This session is for individuals or businesses who want to use AI but are concerned about regulations and their industry's specific requirements.

This session explores why explainability and transparency are essential for applying AI and deep learning in regulated industries. With practical examples of how to explain complex and traditionally labelled "black-box" models

The session will cover:

• Why some models are seen as a black box and how they differ from traditional models.
• The importance of being able to explain how models and tools produced their output and being transparent with decision making.
• Demonstrate tools and techniques to utilise XAI (explainable AI), and how they can be utilised to boost adoption and benefit a business without sacrificing the benefits of complex models.

Attendees will discover practical tools and techniques to make models interpretable, understand the risks of black-box approaches, and learn how transparency drives compliance, trust, and confident adoption.