Multiple Transformations in Spatial Intelligence and Their Effects on Social Reconstruction

Spatial Intelligence (SI) is the cornerstone of Artificial Intelligence (AI) development and represents the integrated capability of perceiving, reasoning, and acting within three-dimensional environments. Despite its significance, the geographical community are yet to systematically explore the operational mechanisms of spatial intelligence and its social impacts. Existing research primarily focuses on technological aspects such as digital twins and spatial heterogeneity modeling, while overlooking the profound social transformations that accompany the deployment of SI. As SI applications permeate autonomous driving, embodied robotics, and smart city infrastructure, fundamentally reshaping human-land interaction patterns, this research gap has become increasingly critical. In this study, we employ a cross-disciplinary literature synthesis approach, integrating perspectives from geography, computer science, and social theory to construct a comprehensive analytical framework for examining technological evolution trajectories and their societal impacts. The core objective is to systematically elucidate multidimensional developmental process of SI and reveal its concomitant social restructuring effects. Through a critical analysis of cutting-edge research and empirical cases, we explore how SI evolution fosters novel spatial practices while triggering structural societal challenges. The methodology focuses on integrating literature themes centred around three core capabilities of SI, supplemented by a socio-theoretical analysis of unintended consequences. The study findings reveals three key technological transformations. First, spatial perception has transcended one-dimensional static representation to achieve three-dimensional dynamic understanding. This shift encompasses a transition in representation from linear encoding to voxel/point-cloud-based 3D modeling, a shift in reference frameworks from absolute coordinate systems to dynamic context-aware systems, and a change in cognitive units from isolated objects to spatiotemporal events. Second, spatial reasoning evolved from deterministic rule systems to probabilistic generative models. This transformation includes cognitive mechanisms shifting from formal logic to probabilistic prediction, learning paradigms evolving from supervised training to world-model-based reinforcement learning, and expression forms upgrading from abstract symbolic descriptions to multimodal embodied interactions. Third, spatial action has transcended the stage of situational adaptation and is advancing toward spatial co-creation. This phase is characterized by: the diversification of agents, where human actors collaborate with increasingly autonomous AI actors in shared environments; and a shift from unidirectional reception to bidirectional co-construction in interaction modes, epitomized by the "Industry 5.0" paradigm emphasizing on proactive human-machine collaboration and natural interaction interfaces. However, these technological transformations have generated significant social restructuring. The digital divide is exacerbated by multiple accessibility and usability barriers. Intelligent infrastructure's reliance on high-performance computing widens regional disparities, while the required technical literacy creates an application gap, disproportionately affecting developing regions and marginalized groups. Concurrently, privacy concerns intensify as intelligent infrastructure conducts a massive-scale collection of spatial, behavioral, and biometric data. Furthermore, legal frameworks lag significantly behind the rapid development of smart infrastructure. Defining liability within complex human-machine-human interaction networks proves challenging, and emerging rights issues, such as virtual property and algorithmic agency, remain unresolved, as evidenced by protracted litigation over autonomous vehicle accidents. In summary, we posit that smart infrastructure development faces a dual imperative: enhancing technical capabilities and proactively addressing socio-ethical challenges. We propose a responsive intelligent infrastructure framework that integrates value-sensitive design with contextual ethical reasoning and embeds geoethics and spatial justice as core design principles. Future development should prioritize interdisciplinary integration with psychology and sociology, shifting research from "technology-driven" to "problem-driven" approaches, and developing novel architectural systems capable of managing complex, multiscale social ecosystems. This study contributes on three levels: theoretically, it systematically analyzes the social effects of the intelligent society within geographical discourse for the first time; methodologically, it integrates interdisciplinary perspectives to bridge technical and social analysis; practically, it provides actionable insights for policymakers to harness the inclusive potential of intelligent society while mitigating risks, thereby, advancing the "AI for Society" agenda and offering theoretical guidance for intelligent society development.