The lesser of two evils: Assessing the public acceptance of AI thermal facial recognition during the COVID-19 crisis

AI thermal facial recognition (AITFR) has been rapidly applied globally in the fight against Coronavirus disease 2019 (COVID-19). However, AITFR has also been accompanied by a controversy regarding whether the public accepts it. Therefore, it is necessary to assess the acceptance of AITFR during the COVID-19 crisis. Drawing upon the theory of acceptable risk and Siegrist's causal model of public acceptance (PA), we built a combined psychological model that included the perceived severity of COVID-19 (PSC) to describe the influencing factors and pathways of AITFR acceptance. This model was verified through a survey conducted in Xi'an City, Shaanxi Province, China, which collected 754 valid questionnaires. The results show that (1) COVID-19 provides various application scenarios for AI-related technologies. However, the respondents' trust in AITFR was found to be very low. Additionally, the public appeared concerned about the privacy disclosure issue and the accuracy of the AITFR algorithm. (2) The PSC, social trust (ST), and perceived benefit (PB) were found to directly affect AITFR acceptance. (3) The PSC was found to have a significant positive effect on perceived risk (PR). PR was found to have no significant effect on PA, which is inconsistent with the findings of previous studies. (4) The PB were found to be a stronger mediator of the indirect effect of the PSC on ST induced by AITFR acceptance.

Security, Privacy and Risks Within Smart Cities: Literature Review and Development of a Smart City Interaction Framework

The complex and interdependent nature of smart cities raises significant political, technical, and socioeconomic challenges for designers, integrators and organisations involved in administrating these new entities. An increasing number of studies focus on the security, privacy and risks within smart cities, highlighting the threats relating to information security and challenges for smart city infrastructure in the management and processing of personal data. This study analyses many of these challenges, offers a valuable synthesis of the relevant key literature, and develops a smart city interaction framework. The study is organised around a number of key themes within smart cities research: privacy and security of mobile devices and services; smart city infrastructure, power systems, healthcare, frameworks, algorithms and protocols to improve security and privacy, operational threats for smart cities, use and adoption of smart services by citizens, use of blockchain and use of social media. This comprehensive review provides a useful perspective on many of the key issues and offers key direction for future studies. The findings of this study can provide an informative research framework and reference point for academics and practitioners.

Modelling and analysis of factors for implementation of smart cities: TISM approach

Purpose

The concept of “Smart Cities” is gaining prominence across the world as a solution to effectively address the issues or impediments faced by cities due to rapid urbanization. The purpose of this paper is to identify the key factors which form the primary basis for the implementation of “Smart Cities”. Particularly, this paper aims to analyse the contextual relationship and driving/dependence power of these key factors and model these using the total interpretive structural modelling (“TISM”) framework.

Design/methodology/approach

The key factors which form the basis for the implementation of Smart Cities were identified through an evaluation of the literature on “Smart Cities” and expert opinions. Thereon, the contextual relationship between these key factors was examined with the help of experts. Thereafter, these key factors were modelled using the total interpretive structured modelling (“TISM”) framework. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was further applied to classify the factors. It is pertinent to note that the driving power and dependence of these key factors were also reviewed.

Findings

This paper establishes a TISM of the key factors for the implementation of “Smart Cities” which will aid in examining the interrelationship among the factors and will also identify the hierarchy among these factors. On extensive examination of the literature and expert opinions on “Smart Cities”, it can be asserted through TISM that quality of life (F1), e-services adoption (F5) and economic growth (F8) are the leading factors in establishing “Smart Cities”. Furthermore, it must be noted that the MICMAC analysis and driving-dependence graph helps in classifying the key factors as autonomous factors, drivers, linkages and outcomes, which assists in comprehending which factors possess driver power and which are exhibiting dependency.

Originality/value

The contribution lies in the authentic manner in which this paper attempts to use the TISM approach combined with MICMAC analysis to model key factors for the implementation of “Smart Cities”; which would aid and assist policymakers and practitioners to construct a structural framework for the implementation of “Smart Cities” through identification of drivers, linkages and outcomes.

The State of Smart Cities in China: The Case of Shenzhen

China is at the midpoint of its urbanisation—the largest scale in human history. The recent smart city movement is influencing the discourse and practice of China’s urbanisation, with numerous cities claiming to build smart cities and/or adopting some forms of smart city strategies and initiatives. A so-called ‘latecomer’s advantage’ is being exploited to advance their pursuit for a smart city status, not only to catch up with overseas counterparts, but to overtake them and become international leaders. This local-level enthusiasm strikes a chord with the central government’s strategy of building an ‘innovative nation’ to drive its economic transformation towards a knowledge economy. This converging central-local interest is creating a ‘smart city mania’ across the nation, which, however, has not received due attention in the international literature, and thus deserves critical examination and reflection to inform policy debates. To address this gap, this study investigates the state of smart cities in China, based on a case study of Shenzhen, China’s fastest-growing, experimental city. Shenzhen grew from a fishing village into an international metropolis in 40 years, and has now won a nickname of ‘China’s Silicon Valley’ or ‘China’s smartest city’. This study analyses the state of Chinese smart cities and the pursuit for a smart Shenzhen from the perspectives of the smart city as a concept, as an urban development paradigm, and as an urban regime, drawing upon the international smart city literature. It concludes that a technology-centric approach to smart cities in China, as illustrated by the Shenzhen case, have advanced innovation capacity and economic growth through capitalising on a ‘latecomer’s advantage’. However, this ‘latecomer’s advantage’ may translate into a ‘latecomer’s disadvantage’ for this approach’s lack of institutional adaptation, and for its insufficient attention to social and environmental problems covered under the shiny economic boom. This latecomer’s disadvantage is likely to impact the long-term sustainability of Chinese cities.

A Cross-Reading Approach to Smart City: A European Perspective of Chinese Smart Cities

The present study, after a literature review of the smart city definitions and ranking tools in Europe and in China, presents a cross-reading approach to the Chinese smart cities concept and implementation. It is indeed nowadays mandatory to re-convert cities in sustainable and smart ecosystems and this can be done with different approaches. In this frame, the role of ICT—the glue of the smart city concept—is central and pervasive. The Smart city model could be a way to reverse the actual trend of cities, re-defining an integrated approach between tangible and intangible infrastructures of cities. Future cities are influenced by two main different visions with different connotations that come along with the planning capacity and with the ability of countries to follow a coherent and sustainable development project. European approach for planning is quite consolidated and based on a long term holistic vision, while Chinese vision is catching up with the dramatic speed of urbanization, deploying critical infrastructures in most cases without a long-term view. On the other hand, Chinese projects are in some cases exemplary for Europe where many constraints and regulatory issues put a strong limitation on the many possible implementations.