MUNESCO 2026

MODEL UNESCO ON ETHICS OF ARTIFICIAL INTELLIGENCE

Dec 9–10, 2026 Online

MODEL UNESCO ON ETHICS OF ARTIFICIAL INTELLIGENCE

Next deadline Nov 30 for chairs

Conference

Online

Dec 9–10, 2026

200 delegates expected

University students

In English

Applications

Open
  • ChairsAug 2 – Nov 30, 2026Open
  • Delegates, Head delegates, Faculty advisors, ObserversAug 1 – Dec 2, 2026Open

About

Operationalizing the Ethical Usage of Artificial Intelligence

Model UNESCO on the Ethics of AI is the formal Model United Nations component of the Global Youth Forum on the Ethics of AI. It is a one-day, six-committee simulation held entirely inside UNESCO Headquarters, in which 250 young delegates from across the 194 Member States debate, draft, and adopt a Youth Resolution on the Operationalisation of the UNESCO Recommendation on the Ethics of Artificial Intelligence.

The Recommendation, adopted in November 2021, is the first global standard on AI ethics. It is binding on the 194 Member States and is anchored on four core values, ten operational principles, and eleven policy action areas. The Model UNESCO takes the Recommendation as its working text. Every draft resolution tabled in any committee must cite the Recommendation by paragraph number. A resolution that does not cite the Recommendation is out of order. This is the rule that makes the Model UNESCO different from a generic MUN: the substance of the debate is the substantive text of an actual international instrument.

The Model UNESCO follows a simplified but faithful version of THIMUN procedure. Speakers speak from a published list. Points of order, points of information, and points of personal privilege are recognised by the Bureau. Draft resolutions are tabled clause by clause. Amendments are voted on in reverse order. A simple majority suffices for procedural votes. A two-thirds majority is required for substantive votes on the final Resolution. The timer is visible to every delegate. The clock governs the day.

 

Committees

  • Data Governance: data trusts, biometric mass surveillance, and the boundaries of informed consent

    50 seats · Intermediate · English
    The Recommendation Anchor is §32 through §35, covering the right to privacy, the conditions under which data may be collected and used to train AI systems, the responsibility of AI actors, and the establishment of adequate data-protection frameworks. The committee debates community-owned data trusts, the legality of biometric mass surveillance under international human rights law, and the age of consent for adolescents interacting with AI services.

    Data Governance: data trusts, biometric mass surveillance, and the boundaries of informed consent

    50 seats · Intermediate · English

    About the committee

    The Recommendation Anchor is §32 through §35, covering the right to privacy, the conditions under which data may be collected and used to train AI systems, the responsibility of AI actors, and the establishment of adequate data-protection frameworks. The committee debates community-owned data trusts, the legality of biometric mass surveillance under international human rights law, and the age of consent for adolescents interacting with AI services.

    Countries

  • Environment and Ecosystems: mandatory environmental impact assessment for frontier AI

    51 seats · Expert · English
    The Recommendation Anchor is §17 and §18, the two paragraphs on environment and ecosystem flourishing and the obligation to reduce the environmental impact of AI systems, including their carbon footprint. The committee debates whether frontier AI model training should be subject to a binding environmental impact assessment, what such an assessment should measure, and whether a global fund should be established to finance green-compute infrastructure in the Global South.

    Environment and Ecosystems: mandatory environmental impact assessment for frontier AI

    51 seats · Expert · English

    About the committee

    The Recommendation Anchor is §17 and §18, the two paragraphs on environment and ecosystem flourishing and the obligation to reduce the environmental impact of AI systems, including their carbon footprint. The committee debates whether frontier AI model training should be subject to a binding environmental impact assessment, what such an assessment should measure, and whether a global fund should be established to finance green-compute infrastructure in the Global South.

    Countries

  • Gender Equality: closing the gendered AI divide, from literacy to leadership

    52 seats · Intermediate · English

    Gender Equality: closing the gendered AI divide, from literacy to leadership

    52 seats · Intermediate · English

    Countries

  • Education and Research: Operationalising AI literacy in low-bandwidth settings

    50 seats · Beginner · English
    The Recommendation Anchor is §41 through §43, the three paragraphs on awareness and literacy, public understanding of AI, and AI ethics training. The committee debates the design of mother-tongue AI literacy curricula for low-bandwidth schools, the role of teachers as ethical-impact-assessment facilitators, and the question of how research universities in the Global South can participate in the global AI ethics discourse.

    Education and Research: Operationalising AI literacy in low-bandwidth settings

    50 seats · Beginner · English

    About the committee

    The Recommendation Anchor is §41 through §43, the three paragraphs on awareness and literacy, public understanding of AI, and AI ethics training. The committee debates the design of mother-tongue AI literacy curricula for low-bandwidth schools, the role of teachers as ethical-impact-assessment facilitators, and the question of how research universities in the Global South can participate in the global AI ethics discourse.

    Countries

Organizers

Nishchal Baniya
Chairman, Board of Directors at Bagmati UNESCO Club

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