Gemeente Amsterdam Veilig
Designing a safer, more humane way to connect citizens with government benefits.
Overview
This project was undertaken as part of my Master’s in Digital Design, in collaboration with Gemeente Amsterdam.
The brief was not to redesign a single interface, but to rethink how government benefits are distributed. Today, citizens must actively apply for resources, while eligibility is assessed through rule-based algorithms that often lack transparency, context, and empathy.
The challenge
In the existing system:
- Citizens must request benefits they are already entitled to
- Algorithms flag potential fraud without explanation
- Decision-making lacks human context
- Data usage is opaque, reducing trust
- Services are fragmented across multiple portals
Design challenge beyond UI: translating complex technical systems (algorithms, data permissions, blockchain contracts) into interfaces that everyday citizens can understand and trust.
Research insights: where trust breaks
From citizen interviews, we identified consistent patterns:
- Users didn’t know where to start
- They feared making mistakes
- They didn’t understand decisions
- They felt powerless in the system
Strategic reframing
We made two foundational design decisions:
1. One unified, citizen-first portal. Organized around life situations (e.g. safety, housing, income support), not departments.
2. Explainable and auditable decisions. Eligibility logic, data usage, and access rights are visible to citizens.
This aligned citizen needs with institutional responsibility.
Designing trust into the system, beyond UI
We explored blockchain conceptually as an infrastructure layer to support:
- Verifiable eligibility logic
- Traceable data access
- Immutable decision records
- Clear accountability
Blockchain was not presented as a feature, but as a trust mechanism operating behind the interface.
Designing under ambiguity
Constraints included:
- Evolving policy rules
- Limited access to real government data
- Legal and accessibility requirements
- Short academic timeline
Design approach:
- Clarify assumptions early
- Design for uncertainty
- Prioritize ethical responsibility over speed
- Focus on decision quality over completeness
Failure prevention and trade-offs
In GovTech, success is often measured by what does not go wrong. This design actively reduces the risk of:
- Wrong benefit applications
- Blind trust in opaque algorithms
- Untracked data access
- Premature over-automation
Simple system flow
- Citizen starts with a life situation (e.g. safety, housing, income support)
- System requests only essential data
- Eligibility rules are evaluated via smart contracts
- Each decision step is logged on the blockchain
- Citizen can see what data was used, why a decision was made, and who accessed their data
- Outcomes are either approved, require clarification, or are escalated to a human caseworker
Design solution
Rebuilding trust, transparency, and usability in a public digital services platform.
The solution reframed the platform from a transactional government portal into a trust-first digital service ecosystem, designed to reduce cognitive load, clarify complex processes, and give citizens explicit control over their data. The experience was structured around three critical moments: pre-engagement (landing), first-time use (Day 0), and repeat usage (Day N), supported by a transparent, end-to-end agreement flow.
Landing page (pre-sign-up). Strategic intent: trust, clarity, expectation setting. A trust-first landing experience that sets expectations upfront, explaining how the platform works, how it improves legacy systems, and how user data is protected, reinforced by social proof.
Dashboard, Day 0 (first-time user). Strategic intent: reduce uncertainty before action. A first-time dashboard that builds confidence by surfacing eligibility signals, data usage principles, and service readiness before users take action.
Dashboard, Day N (returning user). Strategic intent: operational clarity and ongoing trust. A personalized dashboard giving real-time visibility into application status, benefits, and data sharing, reinforcing trust through continuous transparency.
Create digital agreement, end-to-end flow. Strategic intent: simplify bureaucracy into a predictable digital process. A guided flow that converts complex government procedures into a clear, step-by-step digital journey, covering eligibility, data consent, review, and secure submission.
Outcome and validation
We stopped at concept and hi-fi prototype stage. To validate:
- Tested with the same citizens from initial interviews
- Presented at the MDD Feedback Feast, receiving input from visitors, faculty, and peers
- Measured whether the new flows solved real problems
Observations:
- Users easily understood where to start
- Felt more confident navigating eligibility scenarios
- Better understood decisions
- Reported higher trust in system and data usage
Results are qualitative. No quantitative metrics were measured.
Algorithm and ethics
Rather than optimizing fraud detection, the system was redesigned around explainability, minimal data usage and accountability. The focus remained on ethical technology, not automation for its own sake.
Key learnings
- Ethics must be designed in, not added later
- Transparency builds trust faster than automation
- Good UX reduces systemic risk, not just friction
- Decision quality outweighs speed or pixel perfection