Exploring Rurality and Biophilia: The Role of AI in Understanding Nature’s Impact
Zhou, University of Illinois Urbana-Champaign
Keywords: Generative AI; Rurality; Human-Environment Interaction; Place Identity
In recent years, the concept of biophilia—the idea that humans have an innate connection to nature—has gained significant attention (Wilson,1984; Kellert et al., 1993). More and more studies highlight the benefits of human-nature interactions, ranging from improved mental health to increased productivity. But while we know these interactions are beneficial, quantifying them and understanding how they vary across different environments remains a challenge. Could AI provide the answer?
Two recent studies—one by Jang et al. (2024) and another by Duarte et al. (2024)—offer fascinating new perspectives on how we can study biophilia and its effects. Both explore the relationship between people and nature, but each takes a slightly different approach and context. While Jang et al. focused on capturing the "place identity" of cities using generative AI, Duarte et al. applied AI tools to measure biophilic perceptions in urban environments. Together, these studies offer a powerful blueprint for how AI could transform our understanding of biophilia in both urban and rural settings.
So, what do these studies mean for rural environments? While Jang et al. (2024) and Duarte et al. (2024) focused on urban areas, their findings have the potential to be applied to rural environments as well, where the connection to nature is often more direct and pronounced. Rural landscapes are typically less dominated by the built environment than cities, offering a different kind of biophilic experience. The vast, open fields, forests, rivers, and mountains in rural areas might evoke even stronger feelings of connection to nature, but they may also pose challenges for quantification. Unlike cities, where urban features are more standardized and easily identifiable, rural areas vary greatly depending on the region, culture, and geography. The experience of nature in rural settings is deeply personal and often intertwined with local traditions, livelihoods, and environments.
Do rural areas have a collective identity? I asked ChatGPT to generate a collage representing the concept of "rurality," based on Christy Hyman's summary (2023) of the term from a Google search (Figure 1). The collage represents the diverse aspects of rural life, highlighting both its physical and cultural landscapes. It features small population centers with scattered homes, surrounded by vast natural areas, symbolizing the low population density typical of rural settings. Prominent natural elements, such as rolling hills, fields, and forests, emphasize the deep connection to nature. Other sections of the collage showcase essential services like a small general store and clinic, alongside affordable living spaces and the rural economy's reliance on farming and ranching. It also touches on the economic challenges rural areas face, including aging infrastructure and lower wages, as well as the demographic reality of an aging population in many rural communities.
While the application of AI to study biophilia in both urban and rural contexts offers exciting potential, there are several critical considerations, particularly when it comes to rural environments, which have long been neglected in many research areas. From the perspective of a researcher in rural and agricultural geography, as well as biogeography, there is concern that working landscapes and remote communities outside metropolitan areas may be overlooked in the GeoAI trend due to limited data and attention (Nagavi et al., 2024). Typically, crowdsourced data, such as social media and volunteered geographic information, as well as tools like street view imagery, tend to favor urban and affluent areas, often neglecting rural or economically disadvantaged regions (Kruspe and Stillman 2024).This lack of focus could potentially lead to further displacement and isolation, though the extent of these impacts remains uncertain. At the same time, GeoAI also presents opportunities to improve data accessibility and facilitate data collection from previously remote and isolated areas.The lack of sufficient data and limited research interest in rural areas, often due to the absence of key stakeholders or funding, means that AI models may not fully capture the diverse geographies, cultures, and practices of rural communities. This can hinder the ability of AI to accurately represent the nuanced relationship between people in rural areas and nature. Additionally, the digital divide in rural regions, where access to technology is often limited, could result in certain populations being underrepresented in AI-based studies, further skewing the results.
Furthermore, while AI-generated insights can provide valuable data on biophilic perceptions, they may lack the depth and richness derived from lived experiences and cultural context. Rural identity is shaped by local traditions, economic conditions, and historical factors, which AI may not fully capture. There are also ethical concerns around over-relying on AI in fields like urban planning and environmental management, where human judgment, local knowledge, and community engagement are vital for developing solutions that truly address the needs of rural communities. However, initiatives like the Just Rural Futures blog series pave the way for greater engagement, encouraging scholars from rural geography and other disciplines to contribute their insights. In this way, we can ensure that rural areas receive more attention in research, leading to a more holistic and inclusive understanding of rural environments and identities.
— Zhijie “ZJ“ Zhou
Author’s Bio
Connect with us at:
Thanks for reading Just Rural Futures! Subscribe for free to receive new posts and support my work.