• Practical examples for what to consider in building a model for AI ethics and governance
• The ethical, legal, social, and technical challenges with AI
• Present regulators’ and global standards bodies perspectives on the topic and showcase state-of-the art technical approaches to integrating ethical considerations for AI roll out

• Expand the focus of regulation of AI use from processes to outcome(s)
• How can AI support people to manage their finances?
• Relationship between automation of financial decision-making and economic empowerment
  • Who is responsible for the mistakes AI make in finance and how can they be held to account?
  • How will people be able to know that automated actions are being taken in their best interests?

• How can AI integrate greater social motivations into financial decision-making?
• How can AI build trust and guarantee that the information shared is reliable?
• Ethical AI to maintain improve customer service and experience

• Best practise and principles used in the development and roll-out of AI products and solutions
• Digital rights, privacy, security and data management; bias and fairness; transparency; market efficiency and financial stability
• Driving down exclusion and discrimination – with ethical AI

• How can we narrow the knowledge gap between AI “experts” and the variety of people who use, interact with, and are impacted by these technologies?
• How do we harness the potential of AI systems while ensuring that they do not exacerbate existing inequalities and biases, or even create new ones?