# correlation vs causation

Public confidence hinges on how findings are framed, separated from correlations, and backed by transparent methods. New threads connected large-scale health cohorts, environmental signals, and interpretable AI, underscoring that better interpretation can improve decisions across policy, healthcare, and climate risk.

A slate of high-profile studies is prompting sharper scrutiny of what data actually proves and how predictions will be used. A new model forecasting 10-year risks across more than 1,000 conditions stoked concerns about insurance and employment discrimination, while efforts to monetize harms and frame norms debates underscored how evidence shapes policy and power.