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Within the debate on AI’s benefits and risks for medical research, trustworthiness has been defined as a central guiding principle. From an ELSI (Ethical, Legal, Societal Implications) perspective, trustworthy AI requires acknowledging the complex interplay between technical, ethical, legal, social, and societal factors in AI development and deployment. To advance this perspective, this book chapter adopts an interdisciplinary approach that integrates and synergizes perspectives from social sciences, philosophy, ethics, and law. The first section discusses the importance of societal aspects like transparency and bias mitigation in developing trustworthy AI systems in healthcare, to ensure accuracy and fairness in decision-making and outcomes. The second section, which deals with legal aspects of trustworthy AI, is divided into three parts which (1) explore the EU’s proposed AI Act, (2) discusses the relationship between the AI Act and data protection regulations, and (3) showcases the significance of data governance in the context of the AI Act, highlighting the regulation’s key approaches and the implications for AI development in healthcare services within European projects like EuCanImage, INCISIVE, CHAIMELEON, and EUCAIM. Finally, the last section highlights how ethical aspects linked to ethical approval procedures are context-dependent and do not adhere to a one-size-fits-all logic by presenting the specific case study of the project INCISIVE.

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Societal, Legal, and Ethical Aspects of Trustworthy AI

  • 章节

  • 发表日期：

    2025年

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  • Mónica Cano Abadía,
  • Melanie Goisauf,
  • Iman Hesso,
  • Reem Kayyali,
  • Magdalena Kogut-Czarkowska,
  • Ricard Martínez,
  • Pilar Nicolás Jiménez

摘要

Within the debate on AI’s benefits and risks for medical research, trustworthiness has been defined as a central guiding principle. From an ELSI (Ethical, Legal, Societal Implications) perspective, trustworthy AI requires acknowledging the complex interplay between technical, ethical, legal, social, and societal factors in AI development and deployment. To advance this perspective, this book chapter adopts an interdisciplinary approach that integrates and synergizes perspectives from social sciences, philosophy, ethics, and law. The first section discusses the importance of societal aspects like transparency and bias mitigation in developing trustworthy AI systems in healthcare, to ensure accuracy and fairness in decision-making and outcomes. The second section, which deals with legal aspects of trustworthy AI, is divided into three parts which (1) explore the EU’s proposed AI Act, (2) discusses the relationship between the AI Act and data protection regulations, and (3) showcases the significance of data governance in the context of the AI Act, highlighting the regulation’s key approaches and the implications for AI development in healthcare services within European projects like EuCanImage, INCISIVE, CHAIMELEON, and EUCAIM. Finally, the last section highlights how ethical aspects linked to ethical approval procedures are context-dependent and do not adhere to a one-size-fits-all logic by presenting the specific case study of the project INCISIVE.