Steering open-source AI to accelerate the sustainable development goals
Min Chen (Nanjing Normal University)
Kai Wu (Nanjing Normal University)
Prajal Pradhan (University Medical Center Groningen, Potsdam-Institut für Klimafolgenforschung)
Cameron Allen (Monash University, University of New South Wales)
Stefano Nativi (IMAMOTER - C.N.R. Sensors and Nanomaterials Laboratory)
Klaus Hubacek (University Medical Center Groningen)
Alexey Voinov (University of Twente)
Felix Creutzig (University of Sussex, Potsdam-Institut für Klimafolgenforschung)
Tatiana Filatova (TU Delft - Technology, Policy and Management, TU Delft - Technology, Policy and Management)
Niklas Boers (University of Exeter, Potsdam-Institut für Klimafolgenforschung, Technische Universität München)
Michael Meadows (Nanjing University, University of Cape Town)
Peilong Ma (Nanjing Normal University)
Frank Biermann (Universiteit Utrecht)
Hans Joachim Schellnhuber (International Institute for Applied System Analysis)
John Ludden (Krafla Magma Testbed)
Maria Paradiso (Università degli Studi di Napoli Federico II)
Michael Batty (The Alan Turing Institute, University College London)
Huadong Guo (International Research Center for Big Data for Sustainable Development Goals, Aerospace Information Research Institute)
Min Cao (Nanjing Normal University)
Peng Hou (Ministry of Ecology and Environment)
Guonian Lü (Nanjing Normal University)
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Abstract
While the artificial intelligence (AI) revolution is advancing rapidly, the open-source paradigm offers key pathways and potential risks for accelerating progress towards the Sustainable Development Goals and beyond. This comment introduces four governance actions that consider how sustainability, evaluation, safety, and cooperation can be integrated into the transformation of open-source AI, thereby reducing uncertainties and challenges posed by open-source AI for sustainable global prosperity.
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