Page 39 - AI Governance Day - From Principles to Implementation

AI Governance Day - From Principles to Implementation

• Are there other ways of pursuing open-source objectives while keeping models closed-
source?
• How do we decide if models should be open- or closed-sourced?

4.5.4 Insights from the breakout sessions: theme 3

The following outlines key strategies and actions essential for ensuring inclusion and trust in AI.

• Differentiation and guidelines

– Develop guidelines to distinguish between AGI and specific AI models.
– Tailored oversight and regulation are essential for managing each AI type effectively.
• Incentives and policies

– Implement compute taxes and investment requirements to incentivize businesses to
prioritize inclusivity and trustworthiness in AI development.
– Transparency and Oversight
– Establish sandbox environments for AI testing with oversight from civil society,
academia, and public/private sectors.
– Ensure testing processes and outcomes are transparent to build community trust.

• Certification and ethical standards
– Create sector-specific certifications with diverse global input.
– Facilitate international dialogue to establish ethical guidelines that respect local
regulations and cultural differences.
• Education and connectivity

– Promote digital literacy and expand connectivity to underserved communities.
– Support global participation in AI by improving digital skills and access to AI resources.
• Governance and regulatory frameworks

– Develop clear ethical guidelines and regulatory frameworks with global consensus.
– Ensure governance processes are open and inclusive, allowing for public input and
scrutiny.

• Addressing bias
– Urgently address biases in AI algorithms to ensure fairness and prevent inequalities.
– Open Ecosystem and Collaboration
– Encourage an open AI ecosystem to foster innovation and trust.
– Promote collaboration between developers, governments, and NGOs.
• Data hubs and connectivity

– Develop data hubs and improve connectivity, especially in developing regions, to
support AI infrastructure and access.
• Social dialogue and diverse perspectives

– Facilitate regular discussions between stakeholders to understand and adopt AI.
– Ensure diverse perspectives are included in AI development and decision-making
processes.

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