Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation
Соединяя точки в сфере заслуживающего доверия искусственного интеллекта: от принципов ИИ, этики и ключевых требований к ответственным системам ИИ и регулированию
2023-06-24
SCID: 54.1/t92vgk8b
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AI auditingAI ethicsAI regulationResponsible AI systemsTrustworthy Artificial Intelligence
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Abstract (AI)
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 mentioned pillars and requirements. The seven requirements (human agency and oversight; robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental wellbeing; and accountability) are analyzed from a triple perspective: What each requirement for trustworthy AI is, Why it is needed, and How each requirement can be implemented in practice. On the other hand, a practical approach to implement trustworthy AI systems allows defining the concept of responsibility of AI-based systems facing the law, through a given auditing process. Therefore, a responsible AI system is the resulting notion we introduce in this work, and a concept of utmost necessity that can be realized through auditing processes, subject to the challenges posed by the use of regulatory sandboxes. Our multidisciplinary vision of trustworthy AI culminates in a debate on the diverging views published lately about the future of AI. Our reflections in this matter conclude that regulation is a key for reaching a consensus among these views, and that trustworthy and responsible AI systems will be crucial for the present and future of our society.
Key Findings
1
A holistic trustworthiness framework integrates global AI principles, philosophical ethics, risk-based regulation, and the three pillars with their seven requirements.
2
The authors conclude that regulation is essential for reconciling divergent views about AI’s future and enabling trustworthy, responsible AI systems.
3
The paper introduces responsible AI systems as trustworthy systems whose legal responsibility can be addressed through auditing processes, while acknowledging challenges from regulatory sandboxes.
4
The seven requirements are examined through what they mean, why they are necessary, and how they can be implemented practically.
5
Trustworthy AI is framed around seven technical requirements supported by three pillars: lawfulness, ethics, and technical and social robustness throughout the system life cycle.
Research Object
Trustworthy and responsible AI-based systems (AI systems throughout their life cycle)
Research Subject
the principles, ethical and legal requirements, risk-based regulation, auditing, and implementation of trustworthiness and responsibility in AI systems
Publication Details
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2023-06-24
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