Data governance is the process of managing the availability, usability, integrity, and security of data in an organization. It is essential for ensuring that data is used ethically, responsibly, and in compliance with regulations and standards. Data governance also enables the development and deployment of AI systems that are aligned with the values, goals, and expectations of the stakeholders and the society. In this keynote, we will discuss how data governance can serve as a keystone for building ethical AI and digital trust. We will explore the challenges and opportunities of data governance in the context of AI, and present some best practices and frameworks for implementing data governance in AI projects. We will also share some examples and case studies of how data governance can help achieve ethical AI and digital trust outcomes. The keynote will conclude with some recommendations and future directions for data governance in the AI era.
By the end of this session, you will be able to:
- Define data governance and its importance for data and AI systems
- Identify the challenges and opportunities of data governance in the context of AI
- How to apply best practices and frameworks for data governance, such as data lifecycle management, data stewardship, data ethics principles, and data audit and assessment
- Explain how data governance can support ethical AI and digital trust outcomes, such as fairness, privacy, explainability, and reliability
- Recognize the roles and responsibilities of various actors and stakeholders in the AI ecosystem for data governance.