arXiv:2606.13854v1 Announce Type: cross Abstract: We present SpheriCity, an expert-grounded conversational prototype designed to support trustworthy knowledge sensemaking from sustainability reports. City-level circularity assessment reports contain rich information about materials, infrastructure, and policy interventions, yet their length and heterogeneous structure make cross-document synthesis and comparison difficult for practitioners and researchers working on circular economy initiatives. While large language models (LLM) promise faster knowledge access and synthesis, their opaque reaso
The proliferation of complex sustainability data and the maturing capabilities of large language models create a timely need and opportunity for AI-powered decision support in this domain.
This development signals a growing application of AI in complex analytical tasks beyond traditional business, directly impacting environmental policy and resource management.
The ability to more efficiently synthesize and interpret vast, heterogeneous sustainability reports could accelerate evidence-based decision-making in circular economy initiatives.
- · Environmental policy makers
- · Urban planners
- · Circular economy consultants
- · AI-powered knowledge management platforms
- · Traditional manual data analysis firms
- · Organizations slow to adopt AI tools
Sustainability report analysis becomes significantly faster and more comprehensive through AI.
Improved policy decisions and resource allocation lead to more effective circular economy implementations.
Accelerated global transition to sustainable practices, potentially impacting resource markets and geopolitical dependencies.
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Read at arXiv cs.AI