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What is Explainable Artificial Intelligence?

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Explainable Artificial Intelligence focuses on developing AI systems that can provide understandable explanations for their decisions and behaviours. Transparent and interpretable AI models are essential for building trust, ensuring fairness, and addressing ethical concerns. Businesses can benefit from explainable AI by gaining insights into AI-driven predictions and making informed decisions based on those insights.

Other Definitions

Computer Vision

Computer vision is a field of AI that focuses on training machines to understand and interpret images and videos. By analysing visual data, machines…

Uncertainty in Artificial Intelligence

Uncertainty in AI refers to the unpredictability or lack of full knowledge about a situation or outcome. AI models often encounter uncertainties due to…

Federated Learning

Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…

Zero-Shot Learning

Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved…
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