Oct 2026· Land· Vol 15, pp. 1850· 0 citations· 63 references
Abstract
Artificial intelligence (AI) is increasingly embedded in land governance, reshaping how environmental pressures and sustainability goals are addressed. Yet the institutional processes through which human–AI collaboration takes shape remain largely unexplored. This study examines whether human–AI collaboration is emerging as a new governance paradigm in China’s land sector, and if so, through what institutional pathways and practical forms it is being articulated and implemented. Drawing on a systematic analysis of 352 policy documents and case studies from coastal regions, the study develops and applies the CTI framework—an analytical lens that integrates Contextual conditions, Technological capabilities, and Institutional arrangements. The findings reveal three interrelated developments: (1) policy discourse constructs a coherent narrative in which environmental pressures and digital transformation jointly create an imperative for change; (2) a systematic division of labor between AI and human officials emerges in policy and is reflected in practice, with AI handling data processing and preliminary screening while humans retain final decision-making, value judgment, and accountability; and (3) this division is being institutionalized through a staged process of policy guidance, pilot mechanisms, and institutional adaptation. These developments suggest that human–AI collaboration may be taking shape as an emerging governance paradigm in land governance, one that is beginning to be codified and tested in policy and practice. The study contributes an integrative analytical framework, specifies the logic of human–machine division of labor, and extends collaborative governance theory beyond its traditional human-centric assumptions. The findings also carry implications for governance contexts where human–AI collaboration is reshaping land governance and other policy domains.
This study contributes the first comprehensive human-centered AI governance framework specifically tailored to the Southeast Asian context, providing actionable guidance for policymakers navigating complex tradeoffs between technological advancement, human rights protection, and equitable development.
A. Apriansyah, Faqih Wildan Hakim, Ridwansyah· Proceeding of International...· 0 citations
The SLR demonstrates that effective AI and digital platform governance demands a holistic, context-sensitive approach that actively balances efficiency with justice, innovation with accountability, and risk with public value.
This paper explores how AI risk governance can be effectively integrated into the epistemological and structural foundations of such organizations through the lens of fourth-order cybernetics, and offers a conceptual pathway for resilient and ethically aligned AI implementation in complex organizational environments.
Ludmila Jiříčková, Petr Doucek· International Scientific Con...· 0 citations
This study examines the theoretical and empirical challenges that AI governance poses
for the fields of organization studies and human resource management (HRM) and proposes
directions for future research. As AI technologies rapidly diffuse across organizations, AI
governance has emerged as a critical managerial con...
Sungjun Kim, Joonghak Lee· Korean Academy of Organizati...· 0 citations
The EMF demonstrates that an AI mirror as reported by Vallor can function as a developmental instrument: relationally grounded engagement oriented toward resonance, rather than replacement, can deepen discernment and strengthen sovereign decision-making rather than producing moral deskilling.
Arulnageswaran Aruleswaran, Thaatchaayini Kananatu· AI and Ethics· 1 citation
This study proposes Cognitive Governance Systems (CGS) Theory as an original explanatory framework of the interaction between human intelligence and machine intelligence in a co-decision making context of democratic government.
K. Kunwar· Journal of Advances in Socia...· 0 citations
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