Page 22 - AI for Good-Innovate for Impact

AI for Good-Innovate for Impact

societal and environmental issues. This underscores the potential of AI to drive positive
social impact and contribute to global development agendas.
• Diverse Geographic Representation: The use cases exhibited geographic representation,
with submissions from 38 countries spanning both developed and developing countries.
This underscores the global relevance and applicability of AI solutions in addressing local
and global challenges.
• Collaborative Approach: The selection process involved collaboration between project
team members and external stakeholders, such as scholars and authors, demonstrating
the importance of a collaborative approach in curating impactful use cases and fostering
knowledge exchange.
• Standards based and Criteria-based Evaluation: The use cases were evaluated based on
predefined criteria, including clarity, alignment with SDGs, potential for AI acceleration,
future scalability, and adherence to ITU scope and standards. This systematic evaluation
approach ensured the selection of high-quality use cases aligned with project objectives.
• Digital Divide Considerations: While AI holds immense potential for driving innovation
and progress, there were considerations regarding the digital divide and disparities in
access to technology. Efforts were made to ensure equitable access to AI technologies
and promote inclusive growth and opportunity for all.

The use cases provided valuable insights into the diverse applications of AI across sectors
and regions, highlighting its transformative potential and the importance of inclusive and
collaborative approaches to AI development and deployment.

3�2 Future work:
• Scholar Engagement and Capacity Building:

o The selected scholars will play a crucial role in promoting the use cases and engaging
in discussions at the Innovation for Impact Workshop during the AI for Good Global
Summit and AI for Good Innovate for Impact in 2024 and beyond.
o Continued engagement with scholars and onboarding new scholar engagements will
involve capacity building initiatives, such as future workshops, to enhance their skills
and expertise in AI for sustainable development.

• Integration with AI for Good Platform:
o The use case collection will be integrated into the AI for Good platform, providing
global visibility and accessibility to stakeholders interested in leveraging AI for
advancing sustainable development goals.
o Collaboration with other stakeholders will ensure the seamless integration of the use
cases into existing platforms and initiatives focused on AI for good.

• Dissemination and Awareness Campaigns:

o The project team will conduct targeted dissemination and awareness campaigns
to promote the use cases among relevant stakeholders, including policymakers,
researchers, industry leaders, and civil society organizations.
o Strategies such as webinars, social media outreach, and participation in conferences
and events will be employed to raise awareness about the transformative potential of
AI in addressing global challenges and advancing sustainable development agendas.

• Impact Assessment and Evaluation:
o The impact of the use cases on advancing sustainable development goals will be
assessed through qualitative and quantitative evaluation methods, including case
studies, user surveys, and performance metrics.

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