Ethiopian women's development organization/EWDO

In my view, the success of the first Global Dialogue on AI Governance would depend on how practical, inclusive, and action-oriented the outcomes are, rather than just how many ideas are discussed. One important outcome would be reaching a common understanding of what responsible and ethical AI means across different countries and sectors. This should not remain at a theoretical level but clearly reflect real concerns, especially the risks that AI systems pose to women and girls, such as bias, exclusion, and online harm. Recognizing these issues openly would be a strong step forward. Another key outcome would be the development of clear and realistic recommendations that countries and organizations can actually apply. Since not all countries have the same level of digital capacity, the guidance should be flexible and supportive, allowing each context to adapt it in a meaningful way. I also believe the dialogue would be successful if it ensures genuine participation from diverse voices. It is important that women-led organizations, civil society groups, and representatives from the Global South are not only present but are actively influencing the conversation and outcomes. In addition, building partnerships among governments, private sector actors, and civil society would be a valuable result. Collaboration is essential if AI governance efforts are to be effective and sustainable. Finally, there should be clear follow-up actions. Without accountability and continued engagement, even the best discussions may not lead to real change. Overall, success would mean moving from conversation to commitment, and from commitment to practical action that promotes fairness, safety, and inclusion in AI governance.

• AI capacity-building
• Protection and promotion of human rights
• Transparency, accountability, and human oversight
• Safe, secure and trustworthy AI

I selected these four priority areas because they are closely connected to the real challenges we see in how AI is developed and used today, especially for women and vulnerable groups. First, the protection and promotion of human rights is very important. AI systems can sometimes reinforce discrimination or exclude certain groups if they are not designed carefully. Making human rights a priority helps ensure that AI benefits everyone equally. Second, transparency, accountability, and human oversight are essential. Many AI systems are not easy to understand, and this can create trust issues. People should know how decisions are made and there should always be human responsibility behind AI systems. Third, safe, secure, and trustworthy AI is critical. If AI systems are not safe, they can cause harm in different ways, including spreading misinformation or creating biased outcomes. Building trust in AI is necessary for its long-term use and acceptance. Finally, AI capacity-building is important, especially for countries and communities that are still developing their digital systems. Without proper skills, knowledge, and resources, it is difficult to participate in or benefit from AI governance. Capacity-building helps ensure more inclusive and fair participation. Overall, I chose these areas because they focus on fairness, safety, and inclusion, which I believe are the most urgent priorities in AI governance today.

Yes, I believe there are some important cross-cutting and emerging issues that are not fully captured in the listed themes. One key issue is the digital gender divide. While many discussions focus on access to technology, they do not always address the deeper inequalities that limit women and girls from fully participating in AI spaces. This includes gaps in education, digital skills, and leadership opportunities in the tech sector. Another important issue is the impact of AI on unpaid care work and informal economies. In many countries, especially in developing contexts, women are highly involved in informal work that is often not recognized in AI and digital policies. AI systems may ignore or undervalue these contributions, which can increase existing inequalities. Data inequality is also a growing concern. Many AI systems are trained on data that does not represent diverse populations. This can lead to biased outcomes and unfair decisions, especially for marginalized groups. There is a need to ensure that data used in AI is inclusive and responsibly managed. In addition, language and cultural representation remain under-discussed. Many AI tools do not support local languages or reflect cultural contexts, which can exclude large groups of people from benefiting from AI technologies. Finally, the issue of power imbalance should be considered. A small number of countries and companies have significant control over AI development. This can limit the voice and influence of smaller or developing countries in global decision-making. Overall, addressing these cross-cutting issues is important to ensure that AI governance is truly inclusive, fair, and relevant to different realities.

In my context, the gaps in AI governance are already starting to show both challenges and opportunities. One of the main challenges is the lack of clear policies and regulations. AI is being used in different sectors, but there is limited guidance on how to ensure it is fair, safe, and respects human rights. This creates a risk of misuse, especially for vulnerable groups such as women and young people, who may face bias, exclusion, or online harm. Another challenge is low capacity. Many institutions and professionals do not yet have enough knowledge or skills to understand or manage AI systems effectively. This makes it difficult to implement transparency, accountability, and proper oversight. There are also issues with data. In many cases, the data used is limited or not representative, which can lead to unfair outcomes. In addition, there is not enough awareness about data protection and privacy. At the same time, there are important opportunities. AI has the potential to improve services in areas like education, healthcare, and public service delivery. If used properly, it can help reach more people and improve efficiency. There is also growing interest among young people and organizations to engage with digital technologies, including AI. This creates a good opportunity to build local capacity and promote innovation. Overall, while governance gaps create real risks, they also highlight the need for stronger systems, better awareness, and inclusive approaches. If these are addressed early, AI can be used in a way that benefits society and reduces inequality.

In my view, the AI Dialogue can play a very important role in strengthening international cooperation on AI governance. First, it can create a shared space where countries, organizations, and experts come together to discuss common challenges and learn from each other. Since countries are at different levels of technological development, this kind of platform helps bridge the gap and promotes mutual understanding. Second, the dialogue can support the development of common principles and standards for AI governance. While each country has its own context, having some level of global alignment is important to ensure that AI is developed and used in a safe, fair, and responsible way across borders. Another important role is encouraging collaboration and partnerships. The dialogue can connect governments, private sector actors, and civil society organizations, making it easier to work together on solutions, share knowledge, and build trust. It can also help amplify the voices of underrepresented groups, including countries from the Global South and women-led organizations. This is important to make sure that global AI governance is not dominated by a few actors, but reflects diverse perspectives and realities. In addition, the AI Dialogue can promote capacity-building by encouraging resource sharing, training opportunities, and technical support between countries and institutions. Finally, it can help create follow-up mechanisms that encourage continued cooperation, not just one-time discussions. Ongoing engagement is key to responding to the fast-changing nature of AI. Overall, the AI Dialogue can serve as a bridge that connects different actors and supports more inclusive, coordinated, and effective global AI governance.

There are already several global and regional initiatives working on AI governance that the AI Dialogue can build on. For example, efforts like the Global Digital Compact, UNESCO's work on AI ethics, and other multi-stakeholder platforms are creating important discussions and guidance around responsible AI. There are also regional collaborations and civil society networks that focus on digital rights, gender equality, and technology. The AI Dialogue should not duplicate these efforts but instead connect and strengthen them. One important role it can play is bringing these different initiatives together in a more coordinated way. Right now, many efforts are happening separately, and there is limited alignment between them. Another added value of the AI Dialogue is inclusiveness. It can create more space for voices that are often underrepresented, such as countries from the Global South, grassroots organizations, and women-led groups. This can help ensure that global AI governance reflects real needs and diverse experiences. The Dialogue can also help translate global principles into practical actions. While many frameworks already exist, there is still a gap in implementation. By encouraging knowledge sharing and collaboration, the AI Dialogue can support countries and organizations in applying these principles in their own contexts. In addition, it can strengthen partnerships by connecting governments, private sector actors, and civil society in a more structured way. This can lead to more effective and sustainable solutions. Overall, the added value of the AI Dialogue is its ability to connect, coordinate, and make existing efforts more inclusive and action-oriented.

Different stakeholders can contribute to the AI Dialogue in many ways, and the format should make it easy for everyone to participate meaningfully. Governments can share their experiences in developing policies, regulations, and strategies for AI, highlighting successes, challenges, and lessons learned. Private sector actors can provide insights on technological developments, ethical practices, and responsible AI implementation. Civil society organizations and community groups can bring perspectives from marginalized communities, including women, youth, and the Global South, ensuring that diverse voices are represented. Academia and research institutions can contribute evidence-based research, analyses, and recommendations. To make participation inclusive, the dialogue should combine different formats. Panel discussions and keynote sessions can highlight global trends and challenges. Smaller breakout sessions or workshops can allow for more interactive discussions, enabling participants to share local experiences and practical solutions. Online platforms should be available to allow those who cannot attend in person to join and contribute. The dialogue could also include mechanisms for pre-submitted written inputs, allowing stakeholders to share detailed perspectives ahead of time. Translation services and accessible formats should be provided to ensure that language or technical barriers do not exclude participants. Finally, follow-up mechanisms are important. Stakeholders should have opportunities to continue discussions after the event, track progress, and provide feedback. This helps turn dialogue into action and ensures that all voices remain part of the conversation. Overall, a mix of large and small sessions, in-person and online participation, and clear channels for input and follow-up will make the AI Dialogue inclusive, practical, and impactful.

Many voices and communities are still underrepresented in global AI governance discussions. Women and girls, particularly from the Global South, are often missing from conversations even though they are disproportionately affected by AI-related harms. Rural communities, people with disabilities, and other marginalized groups also have limited opportunities to participate. In addition, smaller countries or those with less digital capacity rarely have the same influence as larger, tech-focused nations. Local communities, indigenous peoples, and speakers of less common languages are often excluded because AI systems, policies, and discussions do not fully reflect their realities or cultural contexts. To include these underrepresented perspectives, the AI Dialogue should actively reach out to diverse stakeholders and create accessible spaces for participation. This could include providing translation and interpretation services, using simple and clear language, and offering online participation for those who cannot travel. Targeted outreach to women-led organizations, community groups, and grassroots networks can help ensure these voices are heard. Financial and technical support for participants from low-resource settings would also reduce barriers to engagement. In addition, pre-submitted inputs and consultations at local and regional levels can give underrepresented groups a structured way to share their experiences and priorities. Breakout sessions and workshops focused on specific communities or issues can also create safe spaces for open discussion. Overall, deliberate efforts to reduce barriers, provide support, and actively seek out diverse voices will make AI governance discussions more inclusive. This ensures that policies and decisions reflect the needs of all people, not just those with the most resources or technical expertise.

To foster meaningful and dynamic engagement during the AI Dialogue, a mix of innovative formats can be very effective. Interactive workshops and breakout sessions allow participants to work in smaller groups, share experiences, and develop practical solutions together. These sessions are more engaging than large panels because everyone has a chance to speak and contribute. Roundtable discussions with diverse stakeholders, including governments, private sector, civil society, and academia, can encourage open debate and ensure multiple perspectives are considered. Using moderators to guide conversations can help keep discussions focused and productive. Digital engagement tools, such as live polls, Q&A platforms, and collaborative online whiteboards, can allow both in-person and remote participants to contribute in real time. This makes the dialogue more inclusive, especially for those who cannot attend physically. Storytelling sessions or case-study presentations can highlight real-world experiences and make technical issues easier to understand. This helps participants connect abstract AI governance principles with practical challenges and opportunities. Hackathons or innovation labs can bring together technologists, researchers, and civil society to develop prototypes, tools, or policy ideas during the dialogue. This adds a hands-on, creative dimension and encourages collaboration across sectors. Finally, pre-dialogue consultations and post-dialogue feedback mechanisms ensure that engagement is continuous, not limited to the days of the event. Participants can share their inputs ahead of time and continue contributing afterward, making the process more dynamic and action-oriented. Overall, combining interactive, digital, and hands-on approaches with continuous engagement will create a dialogue that is inclusive, practical, and capable of producing concrete outcomes.

There are several examples of policies and practices that promote effective AI governance and help address its challenges. One example is the European Union's AI Act, which provides clear rules to ensure AI systems are safe, transparent, and respect fundamental rights. It categorizes AI applications by risk and requires strict oversight for high-risk systems. This approach helps prevent harm while encouraging responsible innovation. UNESCO's Recommendation on the Ethics of Artificial Intelligence is another good practice. It offers global guidance on ethical AI, human rights, inclusion, and sustainability, helping countries develop policies that reflect shared values. Platforms like Partnership on AI bring together companies, civil society, and researchers to share knowledge, develop best practices, and ensure AI is developed responsibly. Multi-stakeholder collaborations like this encourage transparency and accountability. Some countries have also introduced national AI strategies that combine regulation, capacity-building, and innovation support. For example, Canada's Directive on Automated Decision-Making sets clear standards for government use of AI, including risk assessments, transparency, and monitoring to protect citizens. On the civil society side, organizations promoting gender-inclusive AI are developing guidelines and tools to reduce bias in AI systems and ensure women and marginalized groups are represented in data, design, and decision-making. Open-source tools and platforms also contribute to effective governance. By providing accessible AI models and data, they allow wider participation, independent evaluation, and collaboration, helping reduce the concentration of power in a few large companies. Overall, these examples show that effective AI governance requires a combination of clear rules, ethical guidance, multi-stakeholder engagement, and practical tools. Adopting and adapting these approaches can help countries and organizations manage AI risks while supporting innovation and inclusion.