Educational companion dossier · Fact, interpretation, lived experience, clinical education, fiction, and mechanics are labeled separately. Scope & safety
PsychologicalWar.orgPeople before labels.
REAL-WORLD INTERPRETIVE

SIMULATION LITERACY

Scenarios Are Not Forecasts

A practical distinction among exploratory scenarios, probabilistic forecasts, observations, and policy decisions.

Read the working brief Choose a learning path
LEVEL 1

ORIENTATION

Why this matters

REAL-WORLD INTERPRETIVE

One-sentence brief

Confusing these categories can turn a useful thought experiment into false certainty or make a vivid counterfactual look like an official warning.

REAL-WORLD INTERPRETIVE

Three key points

  1. Scenarios are conditional: “if these assumptions hold.”
  2. Forecasts require calibration, probability, horizon, and later evaluation.
  3. Observed facts and policy choices must remain traceable outside the model narrative.
LEVEL 2

WORKING BRIEF

Evidence, context, and limits

REAL-WORLD INTERPRETIVE

Scenario

A scenario is a structured counterfactual. It explores what may follow if stated conditions, relationships, and interventions are assumed. It can expose dependencies and failure modes without claiming that the branch will occur.

  • State the assumptions in the same view as the result.
  • Label branch identity and divergence point.
  • Do not assign probability unless a forecasting method supports it.
REAL-WORLD INTERPRETIVE

Forecast

A forecast estimates what is expected within a defined horizon. It should specify a target, base rate, probability or interval, model version, issue time, and evaluation rule.

  • Evaluate forecasts against later outcomes.
  • Publish calibration and error, not only successful examples.
  • Separate probability from confidence in the evidence.
REAL-WORLD INTERPRETIVE

Observation

An observation is a measurement or source report. It can be incomplete, delayed, biased, or erroneous, but it should not be rewritten merely because a model expected something else.

  • Retain raw-source lineage.
  • Mark revisions and late reports.
  • Do not backfill observations from simulated states.
REAL-WORLD INTERPRETIVE

Decision

A decision is an accountable choice made under evidence, law, values, resources, and risk. A model may inform the decision but should not conceal who chose, which alternatives were considered, or which harms were accepted.

  • Name decision authority and date.
  • Record dissent and rejected alternatives.
  • Allow review and correction.
REAL-WORLD INTERPRETIVE

A simple communication test

Before publication, ask whether a reader could identify what was measured, what was assumed, what was simulated, what was forecast, and what was decided. If those states blur, the presentation needs revision.

  • Use explicit labels.
  • Avoid future-tense certainty for scenarios.
  • Keep explanatory narrative subordinate to state labels.
REAL-WORLD INTERPRETIVE

Correction and supersession

A scenario may remain historically useful after its assumptions change, while a forecast should be scored and a factual record should be corrected. Supersession should preserve the earlier state without presenting it as current.

  • Do not erase failed forecasts.
  • Link corrected data to derivative outputs.
  • Keep archived branches visibly non-current.
LEVEL 3

COMPLETE DOSSIER

Limitations, game links, and review context

DISPUTED / MULTIPLE ACCOUNTS

Known limitations and gaps

  • This is a non-operational educational transformation: it does not build or implement a game, executable simulator, forecasting service, emergency tool, or decision system.
  • This page is an educational transformation of supplied research leads; it does not authenticate every citation, equation, product claim, or institutional attribution in those files.
  • A scenario, model run, or map is not an observation, forecast, legal finding, public-health instruction, emergency warning, or proof of future behavior.
  • No source code, nuclear-effects formula, casualty calculation, target-selection method, cyber-intrusion procedure, exploit chain, or instruction for bypassing safeguards is published.
  • Geography, nationality, ethnicity, religion, language, migration, disability, health, poverty, or political identity are not inherent danger, compliance, intelligence, competence, or worth variables.
  • Specialist scientific, public-health, accessibility, legal, regional, ethics, security, and lived-experience review remains pending; the page stays open to correction.
LEVEL 4

RESEARCH EDITION

Sources, methods, and stable links

REAL-WORLD INTERPRETIVE

Linked reports

  • Building Epidemiological ModelsProtected research reference; no public report route in this release.
  • AI Takeover Simulation MapProtected research reference; no public report route in this release.
  • IARPA SimEarth Game Architecture part 2Protected research reference; no public report route in this release.
REAL-WORLD VERIFIED

Method and corrections

This page follows the public method for provenance, confidence, source independence, alternative accounts, limitations, review state, and visible correction.

Read the methodView corrections
NEXT

CONTINUE

Related learning

Simulation LiteracyAccessibility, Performance, and Low-Bandwidth ReviewA standard for making complex maps and simulations inspectable without high-end hardware, constant broadband, motion-heavy 3D, color-only encoding, or inaccessible controls.Simulation LiteracyAgent-Based, Compartmental, Cellular, and Network ModelsA comparative guide to four common model families and the kinds of heterogeneity, interaction, and uncertainty each preserves.Simulation LiteracyCalibration, Validation, and SensitivityHow to tune a model, test it against evidence, and reveal which assumptions drive its conclusions.Simulation LiteracyCompetitive AI Spread as a Fictional ScenarioA non-operational way to use a helpful-versus-harmful AI scenario to examine network assumptions, patching, uncertainty, governance, and recovery. Learning pathSimulation Literacy FoundationsLearn to distinguish scenarios from forecasts, select model families, inspect scale, validate assumptions, trace provenance, and read maps without false precision.