AI predicts tiger attacks by learning from Nepali herders
Source: Conservation news
Nepal's tiger conservation program pairs machine learning with decades of accumulated knowledge from indigenous herders—people who understand seasonal patterns, animal behavior, and landscape vulnerabilities that satellite data alone cannot capture. The system treats local expertise as primary training data, which improves prediction accuracy while keeping decision-making authority with the communities bearing the actual risk. This inverts typical AI deployment in conservation: rather than imposing algorithmic solutions, the technology integrates with existing knowledge. The constraint was never computing power but systematic connection between Western monitoring infrastructure and the experiential knowledge already embedded in affected villages.