University of Padova, Italy

A successful global dialogue on AI Governance would bring real progress in terms of practicality in the field of opportunities and implications, bridging AI divides and human rights. This will help to turn the inclusive principles into real and practical participation, especially by focusing and advocating for the participation of students in the education system. Under cluster 1, there would be a shift from occasional student consultation to real-time co-governance with other stakeholders, reflecting students' educational experience rather than ideas and beliefs formed without students' input. The success would also mean formally when the students and young people will be recognized as stakeholders in the AI governance. Secondly, in cluster 2, the dialogues should end with clear and guideline or a framework that helps institutions to actually involve the students in AI Governance. This is important because most of the organizations support inclusiveness, but that is only in the documents and they often fail because they don't have the valid tools or mechanisms that are needed to make this inclusiveness in practice. A designed framework for AI governance in higher education would aid in making participation more reliable across different regions and institutions. This would also reduce inequality, ensuring that whether or not students can take part in AI decision-making doesn't depend on where they live or how well-resourced their university is. Thirdly, in cluster 4, success requires strong and convincing involvement in capacity building; therefore, the participation is meaningful, not only symbolic. To ensure the genuine participation of students on equal terms, they need AI literacy, governance training, and equal access to resources wherever required. Finally, the Dialogue should establish clear accountability and monitoring systems and to ensure the actual implementation, participation of the students should be tracked through indicators and sharing the progress globally to guarantee fairness, inclusion and transparency. So in view of the above, a successful Dialogue would translate multistakeholderism into institutionalized participation and reduce the gap between AI principles and practice, and ensure that those most affected students help shape the future of AI in education.

• Safe, secure and trustworthy AI
• AI capacity-building
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Protection and promotion of human rights

1. Safe, secure and trustworthy AI Trustworthy AI in education depends on validity and accountability. As highlighted in our policy brief, excluding students from governance weakens both validity and accountability. To ensure safety and trust, there must be inclusive decision-making structures, wherein students can recognize the risks, biases, and inconsistencies in the real world of AI 2. AI capacity-building For meaningful contribution, capacity building is an essential element because students can not participate effectively without AI education, ethical and moral awareness, and understanding of the policy. Our proposed framework focuses on training for students, educators, and administrators to bridge this gap. 3. Social, economic, ethical, cultural, linguistic and technical implications of AI Students experience these implications daily. Their perspectives are crucial in identifying issues such as bias, inequality, and contradictory AI policies in universities. Including them enhances the relevance and responsiveness of governance frameworks. 4. Basic/Individual's rights Participation itself is a democratic right. Excluding students from AI governance risks undermining principles such as agency, equality, and non-discrimination. Implementing and ensuring co-governance that AI systems in education respect human rights and reflect diverse experiences.

There are a few important issues that are not fully covered in the listed themes, especially when we look at AI governance in higher education. One major gap is who actually gets to participate in decision-making. Many of the themes talk about safety, ethics, and transparency, but they don't clearly address participation. In reality, students are most affected by AI in education and are often not included in real decision-making processes. Another issue is the power imbalance in universities and institutions. Even when different groups are included, decisions are usually still made by senior staff or administrators. This makes it hard for students to have a real influence, even if they are asked for their opinions. A related point is AI literacy and understanding. Even if participation is open, not everyone has the same level of knowledge about AI. Without basic understanding and training, especially for students from less privileged backgrounds, participation may not be meaningful. There is also a gap between policy and practice. Many frameworks support ideas like inclusion and multistakeholder governance, but in practice, student involvement is often limited to surveys or feedback forms that do not really affect final decisions. Overall, these gaps show that it is not only about making AI safe and ethical, but also about making sure governance is truly inclusive and gives a real voice to those who are most affected.

Our standpoint: as students advocating for inclusive and equitable AI governance in higher education. A major governance gap is the cutoff concerning AI use and AI regulation in universities. While AI is widely used, policies are often developed without the participation of students which causes low validity, inconsistent rules, and reduced efficiency. Higher education systems are often hierarchical in governance, which means students don't get much say in decisions making. This leaves out different viewpoints and can make existing inequalities and biases in AI even worse. Also, many students don't get the training or support they need to understand AI, which makes it hard for them to take part, especially those from less privileged backgrounds or underdeveloped countries More broadly, there are no clear or common systems that ensure student participation. Because of this, student involvement is often unorganized and limited to just being asked for opinions, without any real impact on decisions. And also, there is a significant opportunity to transform AI governance through structured student participation. As primary users, students bring practical insights that can improve policy design, identify risks, and enhance implementation more practically rather than being in documents. The Global Dialogue can catalyze this shift by promoting frameworks that will enable co-governance, accountability, fairness, and a stronger coalition between policy and practice. Moreover, if participation of the students is institutionalized and supported through training and resources, it can also encourage skills, innovation, and build trust in AI systems.

The Global Dialogue on AI can play a crucial role in advancing international cooperation by: (1) Promoting human rights-based AI governance: It will help to reinforce the inclusive participation of students, which will be essential to protect the basic rights such as agency, equality, and equal access to the education and policy making. (2) Building AI capacities To meaningfully engage stakeholders, AI dialogues will promote investment in AI literacy and training on how AI is governed, so participants can better understand and contribute to decision-making. (3) Developing shared governance frameworks The Dialogue can help develop flexible models to support countries in building systems for participatory governance while still respecting their local needs and contexts. The Dialogues can help countries and institutions learn from best practices in inclusive AI governance, reducing fragmentation.

The Dialogue should build on existing initiatives such as: a. UNESCO's Recommendation on the Ethics of Artificial Intelligence b. The Education 2030 Framework for Action c. National and institutional AI guidelines in higher education include the EU AI Act (high-risk education systems), the Philippines Department of Education (DepEd) foundational guidelines, Italy's Ministry guidelines for schools and universities, Stanford University's generative AI policy guidance, the University of Sydney's generative AI guidelines (2023/2024), and SUNY Cortland's AI guidelines (2025). These initiatives provide strong standardizing foundations but often lack operational and practical mechanisms for participation, particularly for students. AI Dialogue would be more useful if it: a. Translate existing principles into practical governance models. b. Connect global frameworks with local implementation strategies. c. Promote co-governance structures in universities by adding students. d. Enable systematic monitoring and comparison of practices across countries. By focusing on implementation and inclusion, the Dialogue can transform existing commitments into substantial outcomes, particularly in education governance.

Students are left out of the Dialogues often because they don't have enough access, resources, or awareness, especially those from marginalized backgrounds and developing countries. To address this, the Dialogue should offer training sessions to help underrepresented groups of students to understand AI and how decisions are made, and also provide financial and logistical support so they can take part. During the Dialogue, it's important to create dedicated spaces where young people and students can share their views. Participation should go beyond just listening to them; it should be interactive and allow them to actually influence decisions. Encouraging open discussions between different groups, rather than keeping conversations separate. After the Dialogue, there should be clear transparency about how participants' ideas are used. Their contributions should be reflected in the final documents, and there should be follow-up steps to make sure the ideas are actually put into action. Overall, this approach helps make participation more meaningful, inclusive, and effective, in line with the co-governance model described in the policy brief.

Groups that are often underrepresented in AI governance discussions include: a. Students and young people, especially those in higher education: Their involvement is often limited to surveys or consultations, rather than real influence on policies. b. Students from the Global South: Many face barriers like limited access to technology, funding, and global policy spaces. Because of unequal global power structures, their perspectives are often underrepresented in international AI discussions, even though AI systems strongly affect their regions c. Marginalized and low-income communities: These groups often lack access to digital tools, education, and policy platforms. As a result, they are less likely to be invited or able to participate in governance processes These groups are often left out because they lack formal decision-making power, resources, or technical knowledge, even though AI policies directly impact their lives. To make participation more inclusive, several steps are needed: a. Institutionalize participation: Students and other underrepresented groups should not be included only occasionally. They should have formal roles in governance structures, such as representation in committees or decision-making bodies, so their input has real influence. b. Strengthen capacity-building and AI literacy: Many groups are excluded because they don't have enough understanding of AI systems. Providing training and education helps them engage more confidently and meaningfully in discussions. c. Provide financial and structural support: Participation is often limited by cost, time, or lack of access. Offering funding, travel support, and accessible formats ensures that participation is not limited to well-resourced groups. d. Create inclusive engagement platforms: There should be open, accessible spaces, both online and offline, where different stakeholders can contribute easily, regardless of location, background, or technical expertise.

To make the AI Dialogue truly engaging and practical, it should encourage real interaction and group work, not just formal speeches. A good starting point would be to establish a Multistakeholder Advisory Group (MAG) comprising governments, companies, civil society, academia, and affected communities such as students. This group should help shape the agenda and outcomes, not just give feedback. Sessions should be designed so that different stakeholders actively engage with each other, rather than speaking separately to make things happen in real life. The Dialogue should combine two types of discussions. The first sessions look at broad issues like human rights, ethics, accountability, and how to align rules across countries and their implementation. Second, sector-focused discussions that explore how AI affects specific areas such as healthcare, education, jobs, climate, food systems, finance, and security, using practical examples. To keep participants involved, more interactive formats could be used, such as: • Small group discussions and roundtables to encourage exchange • Scenario exercises, where participants work together on real-life AI challenges • Open discussions, where people can join and contribute more freely • Co-creation workshops to develop concrete ideas or recommendations Using simple digital tools like live polls or shared online platforms can also help include remote participants and gather diverse inputs. Finally, follow-up activities, such as working groups or online consultations, can help continue the discussion after the event and turn ideas into real outcomes.

A useful approach to AI governance in higher education is the Framework for AI Governance in Higher Education, inspired by the 2030 Agenda. It is based on the idea that countries should stay in control of their own education systems while also learning from and cooperating with others, so AI benefits both current and future generations. The framework promotes co-governance, meaning students are not just users of AI but active participants in shaping how it is used. In practice, this means involving students in decisions about AI policies, course design, and academic rules related to AI. This helps make decisions more fair and relevant to real learning needs. The framework also provides simple tools that universities can adapt, such as student advisory groups, basic AI guidelines, and ways to include AI topics in courses. Governments are encouraged to support this by funding AI training, encouraging student participation, and helping universities build the right skills. To improve transparency, the framework suggests tracking how students are involved in decision-making and sharing good practices between universities and countries through a common platform. It also highlights the importance of training for students, teachers, and staff so everyone understands how AI works and how to use it responsibly. Regular updates are needed so the rules stay relevant as AI changes quickly. Even though there are challenges like limited resources or resistance to change, the framework offers a simple and flexible way to make AI governance in education more open, inclusive, and up to date.