Research area
Opt-in Layer
Consent as granular, revocable tokens. Local-first architectures. User-driven data flows that providers and customers can verify and reset themselves — including withdrawal from data-marketplace participation at any time.
The Opt-in Layer research explores how a service booking platform can offer meaningful, transparent and user-driven control over personal data. We investigate consent not as a single checkbox at signup, but as a continuous protocol that runs alongside every interaction — granular enough to apply per-action, revocable in one tap, and verifiable at any time.
This work connects directly to our active Ethical Data Economy theses: users grant consent for specific data marketplace participation, and that consent must be withdrawable at any point — including after data has already been encoded into the cryptographic contribution layer. Meaningful consent requires three things in concert: a UX that doesn't impose cognitive overload, an architecture that doesn't leak by default, and revocability that holds through cryptographic encodings.
Thesis in this area
Thesis 01
User-Centered Consent Flow
The thesis designs and prototypes a user-centered consent flow aligned with dynamic consent principles: lifecycle-based design, a centralized dashboard for reviewing and modifying past decisions, a history view for transparency and accountability, and structured interfaces using purpose categorization and dropdown controls.
The prototype was evaluated through criteria-based assessment combined with user testing involving fifteen participants. Findings: strong performance on transparency and absence of manipulative design, with users particularly valuing the dashboard for reviewing past decisions. Cognitive load emerged as the binding scalability constraint — as data categories, processing purposes and third-party actors grow, users perceive even hierarchically-structured prototypes as increasingly hard to manage.
The thesis concludes that scalability requires moving beyond interface design to systemic data practices: the consent UI cannot rescue an architecture that demands too many decisions from the user. Meaningful consent requires the architecture itself to ask less of the user in the first place.
Across the work in this area
Key themes
- Dynamic consent — lifecycle-based, not a one-time signup checkbox
- User-centered consent flow design: purpose categorization, dashboard, history view
- Cognitive load as the binding scalability constraint in consent UX
- Privacy-by-design architectural principles for centralized data sharing
- GDPR-aligned system components for a social booking platform
- Privacy-engineering techniques: anonymization, differential privacy, synthetic data
- Consent withdrawal in cryptographically-encoded data marketplaces
- Local-first architectures reducing unnecessary data exposure