Algorithms and geo-discrimination risk: What hazards for smart cities' development?

In the context of smart cities, people and places get connected by means of sophisticated technologies, tools, and applications, such as data mining, machine learning, big data, and the Internet of Things. The term smart city, which includes related issues such as smart well-being, smart transit, and smart society, has attracted considerable attention in the academia and policymaking due to its impact on people’s quality of life. The development of various models like forecast, preparation, and monitoring in smart cities has been enhanced by deep learning and machine learning techniques for urban development. In self-driving cars, traffic lights and traffic control systems, systems to support the management of energy distribution, and water – in sum, wherever there will be large masses of information to be managed – there is an opportunity to develop algorithms to handle it. Although presented as objective tools, algorithms are to be regarded as sociotechnical devices that incorporate the perspectives of the authors involved in their creation. Thus, mentioning “algorithmic risk” is important to highlight the potentially harmful consequences – intentional or unintentional – that algorithms can generate for individuals and societies in smart cities. The objective of this chapter is to examine a possible hypothetical “geo-discrimination risk”, an issue that might transform smart cities in places where opportunities and possibilities are not evenly distributed. The findings of this research suggest that the unquestioning integration of algorithms in the urban development of smart cities has the potential to affect both the physical urban environment and the lives of individuals, leading to the emergence of geo-discrimination at both these distinct levels. Accordingly, this work may inform future research in this area and support policymakers in developing and managing smart cities.