FiaLign: turning political argument into shared inquiry for voters

Democracy is under measurable global pressure. The share of the world’s population living in liberal democracies has fallen to levels last seen in the 1980s, while authoritarian rule expands — and across twelve high-income democracies, a median of 64% now say they’re dissatisfied with how democracy functions. Satisfaction keeps falling even though political information has never been more abundant.

Finland makes the problem precise. Trust in institutions and media is high, so distrust isn’t the obstacle. Yet young voters still struggle to relate political messaging to their own circumstances. When the conditions for interpretation break down inside a high-trust system, the failure is structural, not informational.

Aim: treat the political information landscape as a service system — and find where, for whom, and why meaning breaks.

Team: Ashwin Vasudevan — solo, supervised by Satu Miettinen and Kislay Yadav · Tools: NVivo, Figma, Miro, ChatGPT, Claude

The project followed the Stanford d.school Design Thinking process — Empathise, Define, Ideate, Prototype, Test — used not as a linear method but as a logic of inquiry for an ambiguous space where neither problem nor solution was fixed at the outset. The discipline was building a frame to observe one specific relationship: how the information available to a voter shapes the decision they reach.

Empathise

Nine long-form interviews surfaced how voters actually encounter, interpret, and act on political information — six voters aged 20–30, two journalists, and an elected municipal official.

Voters weren’t apathetic — they were reasoning from consequences they experience, and the information available couldn’t help them reliably connect policy to their own lives.

Define

Sensemaking theory was turned into an observational instrument: a voter sensemaking journey map that traced how information moves through creation, interpretation, and enactment — and where each voter’s frame holds or collapses. Findings were synthesised into a causal loop diagram to model the relationship between the information landscape and the decision itself.

Two loops emerged which influence the cognitive frame — one through emotion and identity, the other through context, technology, and language. The second was structurally produced, and therefore designable. That became the leverage point.

Ideate

A co-creation workshop with six participants surfaced what blocks dialogue across political silos, then generated service concepts. This confirmed the lack and the importance of a shared cognitive frame. A Theory of Change structure was chosen over causal loop diagrams precisely because it needed almost no methodological onboarding — letting energy go to content, not notation.

Shared, visible consequences — not better arguments — became the common ground worth designing around.

Prototype & Test

Five participants mapped a personal political issue and read a party manifesto re-presented through the framework’s cause-and-effect logic. The structure landed; the first presentation overwhelmed. Every friction point fed a redesign.

The framework was working but the visuals and layout were overwhelming. Plain-language layers, narrative prompts, and a linear canvas produced FiaLign 1.0.

FiaLign 1.0 is a facilitated participatory workshop built on a four-layer canvas — My Experience → What Influences It → Where It Happens → What Drives It — with Finland’s ministerial domains running down the outer edge. It externalises the reasoning voters usually do alone and incompletely, tracing any issue from lived impact back to the policy that shapes it, and making different perspectives comparable without forcing consensus.

FiaLign reframed a problem everyone else treats as a literacy or misinformation issue into a design problem — the interpretive conditions themselves — and then built a working intervention around it. That shift, from subjective argument to shared structural inquiry, is what the project demonstrates: the ability to take an ambiguous, politically charged brief and turn it into a diagnosis, a leverage point, and a testable tool.

Participants appreciated the framework’s ability to surface vagueness in party promises and expose knowledge gaps. A participant with ADHD and dyslexia found the table far easier to engage with than a PDF manifesto.

The takeaway that carries into any brief: the highest-leverage move isn’t adding more information to a system — it’s redesigning the conditions under which information becomes meaningful. That’s a way of working, not a one-off finding — applicable anywhere users struggle to make sense of a complex system, from public services to onboarding to data-heavy products.