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Ethics guidelines for trustworthy AI 1.56 MB
Description

The aim of the Guidelines is to promote Trustworthy AI. Trustworthy AI has three components, which should be met throughout the system's entire life cycle: (1) it should be lawful, complying with all applicable laws and regulations (2) it should be ethical, ensuring adherence to ethical principles and values and (3) it should be robust, both from a technical and social perspective since, even with good intentions, AI systems can cause unintentional harm. Each component in itself is necessary but not sufficient for the achievement of Trustworthy AI. Ideally, all three components work in harmony and overlap in their operation. If, in practice, tensions arise between these components, society should endeavour to align them.

These Guidelines set out a framework for achieving Trustworthy AI. The framework does not explicitly deal with Trustworthy AI’s first component (lawful AI). Instead, it aims to offer guidance on the second and third components: fostering and securing ethical and robust AI. Addressed to all stakeholders, these Guidelines seek to go beyond a list of ethical principles, by providing guidance on how such principles can be operationalised in socio-technical systems. Guidance is provided in three layers of abstraction, from the most abstract in Chapter I to the most concrete in Chapter III, closing with examples of opportunities and critical concerns raised by AI systems.

  1. Based on an approach founded on fundamental rights, Chapter I identifies the ethical principles and their correlated values that must be respected in the development, deployment and use of AI systems.
  2. Drawing upon Chapter I, Chapter II provides guidance on how Trustworthy AI can be realised, by listing seven requirements that AI systems should meet. Both technical and non-technical methods can be used for their implementation.
  3. Chapter III provides a concrete and non-exhaustive Trustworthy AI assessment list aimed at operationalising the key requirements set out in Chapter II. This assessment list will need to be tailored to the specific use case of the AI system.
Publication Details
Publication Year:
2019