New York City Mayor Zohran Mamdani’s establishment of the Office of Mass Engagement marks an important step towards increasing responsiveness within local government. By committing to listen more closely to the concerns of everyday New Yorkers, Mamdani aims to rebuild public trust. However, simply enhancing listening capabilities is not enough; the city must also address quality-of-life issues with greater agility and foresight.
This need for a more effective approach to local governance was underscored during my tenure as deputy mayor under Mike Bloomberg. Despite the City’s strong performance metrics, I sought to understand how operational challenges impacted the daily lives of New Yorkers. My strategy involved weekly meetings with community representatives across boroughs, which often began with a crucial question: How could city government better serve your neighborhood?
These interactions typically revealed a pattern of common-sense requests that were often thwarted by rigid interpretations of city regulations. For instance, requests to adjust walk sign timings for seniors were consistently denied due to strict adherence to traffic engineering manuals. Similarly, procurement processes often favored the lowest bidder over quality, leading to substandard construction in neighborhood parks. I recall a restaurant owner in Queens expressing frustration after being fined for a minor health code violation while preparing pizzas.
The roots of these bureaucratic challenges can be traced back to the Progressive era, where an overabundance of regulations was enacted in response to political corruption. Though well-intentioned, this has resulted in a labyrinth of compliance requirements that stifle flexibility among city workers. Union leaders, aiming to protect their members from managerial overreach, have added further restrictions to operational protocols, complicating efforts to address community needs.
In this model, the traffic engineer looking at the wide street can pull up pedestrian counts, crash data and the age profile of the surrounding residents in seconds and adjust the walk signal without waiting six months for a manual revision.
Despite a shared desire for fair governance, excessive control can create a counterproductive rigidity that hampers effective decision-making. This inflexibility often leaves traffic engineers, procurement officials, and health inspectors with little room to implement practical solutions. Embracing artificial intelligence (AI), alongside updated civil service and management rules, presents a promising opportunity to achieve a balance between adhering to regulations and exercising sensible discretion.
In a recent article published in the journal Urban Governance, my coauthor Juncheng “Tony” Yang and I introduced the concept of “accountable discretion.” This approach empowers frontline workers to exercise judgment while ensuring that technological solutions render each decision traceable and fair. For example, a traffic engineer could swiftly access relevant data to modify walk signal timings, while a health inspector could issue a warning instead of a fine during a first-time violation at a restaurant.
AI can streamline decision-making processes, enabling frontline workers to focus more on judgment rather than administrative tasks. By managing routine paperwork and maintaining transparent records, AI allows employees to make informed decisions in real time, enhancing accountability. Supervisory roles can also evolve; rather than enforcing uniform rules, supervisors can monitor how inspectors utilize their discretion and intervene only when necessary.
Accountable discretion only works with strong human oversight, clear limits on surveillance, serious investment in staff training and straightforward ways for residents to question a decision and push back.
However, the implementation of AI in city governance is not without challenges. City data remains fragmented and locked within outdated systems, often obstructed by privacy regulations that were established in an earlier technological context. Without addressing these fundamental issues, improvements in responsiveness could lead to inaccurate outcomes. Moreover, risks emerge when agencies overly monitor staff or blindly trust algorithmic recommendations. Effective implementation of accountable discretion requires robust human oversight, transparent surveillance limits, comprehensive staff training, and mechanisms for public feedback.
AI can also enhance urban engagement by enabling cities to listen more effectively to community concerns. Developing technologies like anonymized surveys and AI-driven sentiment analysis can reveal quality-of-life issues sooner, allowing for timely interventions. For instance, an increase in air-quality sensor readings could prompt action before health complaints are formally registered.
When appropriately employed, AI can augment human judgment rather than replace it. By handling routine tasks and sorting information, AI can empower public employees to focus on critical issues. Additionally, an AI-powered interface could streamline the permit application process for new restaurants, allowing them to submit their information in one go, thus improving efficiency and transparency.
Nonetheless, the journey toward integrating AI in city governance will be challenging. Existing civil service protocols are deeply entrenched, and skepticism from union leaders may complicate reform efforts. Public concerns regarding the misuse of AI must also be proactively addressed. Nonetheless, this is a pivotal moment for urban governance, as mayors can lead necessary changes that are imminent regardless of resistance.
As cities navigate the complexities of AI implementation, establishing guidelines will be crucial to prevent bias and ensure equitable outcomes. Mayors with strong relationships with labor organizations should engage in dialogue about how to maintain human oversight in decision-making processes. Ultimately, New Yorkers deserve a City Hall that prioritizes common-sense solutions over bureaucratic hurdles. With the right tools and rules, both city officials and residents can benefit, transforming challenges into opportunities for improved public services.
This article is based on a study by Stephen Goldsmith and Juncheng “Tony” Yang titled “AI and the Transformation of Accountability and Discretion in Urban Governance,” published in Urban Governance.
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