相关论文: Using Case Studies to Teach Responsible AI to Indu…

Responsible design of AI systems is a shared goal across HCI and AI communities. Responsible AI (RAI) tools have been developed to support practitioners to identify, assess, and mitigate ethical issues during AI development. These tools…

As Artificial Intelligence (AI) becomes integral to business operations, integrating Responsible AI (RAI) within Environmental, Social, and Governance (ESG) frameworks is essential for ethical and sustainable AI deployment. This study…

Responsible AI (rAI) guidance increasingly promotes stakeholder involvement (SHI) during AI development. At the same time, SHI is already common in commercial software development, but with potentially different foci. This study clarifies…

Responsible Artificial Intelligence (RAI) is a combination of ethics associated with the usage of artificial intelligence aligned with the common and standard frameworks. This survey paper extensively discusses the global and national…

Responsible AI (RAI) is the science and practice of ensuring the design, development, use, and oversight of AI are socially sustainable--benefiting diverse stakeholders while controlling the risks. Achieving this goal requires active…

Responsible AI (RAI) has emerged as a major focus across industry, policymaking, and academia, aiming to mitigate the risks and maximize the benefits of AI, both on an organizational and societal level. This study explores the global state…

Scientific research organizations that are developing and deploying Artificial Intelligence (AI) systems are at the intersection of technological progress and ethical considerations. The push for Responsible AI (RAI) in such institutions…

Responsible artificial intelligence (RAI) is increasingly recognized as a critical concern. However, the level of corporate RAI prioritization has not kept pace. In this work, we conduct 16 semi-structured interviews with practitioners to…

Responsible AI principles provide ethical guidelines for developing AI systems, yet their practical implementation in software engineering lacks thorough investigation. Therefore, this study explores the practices and challenges faced by…

Responsible Artificial Intelligence (RAI) addresses the ethical and regulatory challenges of deploying AI systems in high-risk scenarios. This paper proposes a comprehensive framework for the design of an RAI system (RAIS) that integrates…

The rapid growth of Artificial Intelligence (AI) has underscored the urgent need for responsible AI practices. Despite increasing interest, a comprehensive AI risk assessment toolkit remains lacking. This study introduces our Responsible AI…

Responsible AI (RAI) tools -- checklists, templates, and governance processes -- often engage RAI champions, individuals intrinsically motivated to advocate ethical practices, but fail to reach non-champions, who frequently dismiss them as…

Large and ever-evolving technology companies continue to invest more time and resources to incorporate responsible Artificial Intelligence (AI) into production-ready systems to increase algorithmic accountability. This paper examines and…

The responsible AI (RAI) community has introduced numerous processes and artifacts (e.g., Model Cards, Transparency Notes, Data Cards) to facilitate transparency and support the governance of AI systems. While originally designed to…

Several recent works have studied the societal effects of AI; these include issues such as fairness, robustness, and safety. In many of these objectives, a learner seeks to minimize its worst-case loss over a set of predefined distributions…

In the last years, the raise of Artificial Intelligence (AI), and its pervasiveness in our lives, has sparked a flourishing debate about the ethical principles that should lead its implementation and use in society. Driven by these…

As artificial intelligence transforms a wide range of sectors and drives innovation, it also introduces complex challenges concerning ethics, transparency, bias, and fairness. The imperative for integrating Responsible AI (RAI) principles…

The rapid development of artificial intelligence (AI) has led to increasing concerns about the capability of AI systems to make decisions and behave responsibly. Responsible AI (RAI) refers to the development and use of AI systems that…

Responsible Artificial Intelligence (AI) proposes a framework that holds all stakeholders involved in the development of AI to be responsible for their systems. It, however, fails to accommodate the possibility of holding AI responsible per…

This study investigates the acceptability of different artificial intelligence (AI) applications in education from a multi-stakeholder perspective, including students, teachers, and parents. Acknowledging the transformative potential of AI…