JKUAT

Outcomes that would make the first Global Dialogue on AI Governance a success would include the meaningful inclusion of developing regions such as Africa and South America in the conversation. This would ensure that global AI governance reflects the realities, priorities, and challenges of all countries, rather than being shaped only by a few technologically advanced nations. A truly global dialogue should create space for diverse perspectives and context-specific approaches to AI governance. Beyond governments, it will also be important to include a broad range of stakeholders in the discussions. These should include civil society organisations , human rights advocates, researchers, youth representatives, developers of both commercial and open-source AI tools, policymakers, private sector actors, and everyday users of AI systems. Inclusive participation will help ensure that AI governance is people centered, equitable, and responsive to the needs of society. Another factor for success will be the selection of thematic areas for discussion. The dialogue should focus on sectors where AI is already having a major impact and where governance frameworks are urgently needed. Key areas could include: Education ,healthcare , agriculture ,climate change, employment and workforce transition ,public services and governance and data protection and privacy .Discussions in these sectors should explore both the opportunities AI presents and the risks it may create, especially for vulnerable populations. Particular attention should also be given to issues of equity, digital inclusion, infrastructure gaps, and capacity building in low- and middle-income countries. Ultimately, the success of the dialogue will depend on whether it creates a collaborative, inclusive, and action-oriented platform that supports responsible AI development while ensuring that no region or community is left behind.

AI capacity-building;Open-source software, open data and open AI models;Transparency, accountability, and human oversight;Safe, secure and trustworthy AI

Here I explain the priorities selected in the previous section. This has been listed in order of priority. 1. Safe, secure and trustworthy AI: Developing responsible, interoperable, and trustworthy approaches to AI governance is essential to ensure AI systems are safe, reliable, secure, and ethically sound. This will be important in aligning standards, strengthening governance approaches, and minimizing risks associated with AI systems. 2. Transparency, accountability, and human oversight:There is need for mechanisms that ensure AI systems remain understandable, accountable, and subject to meaningful human oversight, especially in high-impact sectors. Transparent and accountable governance frameworks are useful to building public trust. This way adoption of AI will be easier. 3. AI capacity-building: Capacity building of AI is important to ensure developing countries are not left behind in the AI ecosystem. This will include strengthening digital infrastructure, technical skills, research capacity, and equitable access to AI technologies. Addressing capacity gaps and strengthening AI ecosystems in developing countries will help bridge AI differences and facilitate access to high-performance computing and related resources. Some of these resources are limited and should be accessible. Besides capacity building in technology there is also the aspect of AI literacy among the citizens, awareness should be created for different groups in the society. 4. Open-source software, open data and open AI models:Promoting open-source software, open data, and open AI models can support innovation, inclusivity, collaboration, and equitable access to AI technologies. Open ecosystems can also help strengthen local innovation capacity and reduce barriers to participation for developing countries and underrepresented communities. Being in academia I support the use of open source data snd software. It provides opportunity for all even those who may not afford, can contribute their ideas.

One important cross-cutting issue that could be more explicitly reflected across the thematic areas is the role of AI in health and public health systems.AI is increasingly being used in healthcare, disease surveillance, medical research, diagnostics, health system management, and emergency response.For instance, Open-source AI models are vital for real-time disease surveillance. By utilizing open data, nations can collaborate on global health security, sharing predictive models for pandemic preparedness without the barriers of proprietary licensing.Whether through enhancing diagnostics to bridge workforce gaps, securing data for global surveillance, or protecting ethical standards in patient care, AI's role in public health is essential for achieving the Sustainable Development Goals (SDG 3) which aims to "Ensure healthy lives and promote well-being for all at all ages". This is also a sector that deals with very sensitive data and ethical issues. Another important aspect is the environmental and climate impact of AI systems. The rapid growth of AI technologies has implications for energy consumption, water use, and carbon emissions due to increasing computational demands. Integrating sustainability considerations into AI governance discussions will be important to support environmentally responsible AI development and innovations. While we highlight capacity building of AI, it is important to mention the need for AI literacy and awareness to the public this way we can develop more inclusive, transparent, and accountable governance processes with input from even the public.

The most significant challenges in AI capacity-building include the lack of adequate digital infrastructure and limited access to computing resources within research and academic institutions. These limitations affect the ability of researchers, students, innovators, and institutions to actively participate in AI development, research, and innovation. Limited access to high-performance computing, quality datasets, and technical resources can slow local innovation and widen existing digital divides between developed and developing countries. At the same time, these challenges also present important opportunities to promote the use of open-source technologies, open software, and collaborative innovation ecosystems. Open-source AI tools and platforms can help lower barriers to entry, expand access to knowledge and technical resources, and support local research and innovation efforts, particularly in resource-constrained environments. Another significant challenge is the absence of comprehensive and localized AI policies and governance frameworks that can effectively guide the development, deployment, and use of AI technologies. In many countries, existing regulatory and institutional frameworks are still evolving and may not adequately address local realities, priorities, and risks. This can create uncertainty around accountability, ethics, data governance, safety, and responsible use of AI systems.At the same time, this presents an opportunity for countries and regions to develop inclusive, context-specific, and human-centered AI governance approaches that reflect local needs while aligning with international principles and emerging global standards.

AI Dialogue can play an important role in advancing international cooperation on AI governance by providing an inclusive and multi-stakeholder platform for countries, institutions, civil society, academia, and the private sector to exchange perspectives, share experiences, and identify common priorities for responsible AI development and use. The dialogue can help build a shared understanding of the opportunities, risks, and governance challenges associated with AI .This could include sharing on best practices that have worked and can be adopted by others. In addition, it is a platform where participants can collaborate in addressing global AI inequalities like digital infrastructure support and even discuss opportunities in open science adoption for AI.

The AI Dialogue should build upon and connect with existing international, regional, and multi-stakeholder initiatives that are already contributing to AI governance, standards development, digital cooperation, and capacity-building. Leveraging existing mechanisms can help avoid duplication, strengthen coordination, and accelerate collective progress on responsible AI governance. There are some academic institutions and research organizations that are supporting AI research, ethics, safety and digital inclusion.

Government and policy makers can identify gaps in governance and adoption and implementation of AI within their countries and the context . They are also best placed to create regulatory frameworks within their countries and regions. Developers of AI tools can give the technical aspects of the developing and deploying the tools . In addition they can provide insights on the scaling up of the tools. Academia and research organisations can contribute on scientific evidence on the use and impact of AI and develop methods of risk assessment of AI and also tools for monitoring and evaluation of AI. Civil and human right organisations would be great to identify any ethical concerns that are in the use of AI and guard any concerns that could arise from the vulnerable groups . This ensures that the concerns and implications of AI for marginalized persons and the less privileged in the society are considered. The citizens/ public will be important stakeholders since they are the ones who will experience the societal impact of AI first hand and can raise inclusivity issues within the society early enough. The Private sector can contribute since they invest in the development and deployment of the AI tools.This will also encompass aspects of commercialisation.

Some of the voices that need to be included in the conversations are the developing countries and marginalised communities. Another group that seems underrepresented is the youth despite that fact that AI will have along impact in different aspects of their life including education, employment and social structures just to name a few.Vulnerable persons like those who are abled differently need to be included in the conversation. Women and girls also need to be included in this conversation.To include these voices there may be need to collect their views early by organising workshops or webinars where they can air their opinions.Another way would be strengthening AI capacity-building and digital literacy initiatives within the regions and scale it down to institutions too.

Roundtable group discussions that are constituted with persons from different stakeholder groups.For online meetings consider polling or voting on issues and the use of breakout rooms. Show cases and panel discussions would also be a good form of engangement

In Kenya, the Data Protection Act (2019) provides an important foundation for responsible AI governance, particularly in areas related to privacy, consent, data security, and accountability in the use of personal data. As AI systems increasingly rely on large volumes of data, the Act offers useful principles that can help guide ethical and responsible AI development and deployment. Universities and research organizations are increasingly organizing training sessions, workshops, webinars, and public engagement forums to strengthen understanding of AI technologies, governance, and responsible use. For instance Jomo Kenyatta University of Agriculture and Technology(JKUAT) has organized AI awareness and capacity-building sessions. African Population and Health Research Center(APHRC) has hosted webinars and discussions on AI and digital governance. Innovation and technology hubs are also contributing through innovation programs, training initiatives, and knowledge-sharing platforms that support AI learning and local innovation ecosystems.