The Algorithm, the Farmer and the Agronomist: Who is Smart in Smart Farming?

The concept of “Smart Farming,” which evolved from “precision agriculture,” has recently emerged as a new paradigm in agriculture. This approach leverages digital technologies—including artificial intelligence, Big Data, and the Internet of Things—to address a key challenge facing modern agriculture: the need to simultaneously increase productivity and reduce environmental impact. Smart Farming aims to transition from process-driven to data-driven agriculture. However, the sheer volume of data generated and the reliance on algorithmic processing, such as the use of machine learning algorithms, raise concerns about the potential erosion of farmers’ decision-making authority. Decision-support tools risk evolving into autonomous decision-makers. For agronomists, the overwhelming influx of data not only threatens to render traditional scientific approaches obsolete but also endangers the very foundation of agronomic science. Consequently, this article poses a critical question: who truly embodies the “smart” in Smart Farming? Is it the farmer, the agronomist, or the digital technologies driving this transformation? By exploring this question, the article delves into the epistemic challenges posed by Smart Farming.