This concept is not only mine to share; the minister of the digital affairs of Taiwan, Audrey Tang, explained with some major wins in his announcement.
Modernising democratic roles
Modernising democracy also means modernising our roles within it. A healthier system depends on shared participation, not hierarchy
- Citizens — Stay curious, seek holistic truth, and engage respectfully with the community. Understanding comes before opinion.
- Representatives & Experts — Study issues deeply, gather reliable evidence, and communicate clearly. Their role is to guide, not rule.
- Journalists & Communicators — Go beyond reporting outcomes. Explain processes, challenge assumptions, and make complex information accessible and accurate.
- Moderators & Facilitators — Ensure discussions remain constructive, inclusive, and fact-based. Conversations need care, not control
Getting inspired by existing tools
This proposal isn’t built from scratch; it stands on the shoulders of platforms already pushing civic understanding forward. Across the world, tools from deliberation to fact-checking show how technology can reduce bias, reveal context, and support healthier public dialogue. Below are the key inspirations:
Platform Features
Civilian Contributions
This is the heart of the platform — the civilian contributions, or what we usually call posts. Every user can contribute something meaningful: an idea, a problem, an opinion, a question, or even an opportunity for improvement. Contributions can be connected to existing topics or open entirely new ones.
But here, it’s not just what you say that matters — it’s how you say it.
The platform’s goal is to guide users toward expressing ideas in a fair, respectful, and inclusive way, helping people frame their thoughts with clarity and empathy. The tone should promote understanding, not hostility.
When creating a post, the system gently assists the user in identifying who might be affected — both positively and negatively — and what risks or consequences the idea might carry. This helps transform a simple complaint or reaction into a civic contribution — a statement grounded in awareness and responsibility.
Example:
- Initial Post:
“It was about time for an accident. Our roads suck!” - Guided Contribution:
“After the accident last week on James Bond Street, I’ve noticed how poor visibility is around that area. I completely understand the need to illuminate archaeological monuments beautifully, but perhaps we can adjust the lighting design to make the road safer for drivers and pedestrians.”
Engaging With Contributions
Once a post is shared, the conversation truly begins. Engagement on this platform isn’t about collecting likes — it’s about building knowledge together. Users can interact with a post by adding further research, supporting documents, related ideas, or personal experiences that enrich the discussion. Reactions are not noise; they are part of the learning process. Every contribution adds a layer of understanding to the original idea.
As discussions grow, the system detects when a post gains meaningful traction — not through volume, but through depth, balance, and constructive participation.
For example, imagine the earlier post about the James Bond Street accident. As others contribute — a local architect sharing a visibility report, a cyclist uploading a nighttime video, a city planner linking to safety regulations — the post evolves into a valuable public thread. The system may then elevate it to the top of the #Transportation section, where local authorities, journalists, or experts can see it easily.
Contributing to engagements becomes a path to collaboration, connecting citizens, experts, and decision-makers around the same living issue.
Feedback, Evaluation, and Reporting Layer
Every contribution can be evaluated by the community through a structured feedback model. Instead of quick reactions, users can mark a post as helpful, insightful, unclear, or biased. They can also add short notes explaining why — offering specific, respectful observations rather than emotional responses.
Take the example of the James Bond Street accident post. As the discussion grows, others might respond like this:
- “Helpful — this identifies a recurring safety issue and offers context.”
- “Unclear — it’s not clear who manages street lighting in that zone; can you clarify?”
- “Insightful — linking the lighting to archaeological site preservation adds an interesting angle.”
This structured feedback system evaluates quality, not popularity. Thoughtful, diverse responses elevate a post; unclear ones prompt clarification or community notes. Citizens can flag misinformation or harm, triggering contextual reviews rather than punishment. Over time, this two-way process teaches users to communicate better and helps the platform highlight substance over outrage.
Enhanced Community Notes
Community Notes has proven that context builds trust. When users add explanations instead of blunt “misleading” labels, people are more likely to believe the correction and share less misinformation. A study published by Oxford University Press found that contextual notes were significantly more trusted than standard misinformation flags.
A University of California, San Diego analysis confirmed that Community Notes were highly accurate and credible, especially for vaccine-related posts. Similarly, research on arXiv reported that when a note is attached to a misleading post, engagement drops sharply — reposts by ~45% and likes by ~43%.
Still, the model struggles with speed, diversity, and visibility.
Many viral posts never receive notes in time, and a small group of contributors writes the majority. This pattern was noted in a large-scale data transparency report and in follow-up analyses on Wikipedia.
Because the platform isn’t optimised for speed or emotional reactions, each post is first shared with a segment of users who have expertise in that topic. This allows knowledgeable contributors to add early context and Community Notes. If the post begins gaining traction, a community review mode activates, inviting a wider and more diverse group of users to contribute additional context before the content spreads further.
All notes appear directly within the post, with the system’s LLM providing clear, neutral summaries.
Algorithm for Understanding
Most digital platforms today are built around one metric — engagement. Their algorithms are designed to maximise emotion, outrage, and addictive scrolling, because the longer we stay online, the more ads we see, and the more profitable the system becomes.
Our platform must take the opposite path. Instead of optimising for emotion, it optimises for understanding. Instead of amplifying what divides, it surfaces what connects.
The algorithm’s purpose is to guide comprehension. It promotes content that helps people see the full picture, not just the side that fits their bias.
Algorithm key principles:
1. Relevance First
Content is served to the people who can meaningfully enrich it: citizens directly affected, experts with relevant insight, and communities equipped to help. This creates deeper engagement, allowing posts to gather context, sources, impacts, and risks — rather than shallow reactions or fragments.
2. Exposure to Multiple Viewpoints
The system deliberately broadens perspectives. It resurfaces skipped materials, introduces contrasting views, and reduces the blind spots that create echo chambers.
3. Promote Thoughtful contributions
Thoughtful contributions are highlighted above heated or repetitive ones, shifting the culture from reaction to reflection. This slows the rush toward instant opinions and encourages users to pause, explore context, and consider alternative viewpoints before responding.
Join Discussion Rooms
When a topic gains traction and enough information is gathered, it can evolve into a virtual discussion room — an open dialogue space where citizens, experts, and representatives come together to exchange ideas in real time.
Because these discussions are hosted within the platform, all previously gathered data helps structure the meeting through dedicated moderator tools. Insights generated during the session are then fed back into the platform, enriching the topic’s knowledge base and improving the ongoing civic process.
Each session is moderated by a certified facilitator from the platform’s community, whose role is to ensure inclusivity, respect, and focus. After the discussion ends, participants can rate the moderator’s fairness and clarity, creating a transparent feedback loop that strengthens future sessions.
Open Source and Transparency
At the foundation of this platform lies a commitment to transparency. Every major component — from the algorithm that ranks posts to the data that informs decisions — should be open source and publicly auditable. People must be able to see how information moves, how visibility is determined, and how their contributions are valued.
By keeping the code, funding sources, and moderation logic open, the platform earns trust through visibility, not promises. Just as citizens can participate in discussions, they can also participate in improving the system itself — submitting code, suggesting fixes, or analysing biases in real time.
Openness makes corruption harder and collaboration easier. It turns the system into a public good, owned and shaped by the very people it serves.
And importantly, as highlighted by the Association Redefine, open source creates long-term resilience. Even if a project shuts down, communities can continue developing and maintaining the tools because the code belongs to everyone. Investments don’t vanish — they evolve into a living civic ecosystem that outlives any single platform
Visualising Data for Clarity
A civic platform can generate thousands of posts, threads, and interactions. To make this complexity understandable, we need simple, smart visualisations that reveal the shape of the conversation at a glance. These visuals help each person see where they stand, how the community thinks, and how decisions evolve.
We focus on five key visual tools:
- Profile Map —helps you understand how you participate in the civic space.
- Press Landscape — compares how different media sources frame the same issue.
- Community Landscape — clusters related discussions to reveal priorities and tensions.
- Debate Pathways — maps the flow of arguments from context to risks.
- Voting Impact Map — shows how different votes influence outcomes and each other.
Profile Map
Inspired by the philosophy behind Readocracy, it doesn’t measure popularity; it measures depth, diversity, and quality of your engagement.
Your Profile Map reflects things like:
- the topics you explore
- the perspectives you’ve engaged with
- the clarity and helpfulness of your contributions
- your willingness to consider alternative views
Over time, the Profile Map becomes a visual record of your learning journey — showing how your understanding evolves and where your strengths or blind spots may lie