SOCIALLY RESPONSIBLE USE OF ARTIFICIAL INTELLIGENCE IN SMART CITIES: AN ETHICAL IMPERATIVE Cover Image

SOCIALLY RESPONSIBLE USE OF ARTIFICIAL INTELLIGENCE IN SMART CITIES: AN ETHICAL IMPERATIVE
SOCIALLY RESPONSIBLE USE OF ARTIFICIAL INTELLIGENCE IN SMART CITIES: AN ETHICAL IMPERATIVE

Author(s): Daniela Popescul, Laura-Diana Radu
Subject(s): Economy, ICT Information and Communications Technologies
Published by: Editura Universităţii »Alexandru Ioan Cuza« din Iaşi
Keywords: smart cities; AI ethics; social sustainability; XAI; privacy
Summary/Abstract: Currently, Artificial Intelligence (AI) is promisingly complementing the technological landscape associated with smart cities, consisting of contextual combinations of solutions based on the Internet of Things (IoT), mobile devices, mobile communications via satellites or short-range, data platforms, Virtual and Augmented Reality, etc. The benefits associated with the use of AI relate to improving services and optimizing resource utilization, with the stated aim of ensuring a better life for citizens in urban areas. The top-down approach in the design and implementation of technological solutions associated with smart cities remains dominant, as a consequence of the power and impact of major stakeholders (technology producers and policymakers), and the social sustainability of technological initiatives is not sufficiently explored. Against this background, this paper aims to analyze the ethical challenges associated with the use of AI in smart cities development projects. The “black-box” functioning of AI tools and the related privacy concerns will be discussed, with a focus on identifying sound solutions for an ethical use of AI in smart cities. Our results show that the eXplainable AI (XAI) approach enhances transparency, trust, control, efficiency, fairness, ethical compliance, accountability, bias mitigation, privacy, and security of AI in smart cities, and a responsible AI implementation implies diverse privacy techniques like encryption, differential privacy, anonymization, edge computing, multi-party computation, federated learning, machine learning, and blockchain.

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