Cultivating Confusion: How AI Research is Misguidedly Transforming Agricultural Innovation
Years ago, the editor of a prominent U.S. agricultural journal showed me a manuscript he intended to reject solely because it focused on applications of "artificial neural networks" in agriculture. He expressed weariness at the influx of such papers, particularly from researchers in developing countries. At that time, machine learning research was virtually nonexistent within our department. Ironically, I recently received a manuscript on the same topic for review, co-authored by the same individual. Today, a significant portion of the research papers I review in agriculture focus on the applications of machine or deep learning. However, a notable shift has emerged: a substantial increase in submissions from computer scientists or electrical engineers. While I acknowledge their enthusiasm, I often find these papers lack a deep understanding of the unique challenges and complexities of the agricultural domain. It's perplexing to me how researchers with primary expertise in...