Western AI models “fail spectacularly” in farms and forests abroad

AI Summary

Western AI models trained predominantly on Western data are failing to perform effectively in agricultural and forestry applications across the developing world. The tools often cannot recognize local crops, forests, or farming conditions, limiting their practical utility for non-Western users. Experts argue that adaptation to local environments is critical for AI tools to have global impact.

Big Tech’s AI tools trained on Western data often can’t recognize local crops, forests, or farming conditions without adaptation to local environments.