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It is suggested that voting-based alignment cannot deliver fair or transparent AI by aggregation alone; at minimum, each stage of the moral AI elicitation pipeline should be audited and disclosed.
The findings show that workplace AI agent risks do not arise from agents alone; they also depend on how people work with agents and how agents are deployed, which means safer workplaces require not only safer agents but also carefully designed human-AI agent collaboration.
UST-GNN is presented, a unified spatial--topological graph neural network framework that integrates neighbourhood connectivity, heterogeneous urban features, and positional/locational embeddings into a single representation and provides a unified GeoAI analytical pipeline that can be embedded into urban digital twin wo...
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