17 pages, British Columbia’s food system is experiencing an emerging trend in the digitalization of agriculture, which will impact agricultural practices in the province. The rapid growth of this field has created a niche for training and education in digital agriculture and more specifically, in areas such as robotics, artificial intelligence, big data analytics, and computing. However, it remains unclear whether current educators and trainers in British Columbia are communicating both the benefits and risks of digital agriculture, and the need for an inclusive and equitable approach to digital agriculture. To understand the emerging education and training landscape in digital agricultural technologies, this exploratory study engaged in a key informant interview with 12 participants, including educators, relevant government staff, and private training consultants/practitioners in the food and agricultural sector in British Columbia. The small sample is reflective of the nascent nature of this area of research, which seeks to better understand digital agriculture from the perspectives of agricultural educators and trainers both in the public and private sectors. The study found that there is currently a lack of consideration for equity and food sovereignty in digital agricultural training and education. This is primarily due to a gap in engagement with the social aspects of digital agriculture. Without engaging critical social scientists and critical data studies, digital agriculture education, and training may be conducted in ways that do not promote responsible and ethical innovation, and are therefore counterproductive to the development of a just and sustainable food system.
6 pages, Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better tools and solutions to help address some of the world’s most pressing challenges, and deliver positive social impact in accordance with the priorities outlined in the United Nations’ 17 Sustainable Development Goals (SDGs). The AI for Social Good (AI4SG) movement aims to establish interdisciplinary partnerships centered around AI applications towards SDGs. We provide a set of guidelines for establishing successful long-term collaborations between AI researchers and application-domain experts, relate them to existing AI4SG projects and identify key opportunities for future AI applications targeted towards social good.
