Published

How should the platform handle policies that take decades to show measurable outcomes?

What role should community consensus play in validating that a real-world outcome actually occurred as reported?

How can the platform better support educators in framing “being wrong” as a learning opportunity?

What is the appropriate threshold for triggering a Divergence Event? Should small variances be treated differently than large ones?

How should the platform handle situations where real-world data is contested or politically charged?

Should students ever have the option to continue a simulation without accepting reality updates? Under what circumstances might this be educationally valuable?