Red teaming is a structured adversarial testing process used to identify weaknesses, unsafe behavior, or harmful outputs in an AI system. It involves deliberately probing the system with challenging, malicious, or edge-case inputs so developers can evaluate and improve safeguards.
Red-teaming means a structured testing effort to find flaws and vulnerabilities in an AI system, often in a controlled environment and in collaboration with developers of AI. AI red-teaming is most often performed by dedicated 'red-teams' that adopt adversarial methods to identify flaws and vulnerabilities, such as harmful or discriminatory outputs from an AI system, unforeseen or undesirable system behaviors, limitations or potential risks associated with the misuse of the system.