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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AI-Powered Infrastructure Inspections for Local Authorities
Leanne McGregor:
Local authorities need to support their funding requests with high-quality data. The problem is that they can't obtain this data at the required...
5 min read
AI Assurance Explained: Trust, Safety, and Operational Impact
Alistair Garfoot:
The UK-USA Technology Prosperity Deal sees overseas organisations pledging £31 billion of investment into UK AI infrastructure. As AI investment...
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