A number of research trends are informing insights in this field. It is also important to be cognizant of any unintended consequences of leveraging AI in these fields, such as problems of bias that algorithmic approaches can introduce, replicate, and/or exacerbate in complex social systems. AI can play an important, and in some cases crucial, role in these areas to motivate and help people take actions that maximize welfare.
In decision-making domains as wide-ranging as medication adherence, vaccination uptake, college enrollment, financial savings, and energy consumption, behavioral interventions have been shown to encourage people towards making better choices. Girish Chowdhary (University of Illinois, Urbana Champaign), Baskar Ganapathysubramanian (Iowa State University contact: George Kantor (Carnegie Mellon University), Soumik Sarkar (Iowa State University), Sierra Young (North Carolina State University), Ananth Kalyanaraman (Washington State University), Ilias Tagkopoulos (UC Davis). Papers will be peer-reviewed and selected for spotlight and/or poster presentation.
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All papers must be submitted in PDF format using the AAAI-23 author kit. Submitted technical papers can be up to 4 pages long (excluding references and appendices). Attendance is open to all registered participants. The workshop will be a one-day meeting comprising invited talks from researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work. Development of open-source software, libraries, annotation tools, or benchmark datasets.Precision agriculture and farm management.Specific topics of interest for the workshop include (but are not limited to) foundational and
Outcomes include outlining the main research challenges in this area, potential future directions, and cross-pollination between AI researchers and domain experts in agriculture and food systems. This AAAI workshop aims to bring together researchers from core AI/ML, robotics, sensing, cyber physical systems, agriculture engineering, plant sciences, genetics, and bioinformatics communities to facilitate the increasingly synergistic intersection of AI/ML with agriculture and food systems. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. By the end of this century, the earth’s population is projected to increase by 45% with available arable land decreasing by 20% coupled with changes in what crops these arable lands can best support this creates the urgent need to enhance agricultural productivity by 70% before 2050. An increasing world population, coupled with finite arable land, changing diets, and the growing expense of agricultural inputs, is poised to stretch our agricultural systems to their limits.
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