How do you implement a robust governance framework for data ethics and risk assessment in a large organization? Learn about the practical steps needed to foster a culture of responsibility, accountability, and effective evaluation, encompassing diverse risk dimensions associated with both discriminative & generative AI

·       Design scalable systems and processes for ethical risk assessment.

·       Foster cultural behaviour change, incentivizing ethical decision-making.

·       Implement accountability mechanisms for data scientists and department heads.

Not only is keeping up with global regulation a challenge, but actually deploying AI in line with regulation, quickly & without problem is another. This discussion will delve the practical steps an organization can take in deploying AI aligned the fast developing regulatory landscape, and then will go on to explore in detail what the real, practical, industry challenges are that come with this deployment against the backdrop of developing regulation and guidance. Join this session to:

·       Explore the best way to optimize AI deployment in line with regulation as an industry decision maker.

·       Understand as a policy maker, how the industry react & strategize regulation into practical deployment and the challenges that come with this.

·       Enhance collaboration & understanding between industry & policy makers to spearhead progress in this field.