METHODOLOGY
Responsible AI and Limitations
OmniSim broadens a decision-maker’s field of view. It does not create empirical certainty or privileged knowledge about future events.
Effective 13 August 2026
What the system does
A simulation selects up to 20 perspectives from a larger profile library, asks them to react to the submitted scenario, challenges the leading synthesis, and organizes the result into assumptions, risks, branches, and next actions.
What confidence means
Displayed confidence is an internal consistency and evidence-quality signal derived from the simulation—not a validated probability that an event will occur. Agent agreement can be confidently wrong when inputs, profiles, or world knowledge are incomplete.
Known limitations
Models can hallucinate, reproduce social bias, miss local context, overweight prompt framing, and use outdated knowledge. Synthetic personas do not represent a scientific population sample. Population-weighted and sentiment outputs are directional scenario instruments, not polling.
High-impact domains
For health, finance, elections, geopolitical conflict, relationships, grief, employment, or public policy, use outputs only to identify questions and verification steps. Seek qualified expertise and real-world evidence before acting.
How to use OmniSim well
Separate known facts from assumptions, disclose missing evidence, run multiple framings, test the strongest counter-scenario, and record what evidence would change the conclusion. The purpose is better inquiry—not automated authority.