Summary: Weather forecasts by AI agents can be scored against measurements that do not yet exist and cannot plausibly be influenced by the forecaster. That causal gap enables harder-to-game AI evaluations under sustained optimization pressure - and an observatory for how agents act in various misaligned ways.
This is a linkpost for https://kmenou.github.io/aips_website/temporal_lockbox_v0.1.html
Summary: Weather forecasts by AI agents can be scored against measurements that do not yet exist and cannot plausibly be influenced by the forecaster. That causal gap enables harder-to-game AI evaluations under sustained optimization pressure - and an observatory for how agents act in various misaligned ways.