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An Analysis of Dubai’s New Human-Machine Collaboration Classification System

 |  August 13, 2025

By: Shabnam Karim, Marcus Evans, Shiv Daddar, Simon Lamb, Elizabeth Yong & Rosie Nance (Norton Rose Fulbright)

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    In this article, authors Shabnam Karim, Marcus Evans, Shiv Daddar, Simon Lamb, Elizabeth Yong & Rosie Nance (Norton Rose Fulbright) describe the launch of Dubai’s “Human-Machine Collaboration Icons” initiative, a first-of-its-kind classification system requiring certain entities to disclose the extent of AI and machine involvement in the creation of research, publications, and content. Announced on 16 July 2025 by His Highness Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, the system uses standardized visual icons to represent different levels of human-machine collaboration. The goal is to promote transparency, credibility, and clarity at a time when the line between human and machine-generated work is becoming increasingly blurred.

    The framework, developed by the Dubai Future Foundation (DFF), will be mandatory for all Dubai government entities and organizations working with them, while other institutions may adopt it voluntarily. It includes two categories of icons: primary icons, which indicate the overall level of collaboration (ranging from “All Human” to “All Machine”), and secondary icons, which specify the stages of content creation—such as ideation, data analysis, writing, or design—where human-machine collaboration occurred. The system is intentionally flexible and does not attempt to quantify exact percentages of machine involvement, recognizing the difficulty of standardizing such assessments across varied creative and research processes.

    The classification applies to a wide range of intellectual and creative outputs, from academic papers and technical documentation to visual content, educational materials, and art. By using the term “human-machine” rather than “artificial intelligence,” the DFF framework allows for broader applicability to future forms of automation and robotics. Further decree-laws and regulatory guidance are expected to clarify implementation and compliance requirements, though it remains uncertain whether penalties will be introduced for entities that fail to disclose—or inaccurately disclose—their use of machine assistance.

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