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Climate action includes a variety of efforts to address climate change and its impacts. The achievement of collective agreement by the public to engage in climate actions presents complexity, as it is influenced by political, ideological, and economic factors and faces resistance from powerful industries . With the progression of digitalisation , large amounts of user-generated data are available, opening new pathways to understand human behaviour in relation to climate action using artificial intelligence (AI). Integrating human knowledge and perception into AI systems via human-in-the-loop (HITL) frameworks can improve contextualised decision-making while mitigating biases. This review explores how HITL design can support AI for climate action at both micro- and macro-scale, especially synthesising instances where HITL systems provide a pathway for ethical alignment, integrating diverse human perspectives to ensure that AI-driven climate solutions respect cultural and social values.
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Stored only when both papers are in the corpus — 12 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.