Urban Artificial Intelligence: From Automation to Autonomy in the Smart City

Abstract

Technological innovation is constantly reshaping the materiality and mechanics of smart-city initiatives. Recently, innovation in artificial intelligence (AI) in the shape of self-driving cars, robots and city brains, has been pushing the so-called smart city to morph into an autonomous urban creature which is largely unknown. In this emerging strand of smart urbanism, artificially intelligent entities are taking the management of urban services as well as urban governance out of the hands of humans, operating the city in an autonomous manner. This paper explores, in theory and practice, how the development of AI intersects with the development of the city. The contribution of the paper is threefold. First, the paper advances a theoretical framework to understand AI specifically in urban contexts. It develops the concept of urban artificial intelligence, capturing the main manifestations of AI in cities. Second, the paper examines the case of Masdar City, an Emirati urban experiment, to show how the genesis of urban artificial intelligences is part of a long-standing process of technological development and a politico-economic agenda which together are enabling the transition from automation to autonomy. Third, it proposes a research agenda to investigate what the paper terms the autonomous city.

Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

“…With a specific focus on technology for responsible urban innovation, the paper concentrates on AI and its use as part of local government systems. The rationale behind this selection is as follows: (a) AI, a technology with an increasing number of applications in the urban context, is referred to as one of the most powerful technologies of our time with both positive and negative externalities for cities [31,32]; (b) AI is an integral part of a smart city structure that provides the required efficiencies and automation ability in the delivery of local infrastructures, services and amenities [33,34], and; (c) there is a trend among local government agencies to adopt AI for managing routine, complex and complicated urban issues, where the knowledge and the experience of the staff in the area of responsible innovation, in general, are fairly limited [35][36][37].…”

Smart and Resilient Urban Futures for Sustainability in the Post COVID-19 Era: A Review of Policy Responses on Urban Mobility

“…The pandemic acted as an accelerator in the experimentation of many emerging technologies, from drones and delivery robots to scanning human encounters through cell phone location data [55,56]. Several institutions have been collecting data of the new outbreaks and statistics, while scientists correlate COVID-19 cases and environmental variables (e.g., air pollution), urban formations (e.g., population density), and other societal data (such as income, poverty rates, and demographics) of the affected areas [57,58]. Yet the level of adoption by city authorities and policymakers is still unclear.…”

Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques

“…are highly dependent on IoT and related cyber-physical systems [ 48 ]. Machine learning techniques are used to better manage those smart city services and resources in an autonomous manner [ 45 , 49 ]. In addition, machine learning techniques can well detect intrusion and cyberattacks in industrial IoT [ 50 ], which therefore can enhance sustainability and ensure uninterrupted services in smart cities by thwarting attacks and intrusion on respective IoT systems.…”