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The development and implementation of Artificial Intelligence (AI) and Machine Learning (ML) systems in the field of official statistics requires an ethical and regulatory approach to ensure the protection of human rights, privacy, and fairness. The 2024 Artificial Intelligence Strategy (Gobierno de España, 2024) emphasizes the importance of responsible AI in guaranteeing that these systems are safe, transparent, and beneficial to society. Given the potential impact of AI, organizations must establish an ethical framework to manage the risks associated with its use. The paper proposes an ethical framework based on international and European principles for AI, such as transparency, impartiality, and human oversight. It also addresses the challenges of AI adoption, including technical competence, infrastructure, and governance. The goal is to ensure that AI-ML systems enhance the quality and efficiency of the production of official statistics, without compromising public trust or ethical standards.

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Ethical Principles for the Production of Official Statistics Using Machine Learning and Artificial Intelligence Techniques

  • 会议论文

  • 发表日期：

    2026年

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  • Jorge-Eusebio Velasco-López,
  • Ramón-Alberto Carrasco,
  • Gema Fernández-Avilés,
  • José-María Montero-Lorenzo

摘要

The development and implementation of Artificial Intelligence (AI) and Machine Learning (ML) systems in the field of official statistics requires an ethical and regulatory approach to ensure the protection of human rights, privacy, and fairness. The 2024 Artificial Intelligence Strategy (Gobierno de España, 2024) emphasizes the importance of responsible AI in guaranteeing that these systems are safe, transparent, and beneficial to society. Given the potential impact of AI, organizations must establish an ethical framework to manage the risks associated with its use. The paper proposes an ethical framework based on international and European principles for AI, such as transparency, impartiality, and human oversight. It also addresses the challenges of AI adoption, including technical competence, infrastructure, and governance. The goal is to ensure that AI-ML systems enhance the quality and efficiency of the production of official statistics, without compromising public trust or ethical standards.