AI Globalism and AI Localism: Governing AI at the Local Level for Global Benefit: A Response to the On-Going Calls for the Establishment of a Global AI Agency

By Stefaan Verhulst

Data & Policy Blog
Data & Policy Blog
5 min readNov 2, 2023


With the UK Summit in full swing, 2023 will likely be seen as a pivotal year for AI governance, with governments promoting a global governance model: AI Globalism. For it to be relevant, flexible, and effective, any global approach will need to be informed by and complemented local experimentation and leadership, ensuring local responsiveness: AI Localism.

Even as consumers and businesses extend their use of AI (generative AI in particular), governments are also taking notice. Determined not to be caught on the back foot, as they were with social media, regulators and policymakers around the world are exploring frameworks and institutional structures that could help maximize the benefits while minimizing the potential harms of AI. This week, the UK is hosting a high-profile AI Safety Summit, attended by political and business leaders from around the world, including Kamala Harris and Elon Musk. Similarly, US President Biden recently signed an Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, which he hailed as a “landmark executive order” to ensure “safety, security, trust, openness, and American leadership.”

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Amid the various policy and regulatory proposals swirling around, there has been a notable emphasis on what we might call AI globalism. The UK summit has explicitly endorsed a global approach to AI safety, with coordination between the US, EU, and China core to its vision of more responsible and safe AI. This global perspective follows similar recent calls for “an AI equivalent of the IPCC” or the International Atomic Energy Agency (IAEA). Notably, such calls are emerging both from the private sector and from civil society leaders.

In many ways, a global approach makes sense. Like most technology, AI is transnational in scope, and its governance will require cross-jurisdictional coordination and harmonization. At the same time, we believe that AI globalism should be accompanied by a recognition that some of the most innovative AI initiatives are taking place in cities and municipalities and being regulated at those levels too.

We call it AI localism. In what follows, I outline a vision of a more decentralized approach to AI governance, one that would allow cities and local jurisdictions — including states — to develop and iterate governance frameworks tailored to their specific needs and challenges. This decentralized, local approach would need to take place alongside global efforts. The two would not be mutually exclusive but instead necessarily complementary.

Why Cities Matter

In a rapidly evolving digital ecosystem, the proliferation of AI technologies is bringing to the fore a spectrum of challenges and opportunities, many of which are particularly manifest in urban settings. Indeed, cities are emerging as hubs of innovation and experimentation when it comes both to AI initiatives and AI governance. For instance, Amsterdam and Helsinki have developed Algorithm Registries to detail how their respective city governments plan to deliver services using AI. (See our repository of examples HERE). Similarly, regulatory initiatives include the Cities Coalition for Digital Rights, the Montreal Declaration for Responsible AI, and many other efforts that are emblematic of how cities are pioneering in the AI governance landscape.

The term AI localism emerges from a recognition of this urban ferment. It encapsulates a paradigm within which local jurisdictions are spearheading responses to global challenges, supplanting a one-size-fits-all approach with more tailored responses. As noted, globalism and localism are deeply intertwined. While global dialogues provide a platform for discussing overarching principles, the dynamism and contextual intricacies of AI applications beckon for a more localized approach. The concept of AI Localism in effect presents a pragmatic pathway from global deliberations to local implementations.

One of the chief advantages of AI Localism is that it is deeply context sensitive. By accentuating the primacy of local governance in navigating the AI policy and ethical maze, it is tailored to the unique socio-economic and cultural fabric of cities and contexts. This context-sensitive approach to governance is not merely a reactionary stance but a proactive, nuanced engagement in order to harness AI for public good while mitigating its adverse impacts.

An AI Localism Canvas

In order to explore the possibilities (and challenges) of AI Localism, The GovLab developed the “AI Localism Canvas,” a pragmatic framework designed to delineate and assess the AI governance landscape specific to a city or region. The canvas serves as a living document and a heuristic tool for local decision-makers, aiding in the meticulous evaluation of risks and opportunities intrinsic to AI deployment. Policies and frameworks can be evaluated along categories such as Transparency, Procurement, Engagement, Accountability, Local Regulation, and Principles, providing a holistic view of the AI governance stack at a local level. This canvas is envisioned to evolve synchronously with the growing imprint of AI at the city level, continually refining the local governance responses to the multifaceted challenges posed by AI.

The advantages of such a canvas, and more generally of AI Localism, lies in its emphasis on immediacy and proximity. It allows researchers, policymakers, and other stakeholders to engender positive feedback loops through a deeper understanding of local conditions and a more granular calibration of AI policies. While we fully recognize (and even embrace) the need for a global perspective, we strongly believe that the global can grow and learn from the local: the general must be built upon the foundations of the particular.

2023, and in particular the latter half of the year, may go down in history as a seminal moment in the regulation of AI. But even as much of the discourse and many of the initiatives emphasize the need for a coordinated global approach, AI Localism presents a compelling counter-narrative. It posits that a globally coordinated yet locally experimented governance model is more attuned to the heterogeneous nature of AI’s societal impact. It offers a bottom-up rather than top-down approach to global AI governance. As such, it is a shame that the current UK AI Summit largely ignores the role and importance of local expertise, experience and experimentation in how AI is governed. When designed responsibly, AI Localism transcends the (false) local-global dichotomy, offering a pathway to a collaborative, multi-level governance model that is both globally informed and locally responsive.

About the Author

Stefaan Verhulst is Co-Founder and Chief Research and Development Officer of The GovLab, and also one of the Data & Policy Editors-in-Chief.


This is the blog for Data & Policy (, a peer-reviewed open access journal exploring the interface of data science and governance. Read on for five ways to contribute to Data & Policy.



Data & Policy Blog
Data & Policy Blog

Blog for Data & Policy, an open access journal at CUP ( Eds: Zeynep Engin (Turing), Jon Crowcroft (Cambridge) and Stefaan Verhulst (GovLab)