CYAIApr 23, 2020

Responsible AI and Its Stakeholders

arXiv:2004.11434v13 citations
AI Analysis

This work addresses the problem of responsibility gaps in AI deployment for policymakers, developers, and society, but it is incremental as it builds on existing Responsible AI frameworks.

The paper tackles the problem of assigning responsibility in AI systems by proposing a framework that includes AI itself as a stakeholder, aiming to address legal and moral gaps in autonomous and self-learning systems. It discusses three notions of responsibility—blameworthiness, accountability, and liability—for all stakeholders, including AI, and suggests roles for jurisdiction and the public.

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 se, which could close some legal and moral gaps concerning the deployment of autonomous and self-learning systems. We discuss three notions of responsibility (i.e., blameworthiness, accountability, and liability) for all stakeholders, including AI, and suggest the roles of jurisdiction and the general public in this matter.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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