Explainability
Also known as: XAI, Interpretability, Explainable AI
The degree to which the internal workings and decision-making processes of an AI system can be understood, interpreted, and explained to humans in meaningful terms.
Sources & References
Related Terms
AI Governance
The frameworks, policies, standards, and oversight mechanisms that guide the development, deployment, and use of AI systems within organizations and across society.
Attention Mechanism
A neural network component that allows models to selectively focus on the most relevant parts of their input, dynamically weighting the importance of different elements in a sequence.
Responsible AI
The practice of designing, developing, deploying, and using AI systems in ways that are ethical, transparent, fair, accountable, and aligned with human rights and societal values.