Given the potentially large economic and social impact of AI technological advancement like LLMs, further in-depth thinking is demanded about the ways in which AI exists in cities. In addition to discussions on ethical regulation, there are relatively few cross-cutting studies on how to realize the synergistic development of AI innovation and city, especially taking AI as a complete industry and governance object, under a broader urban and social context. Based on the policy practice of AI development in Shenzhen, this paper proposes a comprehensive framework for the integrated development of AI and the city, which involves the comprehensive consideration of technology systems, application scenarios, educational literacy and governance schemes. Meanwhile, the transformative trend of urban governance triggered by potential general artificial intelligence at a deeper level is further discussed in terms of planning concepts, digital architecture and governance decision-makings. By city AI integration, AI is expected to be better spread into general social activities and, through the driving effect of industrial economy, contribute to the competitiveness and sustainable development of cities.
A City Is Not a Computer: Other Urban Intelligences
<strong>A bold reassessment of "smart cities" that reveals what is lost when we conceive of our urban spaces as computers</strong> Computational models of urbanism—smart cities that use data-driven planning and algorithmic administration—promise to deliver new urban efficiencies and conveniences. Yet these models limit our understanding of what we can know about a city. <i>A City Is Not a Computer</i> reveals how cities encompass myriad forms of local and indigenous intelligences and knowledge institutions, arguing that these resources are a vital supplement and corrective to increasingly prevalent algorithmic models. Shannon Mattern begins by examining the ethical and ontological implications of urban technologies and computational models, discussing how they shape and in many cases profoundly limit our engagement with cities. She looks at the methods and underlying assumptions of data-driven urbanism, and demonstrates how the "city-as-computer" metaphor, which undergirds much of today's urban policy and design, reduces place-based knowledge to information processing. Mattern then imagines how we might sustain institutions and infrastructures that constitute more diverse, open, inclusive urban forms. She shows how the public library functions as a steward of urban intelligence, and describes the scales of upkeep needed to sustain a city's many moving parts, from spinning hard drives to bridge repairs. Incorporating insights from urban studies, data science, and media and information studies, <i>A City Is Not a Computer</i> offers a visionary new approach to urban planning and design.
Wuhan’s AI Development | Center for Security and Emerging Technology
Wuhan, China’s inland metropolis, is paving the way for a nationwide rollout of “embodied” artificial intelligence meant to fast-track scientific discovery, optimize production, streamline commerce, and facilitate state supervision of social activities. Grounded in real-world data, the AI grows smarter, offering a pathway to artificial “general” intelligence that will reinforce state ideology and boost economic goals. This report documents the genesis of Wuhan’s AGI initiative and its multifaceted deployment.
Strengthening AI Foundations: Emerging Opportunities for Developing Countries
The World Bank’s Digital Progress and Trends Report 2025 explores how AI is accelerating growth in developing countries, while highlighting persistent gaps in access, infrastructure, and skills. Discover key trends, challenges, and the ‘Four Cs’ needed to strengthen AI foundations globally.
A Roadmap to Democratic AI — The Collective Intelligence Project
Our roadmap outlines concrete steps that can be taken in 2024 to build a more democratic AI ecosystem that is adaptive, accountable, processes decentralized information, provides public goods, and safeguards human wellbeing. We describe what the ecosystem could build, research, advocate for, and fun
Democratic Governance of AI Is the Real Solution
The potential for catastrophic effects from the AI boom demands robust deliberation and real democratic governance. Localized initiatives like data center moratoria won't get us there.
AI.Gov | President Trump's AI Strategy and Action Plan
Explore President Trump’s AI initiatives focused on innovation, infrastructure, international engagement, and youth education in artificial intelligence.
Greyhaven — Sovereign AI Systems for Enterprise
Greyhaven builds custom sovereign AI systems: on-premise inference, private data pipelines, and model-agnostic architecture so enterprises maintain full control over their AI.
AI, Ethics, and Society — Home
From the Platform Society to the AI Society: Towards Critical Studies of Generative AI
The era of AI has begun. Generative AI is rapidly reshaping knowledge production, culture, and political authority, giving rise to an emerging AI society. Yet this transformation did not emerge ex nihilo. This paper argues that the AI society can only be understood in relation to the platform society from which it arises. Tracing the transition from platforms to AI, we identify interlinked economic, epistemic, and political shifts. Economically, AI emerges within platform-based rentier capitalism but reconfigures the monopoly mechanisms on which its accumulation depends. Epistemically, LLMs mark a shift from predictive to generative epistemics, entangling theory formation and knowledge production with private research-as-a-service infrastructures. Politically, governance shifts from data politics to alignment politics: from shaping visibility to shaping what can be said, thought, and imagined. Together, these transformations signal a qualitative shift in mediation—from governing interaction to governing cognition itself—and call for a Critical AI Studies.
AI Commons - One Project
What if we could redefine AI? What if we could shift its development from a capitalist model to a more disruptive, inclusive, and decentralized one?
Agentic AI Governance: A Strategic Framework for Autonomous Systems
Agentic AI is moving from chat to action. Learn how to govern autonomous systems using the "Digital Contractor" framework and the 3-Tiered Guardrail system.
3: Consulting the Record: AI Consistently Fails the Public - AI Now Institute
Amid the excitement over AI’s (speculative, hypothetical) potential, we have lost sight of the sobering reality of its present and recent past. AI is already intermediating critical social infrastructures, materially reshaping our institutions in ways that ratchet up inequality and concentrate power in the hands of the already powerful. It is consistently deployed in ways […]
Democratizing AI Companies — The Collective Intelligence Project
As AI reshapes society, the companies behind these technologies face a critical challenge: how to build corporate governance structures that prioritize public benefit over profit maximization;.
From chatbots to assistants: governance is key for AI agents
AI's shift into agentic technology ushers in a new set of governance and security challenges that will mean defining to what extent they should be autonomous
Debates On Frontier Artificial Intelligence Governance: The AI Triad
Analytical Paper Optional: All enrolled students have the option of completing a research paper of at least 20-25 pages, with faculty and peer review of a substantially complete draft. This paper can be used to satisfy the analytical paper requirement for J.D. students. Prerequisite: This course is intended for students intending to work in the […]
Environmental Cost of Artificial Intelligence: Carbon, Water, and Land Footprints
AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.
