Recipient Organization
MISSISSIPPI STATE UNIV
(N/A)
MISSISSIPPI STATE,MS 39762
Performing Department
(N/A)
Non Technical Summary
A conference on artificial intelligence (AI) in agriculture is planned for March 31-April 2, 2025in Starkville, Mississippi. The conference will focus on "AI In Agriculture: The Role Of AI InAutonomous Agricultural Systems And Socioeconomic Effects" following three successful AIconferences held at Auburn University, the University of Florida, and Texas A&M University,focused on AI in agriculture but with other themes. We seek to expand the focus andparticipation beyond the southeastern U.S., supporting a transdisciplinary community ofresearchers, educators, extension experts and industry from across domains, includingsocioeconomic considerations of AI at various farm scales. Since the last meeting, new research,tools, and challenges associated with AI in Agriculture have accelerated. These are fast movingand evolving areas so communication opportunities to share ideas will increase thecompetitiveness of U.S. agriculture and minimize silos. We expect 300 to 400 attendees fromacross the country as well as over 100 online participants. Local hosts include Texas A&MUniversity, Prairie View A&M University and Texas A&M AgriLife Research. Meetingprogramming is co-organized by Hatch Multi-State project, S1090: AI in Agroecosystems: BigData and Smart Technology-Driven Sustainable Production. The planning committees anddifferent speakers and panelists will come from across domains and geographies. Outputs willinclude presentations, preprints, and a conference report. Outcomes include new areas ofresearch and approaches for teaching and education, in addition to new understanding andcollaborations across domains. Impacts will be made through broadening participation andgrowing communities and their use of AI in agriculture.
Animal Health Component
25%
Research Effort Categories
Basic
75%
Applied
25%
Developmental
(N/A)
Goals / Objectives
This conference will provide an assembly where university faculty and students, industry, and representatives of diverse stakeholder groups will share their expertise, vision, and the cooperative need to develop an AI-driven agriculture. The meeting will address multiple aspects of the USDA agriculture innovation agenda and the USDA strategic plan and target NIFA priorities. Specifically, we can build shared knowledge of our diverse research strengths, develop new networking partnerships, and identify topic areas where innovation, policy change, or outreach are needed. The conference's overall goal is to strengthen knowledge sharing and collaboration among U.S. university faculty and students, industry, and diverse stakeholders for implementing AI technology into U.S. agriculture and natural resources in an efficient, sustainable, and socio-economically equitable manner. The specific objectives of the conference include:1) To bring agricultural and natural resources researchers, industry members, students, representatives from stakeholder groups, and funding agencies together to develop collaborations and explore recent developments and opportunities in AI and automation for solving emerging challenges in agricultural production, food systems, and natural resources.2) To identify AI-driven innovations that are still needed to meet the current and future challenges so U.S. agriculture can remain competitive and profitable while sustaining the environment under a changing climate. Also, to identify barriers to implementing these potential AI-driven innovations.3) To increase knowledge of current agriculture-focused teaching in AI-related initiatives across U.S. universities and strengthen teaching curricula.4) To increase knowledge and skills among undergraduate and graduate students, postdocs, and faculty of the emerging AI techniques available for research and extension.5) To develop transdisciplinary teams for AI projects that address needs and opportunities in agriculture.6) To develop action plans to overcome barriers to developing AI-driven solutions and adopting AI technology in U.S. farm and ranch management systems.7) To identify skills among farmers, consultants, and extension agents necessary to manage the farm of the future.8) To strengthen collaboration among U.S. universities, and NIFA-NSF AI in Agriculture centers, industry, and diverse stakeholder groups to develop the next generation of AI-driventechnologies to support U.S. agriculture.9) To assemble resources and information relevant to funding agencies, university administrators, members of the National Academies of Sciences, Engineering, and Medicine (NASEM), and industry on needs to address current and future challenges of U.S. agriculture. This includes personnel and facilities infrastructure needed to advance innovation.10) To provide a forum where researchers, teachers, extension experts, and industry can publicize their work and findings in AI relevant to agriculture and natural resources.
Project Methods
The conference will include pre-conference workshops for attendees who want toimprove their individual skills with AI. It will include multiple plenary/keynote talks fromexperts in AI. It will include a poster session to enable graduate students from multipleuniversities to present their research and compete for poster awards. It will include multiplethemed breakout sessions in which multiple researchers will make oral presentations of theirresearch. It will also have multiple panel discussions involving experts and stakeholdersregarding AI for autonomous agricultural systems and socioeconomic effects. The conferencewill close with an awards luncheon followed by meetings of the multistate project groups inattendance, which we expect to include S1090 and S1098.As a conference, no new raw data is anticipated beyond demographic data of attendees andpresenters' names, affiliations and contact information. Presenters will submit abstracts withtitles and authors; slideshows; and have their talks livestreamed and recorded.