Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation

Díaz-Rodríguez, Natalia; Ser, Javier Del; Coeckelbergh, Mark; Prado, Marcos López de; Herrera‐Viedma, Enrique; Herrera, Francisco

doi:10.1016/j.inffus.2023.101896

articleInformation FusionJun 24, 2023HYBRID OA

Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation

NDNatalia Díaz-Rodríguez JDJavier Del Ser MCMark Coeckelbergh MLMarcos López de Prado EHEnrique Herrera‐Viedma

Universidad de Granada · Instituto Andaluz de Ciencias de la Tierra · +5 more institutions

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Abstract

Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system’s entire life cycle: it should be (1) lawful, (2) ethical, and (3) robust, both from a technical and a social perspective. However, attaining truly trustworthy AI concerns a wider vision that comprises the trustworthiness of all processes and actors that are part of the system’s life cycle, and considers previous aspects from different lenses. A more holistic vision contemplates four essential axes: the global principles for ethical use and development of AI-based systems, a philosophical take on AI ethics, a risk-based approach to AI regulation, and the…

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644

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Topics & keywords

Topics

Keywords

Trustworthiness
Key (lock)
Computer science
Artificial intelligence
Computer security
Engineering ethics
Engineering

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