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.
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.
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.
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.
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.
How to Build an AI Data Center | IFP
Part One of Compute in America: Building the Next Generation of AI Infrastructure at Home
Building Political Superintelligence
Amidst fears of dystopia, a blueprint for how we use AI to reinvent the way we govern ourselves
Irresponsible AI: big tech’s influence on AI research and associated impacts
The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech’s influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech’s influence. Third, we discuss the underlying economic forces driving big tech’s actions. Finally, as a call to action, we invite AI researchers to counter big tech’s influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.
AI Principles
A guiding framework for our responsible development and use of AI, alongside transparency and accountability in our AI development process.
