Data governance for the public good through local solutions to global challenges

The discussion will focus on several policy guiding questions from the ones listed below:

Fairness, Accountability & Ethics in AI and Data Governance

How can data governance frameworks promote fairness, accountability, and ethics in AI systems, particularly in reducing bias and ensuring responsible decision-making?
How do we establish clear lines of accountability within a data governance structure for decisions made or heavily influenced by AI systems, especially when errors or unintended consequences occur?
Are there frameworks that are good practical examples of data governance in AI systems and that deserve to be replicated?

Transparency, Public Engagement & Trust

How can stakeholders be meaningfully engaged in shaping data governance frameworks to foster public trust, openness, and accountability?
What is the responsibility of governments to inform the public about data use and promote awareness of how companies and institutions extract value from personal data?
How can mechanisms be implemented to make it easier for people to understand and manage the permissions they grant for the use of their data?

Open Data & Accessibility

Through open data principles, how do we ensure states provide free and accessible public data that is unbiased?
How can data governance processes be designed to address specific challenges faced by both the Global North and Global South?
What strategies can harmonize data protection policies across sectors while respecting local values, cultural specificities, and fundamental human rights?

Governance Frameworks & Institutional Structures

How can multistakeholder data governance processes be developed and implemented to respond rapidly to new technological challenges?
How have debates on digital and data sovereignty influenced the development of data governance by governments and companies?