Big Data: Usage and Application of Big Data in the Human Dimensions of Agricultural and Natural Resources (ANR) - Sarah A. Bush; Carrie N Baker; J.C. Bunch; Lauri Baker; Jamie L. Loizzo; Brian Myers (Journal of International Agricultural and Extension Education, 2025)
When new science and innovations become available, Extension acts as a liaison for making technology understandable and accessible so their stakeholders can reap the benefits. With rapidly expanding technological advancements such as artificial intelligence (AI), it is crucial for social scientists in Extension and agriculture and natural resources (ANR) to understand their role in the dissemination, adoption, and creation of new technologies. While many of the technologies may be AI driven, they require big data to train machines and create algorithms that leverage this information to produce informed decisions and generate predictions for application. While it may be clear how social scientists can assist in evaluation and the creation of innovation-adoption plans, expansion of ANR social scientist data literacy is needed to advance their role in other components of AI development and big data usage. Additionally, exploration of opportunities for big data usage to support ANR social scientist research, extension, and educational practices is needed to continue progressing this work. In this philosophical paper, we aim to provide insight into how social scientists in ANR can use big data to advance, guide, and support their research, extension, and education practices. We will include an overview of big data, types of data, the big data ecosystem, and opportunities and challenges related to using big data. Further, we address the ethical considerations and social implications of big data usage while emphasizing responsible data stewardship and the need for increased data literacy.
Keywords: Big data; social scientists; SDGs