Anna Johnson
As precision agriculture technology advances, privacy concerns plague farmers who fear that their agricultural data could be exploited by data processors. Despite these concerns, the federal government has failed to enact agricultural data protection laws. With the rise of machine learning (ML), federal and state legislators should act urgently to prohibit AI-driven, farming data misuse. Since data security threats in agriculture can disrupt the stability of the commodities market, a coordinated, industry-specific approach ensuring the privacy of agricultural data must be taken. This paper analyzes the privacy risks created by ML in precision agriculture and proposes legislative and regulatory solutions.