Responsible AI: Building trustworthy solutions

In the era of new AI advancements every week (it feels like!), ensuring that the implementation of these into your solutions is responsible and ethical is more important than ever. In this session we explore the concept of Responsible AI and discuss the key areas of ethical implications - fairness, transparency, accountability and privacy. From data collection and model training to deployment and ongoing monitoring, we cover the considerations needed to foster a responsible AI culture and embedding ethical principles throughout the AI lifecycle. Gain an understanding of the importance of diverse and inclusive datasets, explainable AI techniques, and ongoing model evaluation - all things that can not only mitigate risks but also increase customer trust and long-term sustainability.