LEARNING PATH // EDUCATORS, PUBLIC COMMUNICATORS, SAFETY REVIEWERS, PUBLIC-HEALTH READERS, AND MODEL-GOVERNANCE TEAMS
Examine population dignity, hazard communication, outbreak-model interpretation, fictional AI propagation, deterministic authority, and accountable correction without operational enablement.
Estimated total: 125 minutes
A safety-first framework for discussing catastrophic hazards through uncertainty, preparedness, communication, and accountability rather than operational enablement.
/simulation-literacy/high-consequence-hazard-modelsA person-first standard for using population, mobility, health, infrastructure, and vulnerability data in consequential models.
/simulation-literacy/population-data-and-human-impact-ethicsHow agent-based and compartmental outbreak models can explain mechanisms without becoming medical advice, deterministic predictions, or simplistic policy proof.
/simulation-literacy/epidemiological-models-and-public-communicationA non-operational comparison between one-time spatial envelopes and processes that spread through time, networks, or neighboring cells.
/simulation-literacy/radial-impact-and-propagation-modelsA non-operational way to use a helpful-versus-harmful AI scenario to examine network assumptions, patching, uncertainty, governance, and recovery.
/simulation-literacy/competitive-ai-spread-as-fictional-scenarioA governance pattern in which validated state, rules, and evidence remain authoritative while generative systems provide clearly labeled explanation or narrative proposals.
/simulation-literacy/deterministic-core-generative-narrativeA rights-aware lifecycle for consequential models: ownership, purpose, source review, validation, publication, monitoring, challenge, correction, withdrawal, and archival history.
/international/simulation-literacy/governance-correction-and-public-accountability