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Forget top-down AI deployment: this study shows how a community-led approach to AI-powered wildfire risk assessment can build trust and drive adoption by prioritizing local context and user experience.
MLLMs, despite their video understanding prowess, exhibit a surprisingly strong "better safe than sorry" bias when detecting anomalies in video, crippling their recall in real-world surveillance scenarios.
