AI Bias
AI bias refers to systematic errors in artificial intelligence systems that lead to unfair, inaccurate, or discriminatory outcomes.
AI Ethics
AI ethics is the set of principles and practices that guide the responsible design, development, and use of artificial intelligence systems.
AI Fairness
AI fairness is the principle of designing and using artificial intelligence systems in ways that minimize bias and ensure equitable treatment across different individuals and groups.
AI Safety
AI safety is the practice of designing, training, and using artificial intelligence systems in ways that minimize harm, reduce risk, and ensure reliable, ethical, and aligned outcomes.
Explainable AI (XAI)
Explainable AI (XAI) refers to methods and systems that make artificial intelligence decisions transparent, understandable, and interpretable by humans.
Hallucination (AI)
An AI hallucination occurs when an artificial intelligence system generates information that sounds confident but is incorrect, misleading, or entirely fabricated.
Human-in-the-Loop (HITL)
Human-in-the-Loop (HITL) is a system design approach where human input is intentionally integrated into automated or AI-driven processes to guide, validate, or improve outcomes.