How do you help people move beyond personal self-interest and think about the collective good before a major public consultation?
That was the challenge behind our recent collaboration with the Centre for European Policy Studies (CEPS), a Brussels-based independent think tank and forum for debate on EU affairs. CEPS conducts policy research across a wide range of European issues, from institutions and policymaking to migration, climate, digital innovation, trade, and human rights.
Together, we explored how serious game design could prepare people for more thoughtful democratic participation. The result was a digital, multiplayer simulation designed to help participants experience the trade-offs, constraints, and competing needs that shape real public policy.
Rather than asking players simply to argue for their own preferences, the game asks them to practise procedural empathy: understanding how a decision feels from another person's position, and how fairness depends on the structure of the process as much as on the outcome.
The Architecture of the Policy Game
The game is a collaborative, web-based simulation played in small groups. It turns public policy from an abstract debate into a structured experience where participants must make collective decisions under time pressure, uncertainty, and limited resources.
The gameplay unfolds across three phases:
| Phase | Name | Core activity |
|---|---|---|
| Phase 1 | The Constitutional Round | Players collectively determine the rules of governance before knowing their roles, operating behind a digital "veil of ignorance." |
| Phase 2 | The Implementation Round | Players take part in a live, 10-minute structured deliberation, advocating for assigned policy positions under strict time and resource limits. |
| Phase 3 | The Reflection Round | The group reviews its performance, reflecting on how fair the process felt and where trade-offs succeeded or failed. |
Key Mechanics: Operators, Advocates, and Tolerance Overlap
To mirror the tensions of public administration, players are randomly assigned one of two primary roles.
The Operator acts as the decision-maker. Their task is to listen to competing arguments under time pressure and allocate a limited budget across several policy dimensions.
The Policy Advocates act as constituents. Each receives a specific persona and policy card, outlining the needs, constraints, and priorities they must represent during the discussion.
This role structure matters because it prevents the game from becoming a generic debate. Players must work within assigned perspectives, sometimes advocating for needs that are different from their own. That shift is central to the learning experience.
Building Structural Empathy
The game also introduces deliberate inequality. Some policy cards include severe restrictions on speaking time, such as only 60 seconds across a 10-minute round.
This mechanic simulates the systemic marginalisation often experienced by vulnerable or underrepresented groups. For example, a persona might represent a single parent facing documentation barriers, transport constraints, or digital exclusion. The player must still influence the decision, but with less access, less time, and fewer opportunities to be heard.
The purpose is not to make the game harder for its own sake. It is to make structural disadvantage visible. Players feel how process design can amplify or suppress different voices, and they learn that fair outcomes require more than good intentions.
The Policy Space Win Condition
Instead of creating simple winners and losers, the game hides a mathematical "sweet spot." Every persona card contains a hidden tolerance range: the minimum and maximum level of funding that persona can accept.
If players communicate clearly, they can discover the overlapping intersection of their collective tolerances. The Operator's final decision is then scored according to whether the budget configuration falls inside this shared policy space.
Persona A tolerance: [=======] Persona B tolerance: [=======] Persona C tolerance: [=======] Collective policy space: [===]
The target is not to defeat other players. It is to find a decision that is workable across the system.
Our Iterative Design Method
Our development process was anchored in the MDA framework: mechanics, dynamics, and aesthetics. In practice, this means designing technical rules that produce meaningful emotional and behavioural outcomes.
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Literature and evidence review: We began with a review of behavioural science literature, focusing on digital interventions that can support empathy, perspective-taking, and better group decision-making.
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Flexible systemic design: We then designed the core game engine to be theme-agnostic. The mechanics can stay consistent while scenario content changes across policy areas, from housing investment to public health access. This makes the system flexible enough to support different consultation contexts while keeping the underlying learning experience coherent.
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Co-design and language refinement: Working with policy practitioners, we also refined the game's language. Dry or overly academic terms were replaced with concepts that players could understand quickly during live play. For example, technical scoring ideas became intuitive visual scorecards.
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Aesthetic skinning: Finally, we developed a more distinctive visual identity. The interface moved from a flat prototype into a stylised "Explorer" experience, using clean geometry and high contrast to make the game feel engaging without distracting from the collaborative task.
From Serious Gaming to Scalable Decisions
The simulation is a training ground for perspective-taking, but it is also closely connected to PSi's wider work in collective intelligence.
The mathematical modelling of tolerance overlap, the use of small-group deliberation, and the multi-round discussion structure build on the same principles behind the PSi platform. The same underlying architecture that keeps a five-player game balanced can also help guide large groups of citizens through complex public decisions.
In real consultations, PSi uses structured breakout discussions and collective intelligence methods to help public bodies gather richer, more usable input at scale. The serious game shows the same philosophy in a more concentrated form: give people a fair structure, help them understand each other's constraints, and turn complex dialogue into decisions that can be acted on.
Ready to Experience Collective Intelligence in Action?
Public consultation works best when people are prepared to listen, weigh trade-offs, and think beyond their own immediate interests. Serious games can help build that capacity before the consultation begins.
Book a demo of the PSi platform to see how we turn complex, large-scale community dialogue into structured, actionable public policy.