Posts on what we actually think.
Essays on conformal prediction, social inflation, and where generative AI helps and where it doesn't. Written by the team.
Showing 16 posts · Science · David H. Silver
Clear filtersGeometric Machine Learning on Resolved Cases
Large language models are word guessers, not calculators. To predict the financial outcome of a lawsuit, you must separate the extraction of text from the mathematics of risk.
Measuring Calibration: Why We Publish Error Rates
A claim prediction is useless if you do not know how often the model is wrong. Publishing error rates forces a transition from guessing to actual risk management.
Neural-Symbolic Models for Legal Outcome Prediction
Generative AI is a text engine, not a crystal ball. To forecast litigation outcomes accurately, you must fundamentally separate the act of reading a claim file from the mathematics of predicting its cost.
Generation Is Not Prediction
Large language models are built to produce plausible text, not accurate forecasts. Confusing a statistical parrot for a mathematical pricing engine is a fast way to misprice your entire claims portfolio.
Want to talk to an executive?
Press, partners, investors, candidates — the inbox is monitored. Tell us who you are and we'll route it to the right person within two business days.