**7. Conclusions: The Next Big Sustainability Challenge**

This viewpoint has explored the prospects and constraints of developing and deploying AI technology to make present and future cities more sustainable. The analysis has shown that, while AI technology is evolving and becoming an integral part of urban services, spaces, and operations, we still need to find ways to integrate AI in our cities in a sustainable manner, and also to minimize the negative social, environmental, economic, and political externalities that the increasingly global adoption of AI is triggering. In essence, the city of AI is not a sustainable city. Both the development of AI and the development of cities need to be refined and better aligned towards sustainability as the overarching goal. With this in mind, the viewpoint has generated the following insights, in the attempt to improve the sustainability of AI and that of those cities that are adopting it.

First of all, AI as part of urban informatics significantly advances our knowledge of computational urban science [205]. In the age of uncertainty and complexity, urban problems are being diagnosed and addressed by numerous AI technologies. However, from a sustainability perspective, the quality of our decisions about the future of cities heavily depends on this computational power (technology), *and* on the inclusivity of decision-making and policy processes. The greater computational power offered by AI, therefore, is not enough to achieve sustainability, unless it is coupled with systems of democratic governance and participatory planning.

Second, AI is being exponentially used to improve the efficiency of several urban domains such as business, data analytics, health, education, energy, environmental monitoring, land use, transport, governance, and security. This has a direct implication for our cities' planning, design, development, and management [206]. Yet, the different uses of AI tend to be fragmented, in the sense that heterogeneous AIs are targeting heterogeneous issues and goals without a holistic approach. Coordinating the many AIs present in our cities is thus necessary for a sustainable urbanism, given that sustainability is about thinking and acting in terms of *the whole* rather than single parts. On these terms, artificial narrow intelligences working on narrow tasks are missing the broad spectrum of social, environmental, and political issues, which is essential to achieve sustainability. We cannot and should not expect a hypothetical future artificial general intelligence to fill this lacuna [207]. Human initiative and coordination are needed now.

Third, the autonomous problem-solving capacity of AI can be useful in some urban decision-making processes. Still, the utmost care is needed to check and monitor the accuracy of any autonomous decisions made by an AI—human inputs and oversight are now critical in relation to artificial narrow intelligence, and they would be even more important should innovation reach the stage of artificial general intelligence [208]. AI can help us optimize various urban processes and can

actually make cities smarter. We can move faster towards the goal of smart urbanism, but if we want to create smart *and* sustainable cities, then human intelligence must not be overshadowed by AI.

Fourth, AI can drive positive changes in cities and societies, and contribute to several SDGs [104,209]. Nonetheless, despite these positive prospects, we still need to be cautious about selecting the right AI technology for the right place and ensuring its affordability and alignment with sustainability policies, while also considering issues of community acceptance [210]. AI should not be imposed on society and cities, but rather discussed locally at the community level, taking into account geographical, cultural, demographic and economic differences. Sustainability can only be achieved with a healthy combination of technology, community and policy drivers, hence the urgent need to develop not only technologically, but also socially and politically.

Fifth, we need to be prepared for the upcoming and inevitable disruptions that AI will create in our cities and societies. The diffusion of AI will not be a black and white phenomenon. Many shades of grey will characterize the deployment of heterogeneous AIs in different parts of the world. Even in an optimistic scenario in which a 'benign AI' is promoting sustainability, somewhere someone/something will still be suffering. It is thus imperative to develop appropriate policies and regulations, and to allocate adequate funds, in order to mitigate the disruption that AI will cause to the most disadvantaged cities and social groups, and nature [211]. As we mentioned earlier, sustainability is not about single parts, but rather about the whole. Any form of development that fractures cities, societies, and the natural environment, producing winners and losers, is not sustainable. Like a hurricane, AI is likely to shake everything that we see, know, and care about. It should not be forgotten that we are only as strong as the weakest member of the society.

Sixth, a symbiotic relationship between AI and cities might become a concrete possibility in the future. Combined with progress in public policy and community engagement, progress in AI technology could mitigate the global sustainability challenges discussed in Section 2 [212]. In so doing, while the city might benefit from AI technologies and applications, AI might also benefit from the city to advance itself. This is a key aspect of the intersection between the development of AI and the development of the city. As we explained in Section 4, a key AI skill is learning. AIs learn by sensing the surrounding environment, thereby gaining and accumulating knowledge [15]. Learning is also how AIs improve themselves. AI is a technology that learns from the collected data, from its errors as well as from the mistakes made by other AIs and human intelligences. On these terms, the city represents the ideal learning environment for AI. Cities are the places where knowledge concentrates the most, where a wide-range of events occur, where numerous actors meet and where the biggest mistakes and greatest discoveries of mankind have been made. It this in this cauldron of ideas and experiences that we call *city* that contemporary artificial narrow intelligences can learn the most, potentially evolving into artificial general intelligences.

Seventh, we need to further decentralize political power and economic resources to make our local governments ready for the AI era that is upon us. While planning for a sustainable AI uptake in our cities is crucial, presently, almost all local governments in the globe are not ready—in terms of technical personnel, budget and gear—to thoroughly plan and implement AI projects city-wide [213,214]. Most AI technologies are expensive and it is therefore important to make them affordable, in order to avoid an uneven distribution and ultimately injustice. If AI is to become part of the city, then we need to think of AI not as an elitist technology, but rather as a common good on which everybody has a say. This is, in turn, a question of urban politics and a matter of politicizing AI so that its deployment in cities is discussed and agreed as inclusively and as democratically as possible, instead of being dictated by a handful of influential tech companies. Sustainability will not be achieved in a technocracy.

Eighth, some of the changes triggered by AI might be invisible and silent and, yet, their repercussions are likely to be tangible and loud from an urban perspective. For example, AI is clearly impacting on the economies of cities [215]. This impact will get deeper and wider as innovation keeps improving and expanding the capabilities of artificial narrow intelligences. *What is the role of humans in an economy in which artificial narrow intelligences, artificial general intelligences and artificial*

*super intelligences can cheaply perform human tasks faster and better?* This is a recurring question in AI studies, to which we add a complementary urban question: *What is the role of cities as economic hubs in the era of AI?* A key reason why cities exist is that they provide the spaces that are necessary to perform and accommodate human labor and to train humans in many work-related fields. However, AI is undermining this *raison d'etre*. If human labor decreases or, worse, ceases to exist in cities, then cities are likely to decline and cease to exist too [1]. Now more than ever it is therefore vital to reimagine, replan and redesign cities in a way that their function and shape are not dictated by and dependent on human economies. This is both a matter of rethinking the economic dimension of cities and galvanizing the social, cultural, psychological, political, and environmental dimensions of urban spaces.

Lastly, in the context of smart and sustainable cities, AI is an emerging area of research. Further investigations, both theoretical and empirical, from various angles of the phenomenon and across disciplines, are required to build the knowledge base that is necessary for urban policymakers, managers, planners, and citizens to make informed decisions about the uptake of AI in cities and mitigate the inevitable disruptions that will follow. This will not be an easy task because AI is a technology while the city is not. Cities are primarily made of humans and are the product of human intelligence. The *merging of artificial and human intelligences in cities* is the world's *next big sustainability challenge*.

**Author Contributions:** T.Y. designed the study, conducted the analysis, and prepared the first draft of the manuscript. F.C. expanded the manuscript, and improved the rigor, relevance, critical perspective and reach of the study. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors. The authors thank the anonymous referees for their invaluable comments on an earlier version of the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.
