The rapid advancement of artificial intelligence (AI) technologies has permeated nearly every sector, and forestry is no exception. While AI promises to revolutionize forest management and conservation through enhanced data processing and predictive capabilities, forestry professionals are approaching this technological wave with a mixture of anticipation and caution. The integration of AI tools in forestry holds immense potential but also raises critical questions about reliability, transparency, and ethical application, especially where decisions affecting ecosystems and communities are concerned.
A groundbreaking study conducted by faculty members at Northern Arizona University’s School of Forestry—Alark Saxena, Luke Ritter, and Derek Uhey—delves deep into the attitudes and experiences of forestry professionals interacting with AI. Their research emerged from a notable gap in the scientific discourse: while much has been discussed about AI’s theoretical benefits, little was known about how practitioners on the ground perceive these emerging technologies. By conducting 20 in-depth interviews across sectors including academia, government agencies, and private industry in the southwestern United States, the researchers have illuminated the nuanced ways AI is reshaping forestry work.
Forestry, a domain reliant on intricate ecological knowledge and long-term stewardship, presents a complex landscape for AI application. The study’s participants uniformly expressed that AI should serve as an augmentation tool for human expertise, not a replacement. Central to their concern is the notorious “black box” problem intrinsic to many AI systems: opaque decision-making processes that make it difficult to trace how conclusions are reached. This opacity threatens accountability, which is paramount when managing delicate forest ecosystems or enacting policies that influence biodiversity, wildfire management, and timber harvesting.
One profound risk highlighted by the foresters lies in the quality and bias of data used to train AI models. Poorly curated datasets or those reflecting historical biases can lead to flawed AI outputs with far-reaching consequences. For instance, an AI system making land management recommendations based on skewed data might inappropriately designate areas for prescribed burns or logging, inadvertently jeopardizing both environmental health and community safety. This risk underscores the critical need for rigorous data validation protocols and human oversight in the deployment of AI in forestry contexts.
Despite reservations about decision-making automation, the experts interviewed welcomed the prospect of leveraging AI to alleviate labor-intensive and repetitive tasks. Forestry professionals are often stretched thin, managing vast territories under tight budgets and timelines. AI can offer substantial support by automating routine paperwork, synthesizing large volumes of textual information, and even aiding in educational planning. Such applications not only improve efficiency but could potentially enhance job satisfaction and reduce burnout in this physically and mentally demanding field.
Moreover, participants expressed excitement about AI’s capabilities in complex data analysis, particularly when paired with advanced remote sensing technologies such as light detection and ranging (LiDAR). LiDAR generates high-resolution, three-dimensional data about forest structures, terrain, and biomass. However, translating this deluge of raw data into actionable insights requires sophisticated analytics. AI-driven pattern recognition and predictive modeling can unearth trends invisible to the naked eye, informing everything from wildfire risk assessments to habitat conservation strategies. The key, however, is that these AI tools function as decision-support systems, offering evidence-based recommendations rather than autonomous rulings.
The study’s authors emphasize that ongoing dialogue about AI is essential within forestry education and professional development. As AI evolves rapidly, it is imperative for foresters to understand not just how to use AI tools but also the underlying algorithms, strengths, and limitations of these technologies. Bridging this knowledge gap will empower forestry professionals to critically evaluate AI outputs and advocate for transparent, ethical AI development that aligns with ecological and social values.
Forestry professionals also underscored the importance of multidisciplinary collaboration in shaping AI’s future role. Integrating insights from computer scientists, ecologists, policy makers, and frontline workers can foster AI designs that are not only technically robust but socially responsible. Such partnerships could help establish best practices and regulatory frameworks that ensure AI aids sustainable forest management without compromising accountability.
The fear of AI’s misuse in shaping forest policy was profound and widespread among interviewees. Incorrect or biased AI recommendations could inadvertently lead to regulatory capture, where powerful interests manipulate AI outputs to justify harmful practices like unchecked clear-cutting or neglecting fire prevention efforts. Transparent AI models with explainable algorithms and open datasets will be critical in preventing such abuse, preserving trust between forest managers, policy makers, and the public.
Looking forward, the researchers call for expanded studies involving a broader geographic and institutional range of forestry stakeholders. Capturing diverse perspectives will enrich our collective understanding and help devise nuanced policies that address both the opportunities and ethical challenges AI presents. In particular, incorporating voices from Indigenous communities and international forestry practitioners could yield vital insights, given their distinct relationships with land and technology.
The study’s findings argue persuasively that AI’s successful implementation in forestry hinges on balancing technological innovation with human values and ecological wisdom. Far from heralding a replacement of expert judgment, AI ought to be embraced as a powerful ally, enabling foresters to process overwhelming information, tackle unprecedented challenges such as wildfires and climate change, and ultimately preserve forest ecosystems for future generations.
In sum, the integration of AI in forestry is a double-edged sword—potentially transformative yet fraught with pitfalls. By fostering open dialogue, emphasizing transparency, and championing education, the forestry community can navigate this complex terrain. This foundational research by Saxena, Ritter, and Uhey lays the groundwork for a cautious but optimistic embrace of AI, ensuring it serves as a bridge to more sustainable and informed forest management rather than an opaque authority supplanting human responsibility.
Subject of Research: Not applicable
Article Title: Knowledge, attitudes, and practices of forestry professionals towards artificial intelligence (AI)☆
News Publication Date: 1-Oct-2025
Web References: https://www.sciencedirect.com/science/article/abs/pii/S1389934125002059?via%3Dihub
References: 10.1016/j.forpol.2025.103626
Keywords: Forestry, Deforestation, Logging, Artificial intelligence, Generative AI, Machine learning, Forest fires, Forest ecosystems
