UN smart city AI toolbox puts people in charge of public decisions
Setting a positive example: Helsinki's public AI register describes systems, their purposes and the people responsible for supervising them.
When a city relies on AI to flag a welfare application, prioritise a road repair, or answer a resident’s query, the technology directly influences how public money is allocated and how individuals are treated. Because the stakes are so high, a human must always remain responsible for verifying those outputs, explaining the resulting decisions, and fixing mistakes.
Preserving that human accountability is the core mission of the United Nations’ new Toolbox for People-Centred Smart Cities in the AI Era. Launched in Barcelona on 4 November 2026, the toolbox provides mayors, city managers, and policymakers with practical strategies to maintain strict public oversight as AI integrates into everyday local government.
The resource is jointly issued by the International Telecommunication Union (ITU) (the UN agency for digital technologies) and UN-Habitat, the UN programme for sustainable urbanisation. Developed under United for Smart Sustainable Cities (U4SSC), a UN initiative celebrating its tenth anniversary, the project's flagship publication, Guiding Principles and Frameworks for People-Centred Smart Cities in the AI Era, translates these high-level ethical goals into a clear roadmap and practical safeguards.
Human accountability for AI in city services
The guidance asks cities to define the public problem before choosing a technology, identify who could benefit or be harmed, and assign responsibility throughout the project. Its eight-step implementation cycle connects those early choices with design, deployment, measurement and adaptation.
Consider software that recommends which roads should be repaired first. Processing inspection data can help a municipality identify damaged surfaces, but deciding how to distribute a limited maintenance budget also involves public priorities. Officials must be able to assess the recommendation and explain the choices they make.
To exercise meaningful control, officials need sufficient understanding to question a system’s outputs, time to consider them and authority to depart from them. An approval step offers little protection if the employee cannot assess the recommendation.
The appropriate arrangement depends on the task. A planning officer could review an AI-generated application summary before deciding; a traffic controller could supervise adaptive signals and intervene when necessary.
AI bias in Amsterdam’s welfare screening
Amsterdam’s failed pilot with the "Slimme Check" (Smart Check) system underscores why algorithmic scrutiny must persist after an AI tool goes live. Designed to flag welfare applications for fraud investigations, the system trained on historical data to identify risk patterns. However, AI is fundamentally limited by its training data. Because machine learning models replicate and amplify historical patterns, biased inputs or unrepresentative data inevitably lead to discriminatory predictions and systemic unequal treatment.
This was precisely what happened in Amsterdam. Although city officials adjusted the training data to mitigate bias after initial tests exposed disparities, a subsequent pilot run between June and August 2023 merely shifted the inequality. This time, women and Dutch nationals were significantly more likely to be falsely flagged for investigation than men and non-Dutch applicants.
Consequently, Amsterdam shelved the pilot in November 2023. Ultimately, the project yielded a vital lesson: an apparent improvement in fairness during a controlled testing phase does not guarantee equitable outcomes in practice. This failure underscores the indispensable role of human oversight in continuously evaluating AI performance and deciding whether a system remains fit for service.
New York’s MyCity chatbot gave incorrect advice
While Amsterdam’s system influenced the scrutiny of individual applications, New York’s experience demonstrates how errors can directly mislead the public through advice issued in a city’s name. In March 2024, testing by the investigative newsroom The Markup revealed that New York’s MyCity business chatbot was giving incorrect advice, falsely informing users that they could withhold employees’ tips and refuse cash payments.
Although the city defended the service as a pilot and highlighted disclaimers warning of inaccurate answers, spotting these errors required the very knowledge that business owners used the chatbot to find.
The UN toolbox addresses this friction between automated services and public accountability. It recommends providing human points of contact alongside non-digital or assisted channels for essential services, ensuring that user complaints reach someone with the authority to act.
The toolbox recommends a "traffic light" approach to governance, applying lighter safeguards for routine tasks like drafting and transcription, and far more stringent scrutiny for applications that impact legal rights, public safety, or essential services.
Higher-impact use cases include allocating housing, managing welfare benefits, and operating critical infrastructure. For these high-risk deployments, recommended protections include human rights impact assessments, independent reviews, and mandatory consultation with affected groups.
Ultimately, this risk-based framework means a chatbot providing simple library opening hours requires a completely different level of oversight from one determining eligibility for financial assistance, even if both systems rely on similar underlying technology.
Helsinki’s public AI register makes oversight visible
For residents to challenge or question an AI-supported service, they must first know exactly where automation is being deployed. Helsinki, the capital of Finland, provides a leading example of making this role visible through its public AI register, which details the systems in use, their specific purposes, and the officials responsible for overseeing them. Current entries include a parking and streets bot, a rental housing chatbot, and a library virtual assistant.
In official guidance published on 27 October 2026, Helsinki stated that its services must explicitly disclose AI usage whenever it impacts the service a customer receives, the processing of their case, or content published by the city. Under these rules, digital services indicate AI involvement directly within the user interface, and human operators verify information before it is published.
By clearly documenting specific services and their lines of accountability, the register provides residents with a vital starting point for directing questions to the appropriate authorities.
Better information, accountable choices
Governance safeguards can run alongside practical improvements in municipal services, as demonstrated in South Africa’s eThekwini Municipality, which includes Durban. Here, the Building and Establishment Automated Mapper (BEAM) has helped urban planners obtain far more comprehensive data on local structures.
Developed by the United Nations Innovation Technology Accelerator for Cities (UNITAC) in collaboration with municipal partners, BEAM detects rooftops using aerial and satellite imagery. UNITAC reports that the system successfully mapped more than 1.5 million building footprints across eThekwini, slashing mapping times from months to approximately 72 hours.
While this data significantly enhances housing and infrastructure planning, human officials remain strictly responsible for determining how it is applied, deciding which communities receive investment, and justifying those priorities to the public.
The most responsible thing an authority can do sometimes is to scale back or completely switch off an AI tool. But when a project has a narrow, clearly defined job (like mapping rooftops) it gives officials a solid foundation to measure real-world benefits and figure out exactly where the technology can actually be helpful.
At the end of the day, accountability isn’t a theoretical concept for the person on the receiving end. If a resident is wrongly accused of welfare fraud or given bad advice by a city chatbot, they need to know a real person is looking out for them. This is what the UN toolbox is ultimately about: to protect that human connection as more and more public services adopt AI.
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