Tag: Testing for Harmful Content in Data

Verification of the presence of harmful, offensive, discriminatory, or unsafe content within datasets used to train or feed AI systems. Includes analysis techniques to identify bias, hate speech, unredacted sensitive information, illegal or ethically problematic content that could compromise the reliability and security of the AI model.