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1 – 3 of 3Sumathi Annamalai and Aditi Vasunandan
With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress…
Abstract
Purpose
With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.
Design/methodology/approach
We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.
Findings
This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.
Originality/value
This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.
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Kevin Wang and Peter Alexander Muennig
The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.
Abstract
Purpose
The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.
Design/methodology/approach
This study is a narrative review of the literature.
Findings
The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.
Originality/value
While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.
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Using COVID-19 pandemic as a more immediate empirical reference, this paper aims to understand the biosecurity risks arising from tourist activities and, through a more…
Abstract
Purpose
Using COVID-19 pandemic as a more immediate empirical reference, this paper aims to understand the biosecurity risks arising from tourist activities and, through a more prospective analysis, to consider the relevance of public health issues in the context of tourism-sustainability nexuses.
Design/methodology/approach
The text assumes a hybrid format, incorporating elements resulting from empirical research and essayistic viewpoints. The collection of empirical elements was based on documental research in several sources, such as newspapers, international institutions of an intergovernmental nature and the discussion forum of the travel platform TripAdvisor.
Findings
By assuming mobility and large agglomerations of people from different origins, mass tourism has fostered multiple outbreaks of COVID-19 and the rapid global spread of contagion chains. The pandemic clearly exemplified the responsibility of tourism in the dispersion of biotic agents with severe ecological, economic, social and public health repercussions. It is, therefore, urgent to rethink the tourism growth trajectory and more effectively consider the biosecurity risks associated with mobility in discussions on tourism and sustainability. At the same time, tourism must be delineated in terms of the great aims of sustainability, and this transversal purpose to which it contributes should be considered an intrinsic condition of its own sectorial sustainability as an economic activity.
Originality/value
The biosecurity challenges posed by mass tourism are a very topical issue, still little considered in sustainability policies and on which there is a marked deficit in scientific research.
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