| APrIGF 2026 Session Proposal Submission Form | |||||||||||||
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| Part 1 - Lead Organizer | |||||||||||||
| Contact Person | |||||||||||||
| Mr. Uzair Farooqi | |||||||||||||
| Organization / Affiliation (Please state "Individual" if appropriate) * | |||||||||||||
| Jazz / Employee | |||||||||||||
| Designation | |||||||||||||
| Network Perfomance Analyst | |||||||||||||
| Gender | |||||||||||||
| Male | |||||||||||||
| Economy of Residence | |||||||||||||
| Pakistan | |||||||||||||
| Stakeholder Group | |||||||||||||
| Private Sector | |||||||||||||
| List Your Organizing Partners (if any) | |||||||||||||
| Name: Iqra Ejaz Organisation/Afilliation: UET / Student Email: iqraejaz49@gmail.com Contact Number: +92 3350235467 Gender: Female Economoy of Residence: Pakistan Stakeholder Group: Academia As a co-organizer of this session and a researcher from UET(University of Engineering and Technology ) Lahore, I bring an academic perspective to discussions on Internet governance, AI governance, and digital inclusion. Through participation in ICANN81, APNIC56, APAN58, and MEACSIG, I have engaged with diverse stakeholders and contributed to discussions on emerging digital policy challenges. My research and policy interests focus on the intersection of technology, governance, and societal impact, particularly in underserved communities. This background enables me to facilitate evidence-based and inclusive dialogue, connect technical and policy perspectives, and guide the discussion toward meaningful insights and actionable outcomes on AI memory, digital rights, and governance. |
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| Part 2 - Session Proposal | |||||||||||||
| Session Title | |||||||||||||
| The Right to Be Forgotten by AI: Who Owns Human Knowledge in the Age of Foundation Models? | |||||||||||||
| Thematic Track of Your Session | |||||||||||||
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| Session Format | |||||||||||||
| Panel Discussion (60 minutes) | |||||||||||||
| Where do you plan to organize your session? | |||||||||||||
| Hybrid (with onsite moderator and speakers both online and offline, with online moderator for questions and comments from remote participants) | |||||||||||||
| Specific Issues for Discussion | |||||||||||||
| The emergence of foundation models has introduced a governance challenge that existing data protection and privacy frameworks were never designed to address. While individuals may exercise rights over personal data before it is collected or processed, those rights become significantly less clear once information has been incorporated into the training of large-scale AI systems. As AI models increasingly learn from publicly available content, community archives, cultural records, local knowledge repositories, and user-generated data, important questions arise regarding ownership, consent, accountability, and the possibility of removal. This session will explore whether traditional concepts such as data deletion, consent withdrawal, and the right to be forgotten remain meaningful in the era of generative AI. The session will examine emerging governance questions, including whether AI systems should be capable of 'forgetting,' who should determine what knowledge remains within models, how community consent differs from individual consent, and what accountability mechanisms are needed when knowledge cannot realistically be removed after model training. Rather than focusing on technical solutions alone, the discussion will investigate whether new governance approaches are required to address the relationship between AI memory, digital rights, cultural preservation, and public interest. The session aims to identify governance gaps likely to become increasingly significant as AI systems become foundational components of digital societies. |
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| Describe the Relevance of Your Session to APrIGF | |||||||||||||
| This session directly contributes to the overarching theme of AI Governance for Good by examining a critical governance question that remains largely absent from regional and global policy discussions: what rights, responsibilities, and governance mechanisms should exist once knowledge has already been incorporated into AI systems. Current AI governance debates largely focus on model outputs, safety measures, and regulatory oversight. However, considerably less attention has been devoted to the governance of AI memory itself—the accumulated knowledge foundation models derive from billions of data points. As governments, businesses, educational institutions, and citizens across Asia-Pacific increasingly rely on generative AI, questions surrounding ownership, representation, consent, and accountability in AI training processes will become central public policy concerns. The issue is particularly relevant to Asia-Pacific because the region contains a significant proportion of the world's linguistic diversity, indigenous knowledge systems, cultural archives, and digitally emerging communities. Decisions regarding whose knowledge is incorporated into AI systems, who benefits from its use, and who has the authority to challenge or withdraw participation will have long-term implications for digital inclusion, cultural representation, and equitable AI development. Through a multistakeholder dialogue involving policymakers, technical experts, researchers, civil society, and community stakeholders, the session will explore whether current governance models are adequate for addressing foundation models and generative AI. Expected outcomes include identifying governance gaps, generating recommendations for regional dialogue, and building understanding of how consent, ownership, participation, and accountability may evolve in AI. By addressing this challenge before it becomes a policy-crisis, the session seeks to contribute to AI governance in the Asia-Pacific region |
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| Methodology / Agenda (Please add rows by clicking "+" on the right) | |||||||||||||
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| Moderators & Speakers Info (Please complete where possible) - (Required) | |||||||||||||
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| Please explain the rationale for choosing each of the above contributors to the session. | |||||||||||||
| Iqra Ejaz: Will guide a balanced discussion by connecting technical, policy, and community perspectives, drawing on experience from ICANN81, APNIC56, APAN58, and MEACSIG. Milan Adhikari: Will help participants understand technical realities of AI systems and data retention, ensuring governance discussions remain practical and informed. Tayyaba Iftikhar: Will contribute perspectives on privacy, accountability, and digital rights, helping assess governance implications of AI memory and persistent data use. Shraddha Pandey: Will provide legal insights on consent, ownership, responsibility, and regulatory gaps relevant to AI governance challenges. Dr. Muhammad Aslam: Will explain how AI models learn, retain, and use information, helping bridge technical understanding and policy expectations. |
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| If you need assistance to find a suitable speaker to contribute to your session, or an onsite facilitator for your online-only session, please specify your request with details of what you are looking for. | |||||||||||||
| We are actively seeking to further diversify the panel across stakeholder groups, geographies, and gender representation to ensure a truly multistakeholder and inclusive discussion. While the current panel includes representatives from academia, the technical community, policy, and legal sectors, we would welcome the Secretariat's assistance in identifying additional experts from underrepresented stakeholder groups, including government, civil society, private sector, and international organizations. This would help ensure that a broad range of perspectives is reflected in the discussion and that all relevant voices are represented at the table. We are also committed to maintaining gender balance and fostering equal participation across the panel. Additionally, an onsite facilitator would be valuable for managing audience engagement and relaying questions from the floor, particularly if members of the organizing team participate remotely. | |||||||||||||
| Has AI been used to develop this proposal? | |||||||||||||
| No | |||||||||||||
| Please declare if you have any potential conflict of interest with the Program Committee 2026. | |||||||||||||
| No | |||||||||||||
| Are you or other session contributors planning to apply for the APrIGF Fellowship Program 2026? | |||||||||||||
| Yes | |||||||||||||
| Upon evaluation by the Program Committee, your session proposal may only be selected under the condition that you will accept the suggestion of merging with another proposal with similar topics. Please state your preference below: | |||||||||||||
| Yes, I am willing to work with another session proposer on a suggested merger. | |||||||||||||
| APrIGF offers live transcripts in English for all sessions. Do you need any disability related requirements for your session? APrIGF makes every effort to be a fully inclusive and accessible event, and will do the best to fulfill your needs. | |||||||||||||
| No | |||||||||||||
| Number of Attendees (Please fill in numbers) | |||||||||||||
| Gender Balance in Moderators/Speakers (Please fill in numbers) | |||||||||||||
| Consent | |||||||||||||
 I agree that my data can be submitted to forms.for.asia and processed by APrIGF organizers for the program selection of APrIGF 2026. |
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