data analysis) is important for this project.
Topic 2: How users reason about compatibility of data collection purposes
Motivation: Purpose compatibility, which is where data collection purposes are perceived as being aligned with each other, is important for data repurposing (where data collected for one purpose is reused for another purpose) [1] and basic defaults (a possible solution to replace consent notices) [2]. When purposes are perceived to be aligned, data reuse can happen more responsibly [1]. However, there is a gap in the literature about which purposes are perceived to be aligned with each other, and how data reuse can happen more responsibly.
Research problem: This MSc thesis project will entail an investigation into which data collection purposes are perceived as being aligned with each other according to users, and why they might be aligned. The project will provide insights into how data reuse can be more responsible, an important research problem in the age of AI and data collection.
Requirements: Experience with, or knowledge of, survey and/or user interview techniques, or be open to learning
The student should have experience (or be open to learning) conducting quantitative surveys and/or qualitative interviews with users
Additionally, experience with the user study pipeline (participant recruitment, forming interview/survey questions, and data analysis) is important for this project.