The software started as a way to evaluate the reliability of systems that look for anomalies in aircraft components and respond to them in flight. Today it is predicting how autonomous drones will behave and how drugs will move through the body, and its creators see no reason why it couldn’t be applied to any complex system: the stock market, the spread of an illness through a population, or the actuarial science of insurance pricing.
It’s software that predicts the future, or at least the probabilities of various outcomes. And it started at NASA’s Langley Research Center.
Called the Algorithms for Uncertainty Representation and Analysis (AURA) program, the software is based on polynomial chaos theory, a branch of mathematics so complex that it wasn’t much used until computing capabilities caught up to it in the 1990s.
By the mid-2000s, there was a lot of interest in developing advanced, intelligent, automated diagnostic and control systems that could detect and respond to aircraft damage and failures and thereby increase aircraft safety and autonomy. But no transition to new flight-safety algorithms is taken lightly.