For artificial intelligence (AI)-driven companies, awareness of the urgency of the responsible application of AI became essential with increased interest from different stakeholders. Responsible AI (RAI) has emerged as a practice to guide the design, development, deployment, and use of AI systems to ensure a benefit to users and those impacted by the systems’ outcomes. This benefit is achieved through trustworthy models and strategies that assimilate ethical principles to ensure compliance with regulations and standards for long-term trust. However, RAI comes with the challenge of lack of standardization when it comes to which principles to adopt, what they mean, and how they can be operationalized. This article aims to bridge the gap between principles and practice through a study of different approaches taken in the literature and the proposition of a foundational framework.

中文翻译：

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负责任的人工智能实践的基石：当前形势展望

对于人工智能（AI）驱动的公司来说，随着不同利益相关者兴趣的增加，对负责任地应用人工智能的紧​​迫性的认识变得至关重要。负责任的人工智能（RAI）已成为指导人工智能系统的设计、开发、部署和使用的实践，以确保用户和受系统结果影响的人受益。这种好处是通过值得信赖的模型和策略来实现的，这些模型和策略吸收了道德原则，以确保遵守长期信任的法规和标准。然而，在采用哪些原则、它们的含义以及如何实施这些原则方面，RAI 面临着缺乏标准化的挑战。本文旨在通过研究文献中采用的不同方法并提出基本框架来弥合原则与实践之间的差距。