AI IN AGRICULTURE: INNOVATION AND DISCOVERY TO EQUITABLY MEET PRODUCER NEEDS AND PERCEPTIONS

During a recent meeting in Gainesville, FL, of the Hatch Multi-State project, S1090: AI in Agroecosystems: Big Data and Smart Technology-Driven Sustainable Production, a decision was made to organize a conference to better address social and economic implications of introducing AI technology in the U.S. and further explore technological innovation. This project will support the development of this AI in Ag conference. The overall goal of this project and conference is to strengthen knowledge sharing and collaboration among U.S. university faculty and students, industry, and stakeholders for implementing AI technology in an efficient, sustainable, and socio-economically equitable manner.Specific objectives include:1) Bring agriculture researchers, industry, representatives from stakeholder groups, and funding agencies together to build collaboration by exploring recent developments in AI and automation and explore how they can be used to solve emerging challenges in agricultural production and food systems.2) Identify the AI-driven innovations needed to meet the current and future challenges so Agriculture can remain competitive and profitable while protecting the environment. The barriers to implementing these potential innovations will be also identified.3) Increase knowledge of current agriculture-focused teaching in AI-related initiatives across U.S. universities and strengthen teaching curricula.4) Increase knowledge and skills among graduate students and faculty of the emerging AI techniques available for research and extension.5) Teams formed to develop AI-related projects addressing the needs and opportunities in agriculture.6) Identify action plans to overcome existing barriers to developing AI-driven solutions and adopting AI technology in farm and ranch management systems.7) Identify the skills, among farmers, consultants, and extension agents, necessary to manage the farm of the future.8) Strength collaboration among U.S. universities, industry, and stakeholder groups to develop the next generation of AI-driven technologies that will support U.S. agriculture.9) Gather information to update funding agencies, university administrators, members of National Academies of Sciences, Engineering, and Medicine (NAEM), and industry on the areas that are needed to advance on the current and future challenges of U.S. and SE agriculture. Information will also be provided on the funding as well as the personnel and facilities infrastructure needed to advance innovation across SE universities. After the conference, it will be possible to provide funding agencies with a list of experts and their AI related knowledge areas that could potentially serve on review panels, ad hoc groups, and advisory teams.