Enable language models to express uncertainty in natural language

AI Impact Summary

This change indicates a capability to have language models articulate uncertainty directly in their outputs, likely through calibrated hedges and uncertainty cues in prompts or model instructions. For product teams, this enables more transparent risk communication but requires careful calibration to avoid confusing users or degrading usefulness. Engineering considerations include updating prompts, creating evaluation benchmarks for uncertainty quality, and integrating uncertainty signals into monitoring dashboards and decision workflows.