From SARS to COVID-19: Digital infrastructures of surveillance and segregation in exceptional times

Simulated Misuse of Large Language Models and Clinical Credit Systems

Large language models (LLMs) have been proposed to support many healthcare tasks, including disease diagnostics and treatment personalization. While AI may be applied to assist or enhance the delivery of healthcare, there is also a risk of misuse. LLMs could be used to allocate resources based on unfair, inaccurate, or unjust criteria. For example, a social credit system uses big data to assess "trustworthiness" in society, punishing those who score poorly based on evaluation metrics defined only by a power structure (corporate entity, governing body). Such a system may be amplified by powerful LLMs which can rate individuals based on multimodal data - financial transactions, internet activity, and other behavioural inputs. Healthcare data is perhaps the most sensitive information which can be collected and could potentially be used to violate civil liberty via a "clinical credit system", which may include limiting or rationing access to standard care. This report simulates how clinical datasets might be exploited and proposes strategies to mitigate the risks inherent to the development of AI models for healthcare.

Spatial-temporally and industrially heterogeneous effects of new infrastructure construction on fostering emerging industries in Chinese cities

New infrastructure construction stemming from the new waves of technological revolution worldwide is exemplified by 5G base stations, big data centers, and ultra-high voltage. It has aroused extensive academic and policy interests in recent years, especially due to its beneficial role in empowering regional novel economic dynamics. However, this argument is still too general to capture the nuanced effects of new infrastructure construction on fostering emerging industries in specific spatial-temporal and industrial contexts, which is left for geographers to take up. This paper focuses on the spatial-temporally and industrially heterogeneous effects of new infrastructure construction on fostering four distinctive emerging industries in major Chinese cities over the last decade. It reveals that new infrastructure construction and emerging industries have experienced rapid development in major Chinese cities, with geographical agglomeration in national central cities with advanced economic development level. It is empirically demonstrated that new infrastructure construction can facilitate the development of emerging industries in major Chinese cities, while significant spatial-temporal heterogeneity characterizes the contributory forces. Furthermore, artificial intelligence as a Key Enabling Technology, robotics as a kind of hardware-featured industry, software-as-a-service as a software-centered industry, and blockchain as a networking-oriented industry vary markedly in the extent and the ways in which they benefit from new infrastructure construction, and they consequently exhibit industrial sensitivity to spatial-temporal heterogeneity in the fostering effects.

The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities

The COVID-19 pandemic has resulted in cities implementing lockdown measures, causing unprecedented disruption (e.g. school/shop/office closures) to urban life often extending over months. With the spread of COVID-19 now being relatively contained, many cities have started to ease their lockdown restrictions by phases. Following the phased recovery strategy proposed by the UK government following the first national lockdown, this paper utilises Greater London as its case study, selecting three main reopening measures (i.e., schools, shops and hospitality reopening). This paper applies sentiment analysis and topic modelling to explore public opinions expressed via Twitter. Our findings reveal that public attention towards the reopening measures reached a peak before the date of policy implementation. The attitudes expressed in discussing reopening measures changed from negative to positive. Regarding the discussed topics related to reopening measures, we find that citizens are more sensitive to early-stage reopening than later ones. This study provides a time-sensitive approach for local authorities and city managers to rapidly sense public opinion using real-time social media data. Governments and policymakers can make use of the framework of sensing public opinion presented herein and utilise it in leading their post-lockdown cities into an adaptive, inclusive and smart recovery.

The Impact of Digital Economy on the Economic Growth and the Development Strategies in the post-COVID-19 Era: Evidence From Countries Along the "Belt and Road"

The digital economy is considered as an effective measure to mitigate the negative economic impact of the Corona Virus Disease 2019 (COVID-19) epidemic. However, few studies evaluated the role of digital economy on the economic growth of countries along the "Belt and Road" and the impact of COVID-19 on their digital industries. This study constructed a comprehensive evaluation index system and applied a panel data regression model to empirically analyze the impact of digital economy on the economic growth of countries along the "Belt and Road" before COVID-19. Then, a Global Trade Analysis Project (GTAP) model was used to examine the impact of COVID-19 on their digital industries and trade pattern. Our results show that although there is an obvious regional imbalance in the digital economy development in countries along the "Belt and Road", the digital economy has a significantly positive effect on their economic growth. The main impact mechanism is through promoting industrial structure upgrading, the total employment and restructuring of employment. Furthermore, COVID-19 has generally boosted the demand for the digital industries, and the impact from the demand side is much larger than that from the supply side. Specifically, the digital industries in Armenia, Israel, Latvia and Estonia have shown great growth potential during the epidemic. On the contrast, COVID-19 has brought adverse impacts to the digital industries in Ukraine, Egypt, Turkey, and the Philippines. The development strategies are proposed to bridge the "digital divide" of countries along the "Belt and Road," and to strengthen the driving effect of the digital economy on industrial upgrading, employment and trade in the post-COVID-19 era.