Fourth Industrial Revolution

How equitable data practices can shape the future of urban planning

graphic showing a modern digital city with binary data flows

Equitable data practices are key to designing the AI systems that will define future urban transformation. Image: Getty Images/iStockphoto

Jacqueline Lu
Chief Executive Officer and Founder, Helpful Places (Digital Trust for Places & Routines)
Jeff Merritt
Head of Centre for Urban Transformation; Member of the Executive Committee, World Economic Forum
  • AI systems are increasingly part of new forms of urban infrastructure being used in our cities to provide services and define place-based outcomes.
  • Current practices around AI systems' design and deployment are not best suited for having inclusion, equity and participation in the innovation process.
  • The future of equitable and sustainable cities could be accelerated by advancing data equity in practice when it comes to urban planning.

Digital technologies have become ubiquitous in today’s urban environments. Facial recognition systems are used at sports and entertainment venues and public events. Vehicle mounted, camera-based artificial intelligence systems count potholes and signs of homelessness. Licence plate recognition systems enforce traffic rules and charging tolls.

As AI systems are increasingly part of the new urban infrastructure that cities use to provide services and operate shared spaces, it is critical that these applications are considered and reflected in broader conversations about the benefits and potential harms of this technology and the need for regulation.

These new forms of digitalized urban infrastructure are critical to society’s ability to achieve sustainability and climate goals – for example, helping manage energy demand to reduce greenhouse gas emissions, or using cameras to regulate and manage vehicle traffic to minimize congestion and improve air quality. At the same time, these technologies raise pressing issues and considerations in their application to ensure that the digital age enables a vision of shared prosperity.

These technologies have transformed what were once static spaces, roads and plazas into dynamic AI systems that make decisions affecting all of us. We live in an era where automated decision-making systems based on algorithms and data are no longer limited to software that runs on our computers and screens, but into the built environment as infrastructure.

Urban AI systems are not inherently equitable

History has shown that the way places are built has the potential to divide, marginalize and exploit people in their communities. The permanence of built infrastructure – like a highway, park, or school – makes it tangible to the people it has impacted.

As a result of this prior history, people and communities now demand and expect participation in the decisions that shape their urban environments. Massive infrastructures are visible and, as such, affected communities can respond to, adapt and co-opt them to mitigate their negative effects.

For example, it’s possible for people to see and discuss the impacts of a highway or a major road running through their neighbourhood; but much harder to realize that there is an algorithm that adjusts the timing of traffic lights to prioritize the speed of cars over how long people need to wait to cross the street.

Digitalized infrastructure is different. It is often invisible. Data-collecting technologies deployed in the public realm are often installed to be as invisible as possible. This invisibility hides the impact digital infrastructure has on communities – the decisions that are made with the data collected and how it’s processed, the changes to policy made by changes in code, and the deployment of AI models and algorithms.

A security camera in a corner of a physical space could be reviewed and used only when there is a reported incident; or, it could be providing data to a computer vision system using facial recognition to identify specific individuals. Unlike large physical infrastructure, the impacts of digital infrastructure are hidden, and ever-evolving.

As the world is increasingly data driven, it is critical to recognize that digitalized forms of infrastructure have the potential to perpetuate existing, inequitable power dynamics through issues such as infringing on privacy, automating decisions and perpetuating sources of bias.

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Even if a technology’s designers are careful to account for these risks in the design of these technologies, inequities can persist through decisions of where, and when, those technologies are utilized. Every technology can be used to benefit cities, and the same technology has the potential to cause harm to the communities we seek to benefit.

A data equity lens is critical for the future of cities

The Global Future Council on Data Equity has defined and created a “framework of inquiry” to foster action in addressing historical and current imbalances in the use and access of datasets in various domains, and for decision-making in algorithmic and AI systems and their societal impact.

Data equity is defined as the shared responsibility for fair data practices that respect and promote human rights, opportunity and dignity – and these concepts are applicable and extensible to digitalized forms of urban infrastructure.

Just like it's clear people have a right to participate in the design of these digital layers and urban technologies, it's important to actively involve communities in the deployment and governance of new technologies so that potential benefits and tradeoffs can be discussed.

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Most processes for public transparency and consent for technology use are centered on consumer technologies and utilize individual “opt-in” processes. However, this individualistic approach is not well suited for urban technologies that impact diverse groups over large geographies and long time-scales. The action oriented Advancing Data Equity framework offers a way to get started with addressing these challenges.

Designed to be flexible and a starting point for inquiry, the data equity considerations in the framework are intended to be applicable to a broad range of issues and industries. Just as equity considerations can be brought into the design and development of public spaces and streets, so can data equity for urban technology.

Advancing Data Equity: Data equity framework
A framework to advance data equity. Image: The World Economic Forum

A next practice for urban planning?

In their 2023 Trend Report, the American Planning Association suggested that with the increasing digitalization of public spaces, planners should start incorporating and thinking about technology and how it is being used. Ethical, democratic and effective use of these AI-enabled smart city technologies requires foresight and planning.

Proactive actions that can be taken to advance data equity in urban technology have many parallels with practices in urban planning. Here’s how:

  • Ensuring transparent processes for obtaining community permissions for data-related decisions can borrow from planning practices of providing notice and clear review steps for changes that are being made to the built environment. For example, the New South Wales government in Australia has issued guidance to place owners and local councils to utilize the open-source Digital Trust for Places and Routines standard as a way to help people engage with and understand urban technology, following on learnings from a digital trust pilot in Sydney Olympic Park.
  • Consideration of how the outcomes of the data or technology can be beneficial to impacted individuals and communities, could borrow from urban planning engagement practices developed to bring together diverse groups of stakeholders to align on outcomes for a place – or go even further, by involving them in the process. For example, the City of Long Beach’s Co-Lab programme engaged community members in a process to identify neighbourhood needs, and involved them in the design and implementation of a technology solution to address an agreed-upon challenge – as part of a broader strategy of ensuring that smart city solutions are implemented with an equity lens.

Planners and urban innovators, with processes and expertise in bringing multiple stakeholders together to align on place-based outcomes, are well positioned to advance data equity in practice.

They should collaborate with actors designing, deploying and regulating these technologies to ensure that equity considerations are taken into account, and to ensure the inclusion of communities and key stakeholder groups.

Opportunities exist for local governments to enable foresight and planning for technology in our cities and public spaces, through existing land use and development planning processes, and tools such as zoning bylaws and design review panels.

Discover

How is the World Economic Forum creating guardrails for Artificial Intelligence?

It’s about recognizing parallels in how equity is considered across the many stages of planning and urban development with how data equity is addressed in similar stages in the data lifecycle – and using these considerations as a starting point for inquiry, collaboration and shared learning.

In this way, the future of equitable, sustainable cities could be accelerated by bringing the design and deployment of digital systems closer together with the practice of urban planning.

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