What does AI Localism look like in action? A new series examining use cases on how cities govern AI

Series by Uma Kalkar, Sara Marcucci, Salwa Mansuri, and Stefaan Verhulst: “…We call local instances of AI governance ‘AI Localism.’ AI Localism refers to the governance actions—which include, but are not limited to, regulations, legislations, task forces, public committees, and locally-developed tools—taken by local decision-makers to address the use of AI within a city or regional state.

It is necessary to note, however, that the presence of AI Localism does not mean that robust national- and state-level AI policy are not needed. Whereas local governance seems fundamental in addressing local, micro-level issues, tailoring, for instance, by implementing policies for specific AI use circumstances, national AI governance should act as a key tool to complement local efforts and provide cities with a cohesive, guiding direction.

Finally, it is important to mention how AI Localism is not necessarily good governance of AI at the local level. Indeed, there have been several instances where local efforts to regulate and employ AI have encroached on public freedoms and hurt the public good….

Examining the current state of play in AI localism

To this end, The Governance Lab (The GovLab) has created the AI Localism project to collect a knowledge base and inform a taxonomy on the dimensions of local AI governance (see below). This initiative began in 2020 with the AI Localism canvas, which captures the frames under which local governance methods are developing. This series presents current examples of AI localism across the seven canvas frames of: 

  • Principles and Rights: foundational requirements and constraints of AI and algorithmic use in the public sector;
  • Laws and Policies: regulation to codify the above for public and private sectors;
  • Procurement: mandates around the use of AI in employment and hiring practices; 
  • Engagement: public involvement in AI use and limitations;
  • Accountability and Oversight: requirements for periodic reporting and auditing of AI use;
  • Transparency: consumer awareness about AI and algorithm use; and
  • Literacy: avenues to educate policymakers and the public about AI and data.

In this eight-part series, released weekly, we will present current examples of each frame of the AI localism canvas to identify themes among city- and state-led legislative actions. We end with ten lessons on AI localism for policymakers, data and AI experts, and the informed public to keep in mind as cities grow increasingly ‘smarter.’…(More)”.