Risk Has Changed. Our Thinking Hasn’t.
We’ve built a world that trusts the output. more than the reasoning behind it. Models have become modern oracles.
Convenient. Scalable. Fast.
But with each delegation of judgment, we lose a bit of it.
How We Got Here
Wildfires now cause tens of billions in losses each year. Traditional catastrophe models built for yesterday’s world, can’t keep up. They assume fire seasons. They assume fire zones. But fire no longer asks permission. Ember spread, urban sprawl, human triggers, the new wildfire frontier is probabilistic, not historical.
And so, reinsurers now turn to smarter algorithms: AI-powered risk engines, real-time vegetation stress maps, human ignition predictors. These are more advanced, yes. But the philosophy hasn’t changed. It’s still: trust the model.
Are We Smarter, or Just Outsourcing Thought?
We reward the measurable over the meaningful. Teachers optimize for test scores, not curiosity. Auditors work through lunch, performing their productivity. Risk managers feed algorithms and assume clarity will follow.
But what if the fire jumps the map again?
What if the climate shifts faster than the update cycle?
What if the model gets it almost right just enough to convince us, but not enough to save us?
My Final Thought
We aren’t just relying on models, we’re living by them. But the more we let them decide, the less we seem to ask: what are we not seeing?
If risk is now real-time, fluid, and volatile, then any model however smart is just a guess dressed in code. And in that world, the real danger isn’t fire or flood. It’s believing that the algorithm knows best.
