One of the biggest risks to any AI tool is data integrity. Cybersecurity is built on the CIA triad of confidentiality, ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Trust is fragile, and that's one problem with artificial intelligence, which is only as good as the data behind it. Data integrity concerns -- which have vexed even the savviest organizations for ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.