Applications of Artificial Intelligence in Reconstruction Governance Lessons from Nepal Earthquakes

Abstract

This chapter examines achievements, challenges and other associated factors of reconstruction through an artificial intelligence (AI) lens after earthquakes of 2015. Plan and policy decisions were taken on the basis of information related to loss of life and property, damaged developmental infrastructures, banking information, citizens’ grievances, household survey and resurvey, geological survey and local bodies through the application of collaborative system model of AI. The study reveals that about 40 percent of reconstruction governance was completed, based on data gathered from 2015 to 2018, and remaining work was going on even though it was expected to be completed by 2019. It shows through application of AI that implementation of plans and policies of reconstruction governance had faced serious challenges to complete expected reconstruction works within stipulated time frame because of faulty institutional setup, vague plans and policies, financial resource gap, politicization, bureaucratic attitude, people’s sentiment attached to parental property and so on. Thus, reconstruction governance is based primarily on cognition of human elements despite many codes and standards developed for an appropriate application of AI.