Bark beetle infestation is an existential threat to California’s forests. From 2010-2019, bark beetles have contributed to the destruction of more than 150 million trees in California. Conventional methods of exterminating bark beetles with insecticides or managing the outbreak with logging and pruning have proven to be ineffective and overall harmful to the ecosystem. A fresh approach is necessary. We propose the use of RNAi (RNA interference) to silence olfactory receptors in beetles. The gene DfOR6 is responsible for expressing olfactory receptors that are critical for the mass aggregation of beetles. Silence that gene and the beetles cannot call upon other beetles to aggregate. We can reliably identify beetle-infested trees in near real-time by using AI (Convolutional Neural Networks) on publicly and commercially available satellite imagery 30 cm to 30 m in spatial resolution. We will use a foliar spray to precisely introduce dsRNA (double-stranded RNA) only on the infested trees and contain the large scale outbreak. We will also develop a GIS-based app to map areas of decreased health that are likely to become epicenters for massive outbreaks which require targeted RNAi therapy. Space, AI, and Synthetic Biology can collectively drive eco-friendly and precise management of bark beetle outbreaks.