Bring digital twins back to Earth

被引:2
|
作者
Saltelli, Andrea [1 ,2 ]
Gigerenzer, Gerd [3 ]
Hulme, Mike [4 ]
Katsikopoulos, Konstantinos V. [5 ]
Melsen, Lieke A. [6 ]
Peters, Glen P. [7 ]
Pielke, Roger [8 ]
Robertson, Simon [9 ]
Stirling, Andy [10 ]
Tavoni, Massimo [11 ]
Puy, Arnald [12 ]
机构
[1] UPF Barcelona Sch Management, Carrer Balmes 132, Barcelona 08008, Spain
[2] Univ Bergen, Ctr Study Sci & Humanities, Bergen, Norway
[3] Max Planck Inst Human Dev, Berlin, Germany
[4] Univ Cambridge, Dept Geog, Cambridge, England
[5] Univ Southampton, Optoelect Res Ctr, Southampton, England
[6] Wageningen Univ, Hydrol & Environm Hydraul, Wageningen, Netherlands
[7] CICERO Ctr Int Climate Res, Oslo, Norway
[8] Univ Colorado, Boulder, CO USA
[9] Univ New South Wales, Kensington, Australia
[10] Univ Sussex, Sci Policy Res Unit, Brighton, England
[11] Politecn Milan, Sch Management, Milan, Italy
[12] Univ Birmingham, Sch Geog Earth & Environm Sci, Birmingham, England
基金
英国科研创新办公室;
关键词
digital twins of the Earth system; ethics of quantification; machine learning; mathematical modeling; sociology of quantification; UNCERTAINTY; SCIENCE; POLICY;
D O I
10.1002/wcc.915
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We reflect on the development of digital twins of the Earth, which we associate with a reductionist view of nature as a machine. The projects of digital twins deviate from contemporary scientific paradigms in the treatment of complexity and uncertainty, and does not engage with critical and interpretative social sciences. We contest the utility of digital twins for addressing climate change issues and discuss societal risks associated with the concept, including the twins' potential to reinforce economicism and governance by numbers, emphasizing concerns about democratic accountability. We propose a more balanced alternative, advocating for independent institutions to develop diverse models, prioritize communication with simple heuristic-based models, collect comprehensive data from various sources, including traditional knowledge, and shift focus away from physics-centered variables to inform climate action. We argue that the advancement of digital twins should hinge on stringent controls, favoring a nuanced, interdisciplinary, and democratic approach that prioritizes societal well-being over blind pursuit of computational sophistication. This article is categorized under: Climate Models and Modeling > Earth System Models Climate Models and Modeling > Knowledge Generation with Models Climate, History, Society, Culture > Disciplinary Perspectives
引用
收藏
页数:10
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