Computational Socioeconomics: A data-driven framework for quantifying progress towards achieving the Sustainable Development Goals (SDGs)

Abstract

The improvements in data acquisition and processing capabilities, as well as artificial intelligence and statistical mechanics, have rapidly and significantly changed the methodology of social and economic research. The recent paradigm shifting of social science driven by big data and artificial intelligence provides promising and novel data-driven methods for measuring the progress of Sustainable Development Goals (SDGs). This shift affects areas ranging from no poverty to good health and well-being, from gender equality to quality education, and from economic growth to innovation and infrastructure. Governments at both national and regional levels can benefit from leveraging new methods under the framework of Computational Socioeconomics to better assess their progress towards sustainable development over space and time with a higher efficiency and a lower cost.

Publication
Future Cities, New Economy, and Shared City Prosperity Driven by Technological Innovations