AI GLOSSARY
Explainable AI (XAI)
Explainable AI (XAI) refers to methods and techniques that make the decision-making processes of AI systems transparent and understandable to humans. Unlike black box models, explainable AI provides insights into how an AI model reaches its conclusions, allowing users to interpret, trust, and verify the outputs. This is particularly important in high-stakes applications like healthcare, finance, and autonomous systems, where understanding the rationale behind AI decisions is critical.
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Machine Learning Types and Their Infrastructure Use Cases
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AI and Machine learning is a complex field with numerous models and varied techniques. Understanding these different types and the problems that each...
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The Business of AI in UK Defence and National Security
by Al Bowman
While the technical aspects of an AI system are important in Defence and National Security, understanding and addressing AI business considerations...
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