How poisoned data can trick AI − and how to stop it
Hadi Amini and Ervin Moore discuss how the quality of the information that the AI offers depends on the quality of the data it learns from. But if someone tries to interfere by tampering with their training data – either the initial data used to build the system or data the system collects as it’s operating to improve – trouble could ensue.
