AI Black Box Testing
AI Black Box Testing refers to the process of testing artificial intelligence systems where the internal workings or algorithms are not fully known or understood. This type of testing focuses on evaluating the system's outputs or behavior without needing knowledge of its internal logic. It involves feeding inputs into the AI system and analyzing the outputs to assess its accuracy, reliability, and performance. The goal of AI Black Box Testing is to identify any potential issues, biases, or errors in the AI system's decision-making process, without needing access to its underlying code or design.