The ability to understand and explain how an AI model reaches its decisions. Explainable AI is crucial for building trust, meeting regulatory requirements, and debugging model behavior.
The framework of policies, processes, and controls that ensure AI systems are developed and used responsibly. AI governance covers ethics, bias, privacy, security, and regulatory compliance.
Systematic errors in AI systems that create unfair outcomes for certain groups. Bias can originate from training data, algorithm design, or deployment context. Identifying and mitigating bias is critical for responsible AI.
AI概念があなたの課題にどのように適用されるかを話し合う相談を予約してください。