This Perspective discusses the limitations of current grid data prediction technologies and emphasizes the need for more reliable, interpretable, and data-driven approaches to support the increasing complexity of modern power systems and the ongoing energy transition. More >

The rapid advancement of generative AI has created a critical gap between technological innovation and accountability frameworks. Traditional responsibility mechanisms fail structurally when confronted with AI's black box nature, emergent behaviors, and capacity for autonomous decision-making—characteristics that sever the causal chains upon which legal and ethical liability depends. This Perspective argues that resolving this accountability paradox requires not a single regulatory fix but a distributed responsibility model spanning four interconnected domains: the proactive obligations of technology developers across the AI lifecycle, the paradigm shifts required in legal frameworks inclu... More >