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 also includes a regulation debate, with the purpose of serving as an entry point to this crucial field in the present and future progress of our society.

翻译：可信人工智能（Trustworthy AI）基于七项技术要求和三大支柱，这些要素应在系统全生命周期内得到满足：系统应（1）合法、（2）合乎伦理、（3）在技术和社会层面均具有鲁棒性。然而，实现真正可信AI涉及更广泛的愿景，涵盖系统生命周期中所有流程与参与者的可信度，并从不同视角审视前述方面。一种更全面的视角考量了四个核心维度：基于AI系统伦理使用与开发的全球原则、AI伦理的哲学思考、基于风险的AI监管方法，以及前述支柱与要求。七项要求（人类能动性与监督；鲁棒性与安全性；隐私与数据治理；透明度；多样性、非歧视与公平性；社会与环境福祉；问责制）从三重角度分析：每项可信AI要求是什么、为何需要、以及如何在实践中实施。另一方面，实施可信AI系统的实用方法允许通过特定审计流程，定义AI系统面对法律时的责任概念。因此，本文引入的“负责任AI系统”概念，是一种可通过审计流程实现且具有迫切必要性的概念，但面临监管沙盒使用带来的挑战。我们关于可信AI的多学科视角还包含监管讨论，旨在为这一关乎社会当前与未来进步的关键领域提供入门指引。