Page 44 - AI for Good-Innovate for Impact Final Report 2024

AI for Good-Innovate for Impact

6�2� Use case description

6�2�1 Description

Currently, there exists a standard gap between developed and developing nations, especially
in emerging technologies such as 6G. Due to several factors such as resource scarcity and
other priorities, emerging nations in Africa find it difficult to bridge the standards gap. A
strong research background is needed to produce standards based essential innovations and
contributions which can create global solutions while being customized for regional needs. In
many cases, this background requires time and effort to set up. Due to the knowledge gap that
exists between different regions, it takes longer time for converting innovations from research
labs such as WINEST into deployment. Also, contributors from emerging regions such as Africa
find it difficult to attend, track and create contributions which are impactful technically especially
on leading technologies such as 6G.

ITU has several initiatives such as bridging the standards gap (BSG) and ML5G initiatives which
tries to bring the experts closer to such emerging regions. ITU already rolled out open source
initiatives such as ITU FG AN Build-a-thon which created reference implementations supported
by WINEST. ITU AI4Good Summit, and ML5G Discovery series of webinars and the ML5G
Challenge initiatives provides platform and opportunities, including technical videos and
webinars available free of cost. ITU provides computers including GPUs free of cost. WINEST
team, led by Prof. Agajo has already made international presentations in July 2023 in Geneva
during ITU workshop Using AI as an enabler for standards and innovation, we are able to predict
the new use cases and its architectures, classify material, including multimedia material from
ITU into context specific useful classes which can be easily consumed, generate captions in
regional languages and provide answers to queries from students and scholars. Using a co-pilot
like chatbot trained on ITU materials, we are able to easily create scenarios, experimentation
setup using open source, utilizing the already trained models, but fine-tuning based on our
needs in 6G. AI based and graph based knowledge bases (demonstrated by WINEST during
ITU FG AN Build-a-thon in 2023 and during ITU workshop on 19 Jan 2024), allows us to create
regionally curated knowledge bases based on ITU materials.

Repository Link here.

UN Goals:

• SDG 9: Industry, Innovation and Infrastructure,
• SDG 17: Partnerships to achieve the Goal
Justify UN Goals selection: The proposed use case aligns closely with UN SDG 9 and 17.

Our proposed use case aims to:

1. Address the standards gap between developed and emerging nations, especially in 6G,
thereby creating an innovative ecosystem in Africa (and beyond), which lowers the overall
cost for connectivity and interoperability for future networks.
2. Create a strong research mindshare. This creates regional standards based essential
innovations and contributions customized to regional needs, at the same time leading
the global standards. This requires strong partnership based on the open datasets and
tools put in place as described above.
3. Balance the AI awareness and expertise in Africa (and around the world), thereby
addressing the inequality and accessibility of innovations.

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