Steering Clear of Utopia and Dystopia: How to Build Plausible Binary Scenarios
Two scenarios can be enough for a foresight process. The difficulty is stopping one of them from becoming the good one and the other becoming dark.
AI-generated image through Midjourney
Most futurists often work with 4 scenarios divided into a 2x2 scenario matrix. But a question I often get is: Does it makes sense to work with just two scenarios?
Short answer: It does, sometimes. A binary scenario set, sometimes called a polarity, is a pair of distinct and internally consistent futures built around opposite outcomes of a single critical uncertainty. It suits a bounded question rather than a whole operating environment: the future of data sharing (Will we see increased collection and aggregation of data or will we see an increased focus on privacy and selectiveness?), the adoption path of a particular technology, whether a regulatory regime tightens or loosens, and for many other things.
The difficulty with two is that a pair invites a verdict. Where four futures sit in a field, two sit on a scale, and a scale has a better end. Left unchecked, a binary set drifts into a utopia and a dystopia, one world where things work out and one where they fall apart.
Utopias and dystopias might be useful for storytelling, but they are poor guides for strategic planning.
When two scenarios are the right tool
Two works when a single uncertainty clearly dominates the question, and when the decision on the table turns on how that one thing resolves. A pair is also easier to carry through an organisation than a quartet: two futures fit on one page and survive a management meeting without a facilitator in the room.
Four works when you are exploring a whole operating environment, where several uncertainties interact and the combinations matter as much as the individual outcomes.
The failure mode of choosing two is picking a binary because it is quicker, when the question actually had three or four moving parts. If you find yourself smuggling a second uncertainty into the scenario descriptions to make them feel different enough, you needed a matrix.
Why the trap is so easy to fall into
The relationship between utopia and dystopia is dialectic rather than oppositional. They are two readings of the same conditions. Every utopia is somebody's dystopia, and the pursuit of a perfected world tends to produce the conditions for its opposite, because the control required to sustain the ideal becomes the thing that spoils it. Treating them as endpoints on a line misses this entirely.
The practical consequence shows up in the room. When a set is arranged as good and bad, the good scenario collects the strategy work, because planning for it is more pleasant. The bad scenario turns into a risk register rather than a future anyone inhabits. And the question that justified the exercise, what we would do differently in each world, never gets asked, because everyone has already voted.
Anchor the pair on a mechanism
A critical uncertainty is an issue that is both highly uncertain over your horizon and highly consequential for the decision in front of you. Building a binary set around one is the standard fix, but it only works if the uncertainty is phrased carefully.
The test: the uncertainty should be about how the world works, rather than about whether things turn out well. "Will technology adoption accelerate, or proceed cautiously?" is a question about mechanism, and either answer produces a liveable world with costs attached. "Will technology save us or fail us?" is a question about outcome, and it has answered itself before you start writing.
Then add two or three secondary change dynamics that run across both futures, so neither scenario is one variable turned up and down. Demographics, capital costs and geopolitical alignment will look different in each world without being the thing that separates them.
A worked example: two futures for urban development
In a scenario project with a client in urban development from my time at the Copenhagen Institute for Futures Studies, I built a pair around the speed and shape of technology adoption in the city. The two futures were called Full Steam Ahead and Treading Carefully.
Full Steam Ahead. Residents trade privacy for convenience. Standardised protocols across public and private actors mean that access to the right platforms decides who gets to participate, which favours large incumbents and pushes smaller local suppliers to the margins. Mobility runs on fleets of electric, semi-autonomous vehicles. New and retrofitted buildings carry sensor networks monitoring air quality, heating and lighting, and energy performance improves sharply. So does the concentration of control: a small number of platform operators hold the data the city runs on, and the city's room to change supplier, or direction, narrows year by year.
Treading Carefully. Concerns about data privacy and security have reduced the reach of the large technology firms and slowed the adoption of integrated services. Residents hold real control over their own data, and public trust in city institutions is high, because the city has visibly declined to trade it away. The cost is friction. Limited data sharing makes aggregation difficult, so most of the efficiency gains available in the other world never arrive. Mobility stays fragmented across poorly integrated modes. Automation lands in heavy industry rather than services, which keeps service employment intact and productivity flat. Contests over who controls the digital infrastructure run on, arbitrated by the city government.
Each world holds something the other lacks, and each pays for it. That is the sign the pair is working.
Four tests before the pair leaves the room
The preference test. Ask the group which future they would rather live in. A split is a good result. Unanimity means you have built a preference rather than an uncertainty.
The symmetry test. Each scenario should name its own winners and its own losers. If one description lists benefits and the other lists problems, the verdict is already written into the text.
The language test. Read both descriptions and mark the loaded words. The tell is usually in the verbs. Things are "left", "poorly integrated" and "hard to" in one scenario, while they are "seamless" and "enabled" in the other. Names matter here too. Full Steam Ahead and Treading Carefully are two ways of driving, whereas Digital Dark Age settles the argument super fast and inconclusively.
The advocate test. Give each scenario a defender whose job is to argue that theirs is the better world to live in. If one defender has nothing to work with, rewrite the scenario rather than the brief.
What the last three years suggest
Since that project three years ago, we can look back at a pair like this and see how it held up. Reality tends not to select a scenario. It samples from both, at different speeds in different domains.
European technology regulation shows the pattern clearly. The EU adopted the AI Act, a decisive move in the Treading Carefully direction, and then, under a competitiveness push, adopted an omnibus in June 2026 that postponed the high-risk system obligations to December 2027 and August 2028. Caution arrived, and then part of it was deferred.
A pair built as good and bad handles this badly, because the only available question is which scenario won. A pair built as two mechanisms handles it well, because the useful question is which elements of each world are showing up, where, and how quickly.
This is the argument for leaving a scenario project with indicators. When you finish a binary set, write down the handful of observable developments that would tell you which way the balance is tipping, and look at them once a year.
Three things to take away
Two scenarios work when one critical uncertainty dominates the question. Four work when several uncertainties interact and their combinations matter.
Build the pair around a mechanism rather than an outcome. An uncertainty phrased as a verdict has already been decided.
Give each scenario its own winners and losers, and judge the set on what is plausible, not what is preferable.
Frequently asked questions
What is a binary scenario? A pair of distinct, internally consistent futures built around the opposite outcomes of a single critical uncertainty. Also called a polarity. Binary sets are used to explore a bounded question rather than a whole operating environment.
Are two scenarios enough? Yes, when one uncertainty dominates the decision. Two scenarios are easier to communicate and easier to use than four. When several uncertainties interact and their combinations matter, a 2x2 matrix producing four scenarios is the better choice.
What is a critical uncertainty? An issue that is both highly uncertain over your time horizon and highly consequential for the decision at hand. Critical uncertainties are the axes that scenario sets are built on, as distinct from predetermined elements, which are largely settled over the same horizon.
How can you tell if a scenario has become utopian? It lists benefits without naming who pays for them. A useful check is whether the scenario contains a group that is worse off in it. If every stakeholder gains, you are describing a preference rather than a future.
What is wrong with best case and worst case scenarios? They answer the question before the analysis starts. Best and worst are judgements about outcomes, so the set tests optimism against pessimism rather than testing a strategy against different ways the world could work. Planning attention also drifts towards the pleasant scenario, which is the opposite of what scenario work is for.
How many change dynamics should a binary scenario contain? One critical uncertainty separating the two futures, plus two or three secondary dynamics running across both. That keeps each scenario from reading as a single variable turned up and down.
Originally published on Medium in 2023, then revisited and substantially revised in September 2026.
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