Page 60 - AI for Good - Impact Report

AI for Good

Key considerations:

• Adopt and tailor international frameworks: Base national AI policies on established
frameworks adapting them to local needs and priorities.
• Develop a comprehensive national AI strategy: Create a strategy that integrates ethical
principles, governance, and national challenges.
• Implement and enforce ethical standards: Ensure fairness, transparency, and accountability
by developing and enforcing ethical guidelines.
• Foster stakeholder engagement: Involve diverse stakeholders in shaping and monitoring
AI policies to ensure broad representation and accountability.

2) Capacity Building and Education
Building AI skills and knowledge through capacity building and education is vital for bridging
the AI digital divide. Enhancing institutional and individual capabilities ensures that both present
and future generations are equipped to leverage AI's benefits. Robust educational programs
provide professionals with the essential knowledge for successful AI integration, while capacity
building strengthens institutions to support and sustain AI-driven advancements, creating a
more inclusive and equitable technological future.

Key considerations:

• Integrate AI into curricula: Incorporate AI and data science education across all levels,
from early education to higher education, to build foundational skills and prepare future
generations for an AI-driven world.
• Develop training programs: Establish targeted training and certification programs for AI
professionals and policymakers to ensure they have the necessary skills and expertise for
AI development and governance.
• Support research and development: Invest in R&D to drive AI innovation, advance
knowledge, and develop cutting-edge applications that benefit national development.
• Establish scholarships for underrepresented groups: Implement targeted scholarship
programs to support individuals from diverse backgrounds in AI education and training.
3) Promote Responsible AI Investment

Investment is crucial for advancing technological capabilities, driving innovation, and ensuring
effective implementation of AI applications across sectors. It can help boost economic growth,
enhance competitiveness and facilitate international collaboration.

Key considerations:
• Incentivize responsible AI research and development: Provide grants, tax incentives, or
subsidies for projects that prioritize ethical considerations, sustainability, and social impact
in AI research and development.
• Promote public-private partnerships: Foster collaboration between government,
academia, and industry to develop and implement best practices for responsible AI and
facilitate knowledge sharing and innovation.
• AI responsible innovation fund: Allocate funds to support startups and scale-ups
developing AI technologies that advance the UN SDGs or other AI projects that aim to
solve social and environmental matters. This fund could offer financial support, mentorship,
and resources to AI-driven ventures that contribute to sustainable development and
enhance social impact.

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