Trustworthy Artificial Intelligence (TAI) systems have become a priority for the European Union and have increased worldwide importance. The European Commission has consulted a High-Level Expert Group that has delivered a document on Ethics Guidelines for Trustworthy AI to promote Trustworthy AI principles. TAI has three overarching 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 TAI. Ideally, all three elements work in harmony and overlap in their operation. If, in practice, tensions arise between these components, society should endeavor to align them. From a practical standpoint, these foundational principles manifest into various TAI dimensions, encompassing robustness, reproducibility, safety, transparency, explainability, diversity, non-discrimination, fairness, auditing, independent oversight, privacy, data governance, sustainability, and accountability.

Calegari, R., Giannotti, F., Milano, M., Pratesi, F. (2025). Introduction. New York, NY, USA : ACM [10.1145/3711127].

Introduction

Calegari R.;Milano M.;
2025

Abstract

Trustworthy Artificial Intelligence (TAI) systems have become a priority for the European Union and have increased worldwide importance. The European Commission has consulted a High-Level Expert Group that has delivered a document on Ethics Guidelines for Trustworthy AI to promote Trustworthy AI principles. TAI has three overarching 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 TAI. Ideally, all three elements work in harmony and overlap in their operation. If, in practice, tensions arise between these components, society should endeavor to align them. From a practical standpoint, these foundational principles manifest into various TAI dimensions, encompassing robustness, reproducibility, safety, transparency, explainability, diversity, non-discrimination, fairness, auditing, independent oversight, privacy, data governance, sustainability, and accountability.
2025
Special Issue on Trustworthy Artificial Intelligence (Part II)
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Calegari, R., Giannotti, F., Milano, M., Pratesi, F. (2025). Introduction. New York, NY, USA : ACM [10.1145/3711127].
Calegari, R.; Giannotti, F.; Milano, M.; Pratesi, F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1018917
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