Currently, AI engineers evaluate fairness with a single leaderboard number, but research from Princeton Engineering shows that reducing fairness to a single metric could lead to societal harm.
A growing body of evidence has revealed deep flaws in how machine learning is used in science, a problem that has swept through dozens of fields and implicated thousands of erroneous papers.
Princeton researchers have created an artificial intelligence tool to predict the behavior of crystalline materials, a key step in advancing technologies like batteries and semiconductors.