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Cutting through Environmental Issues: Technology as a Double-Edged Sword
... Given the more limited set of hits, all WoS search results were examined, but results from Google Scholar were further narrowed down by period of publication (2008-2024), language (English), and prioritizing peer-reviewed papers. I made exceptions for a few older references [5,45] that were found to be great or unique examples of dyads. The first usage of "risk cascade" outside biology and on systemic risk outside finance was found in the work of German scholar Dirk Helbing in 2012-2013 [54,55]. ...
... TechNat Energy technology's emission challenges began with the Industrial Revolution [5] 2001 ...
Re-reading the risk literature, I sketch a novel nomenclature for 36 dyadic risk interactions that constitute the prototypes of what eventually become cascading effects. This analysis demonstrates where cascading risk effects originate and also hints at how they get their enormous power. Risk dyads derive from basic first-order interactions across six disruptive forces: sci-tech, governance, economics, social dynamics, ecological impact, and health adversity. I give brief examples of each and provide a short case description of six of the most prominent dyads. Very few of these dyads have an existing shorthand. The exception is NaTech, which denotes natural disasters being amplified by, or amplifying industrial risk, or now more broadly, sci-tech-derived risk. By generalizing the NaTech-style nomenclature across domains, I aim to provide the basic building blocks for a precise understanding of contemporary risk mechanics. This step is often skipped by avid complexity scholars intent on first describing system-wide features. Yet, dyadic analysis is an important prerequisite for systemic understanding of complex cascading effects that depend on triadic or tetradic risk relationships. In reality, even if systemic, and existential risks, as they emerge in the twenty-first century, depend on a myriad of cascading effects, they cannot be fully understood simply by looking at the whole system and attempting to analytically ignore its constituent parts claiming to gain a better overview.
Development and environmental security are mostly considered contradictory principles. The post-Second World War period profoundly needed development but as its by-product the environmental stability was lost. Environmentalists and Ecological movements called for environmental justice. They emphasized the need for a quality environment not only for the present but also for the coming generations. Sustainable development thus evolved as a suitable developmental model. Towards the end of the 20th century there originated the human security paradigm, which advanced the idea of sustainable human development. This neologism proposed a people-centered developmental model without disregarding ecological concerns. Since the globe is in industry 4.0 and almost started to actively engage in industry 5.0, the sustainable human development model can function as a perfect mechanism to link both development and environmental security. In this perspective, this chapter focuses on a global policy design that promotes sustainable human development without endangering the environment.
This study examines human economic behavior and views on environmental perceptions using social identity theory to determine how human behavior could impact the outcomes of alternative courses in the future in relation to the environmental crisis. Alternative economic scenarios for the future include growth, unsustainable growth, transformation, and downfall scenarios. The future will be shaped by high uncertainty and the influence of megatrends. Analyzing data which originate form field research conducted from 2019 to 2020 in Greece, we locate through principal components analysis, the variables that influence environmental preferences and, thus, the alternative future scenarios. We find that environmental behavior depends on “life variables” with long-term characteristics and effects. We conclude that environmental preferences comprise a broader and more sophisticated post-materialistic portfolio of attitudes within a wider social identity framework. Policymaking suggestions are designed to promote environmental sustainability for a preferable future.
Many emerging technologies have aspects of General Purpose Technologies (GPTs). However, true GPTs are rare and hold potential for large-scale economic impact. Thus, it is important for policymakers and managers to assess which emerging technologies are likely GPTs. We describe an approach that uses data from online job ads to rank emerging technologies on their GPT likelihood. The approach suggests which technologies are likely to have a broader economic impact, and which are likely to remain useful but narrower enabling technologies. Our approach has at least 5 years predictive power distinct from prevailing patent-based methods of identifying GPTs. We apply our approach to 21 different emerging technologies, and find that a cluster of technologies comprised of machine learning and related data science technologies is relatively likely to be a GPT.
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