In 2018, there were 281 climate-related and geophysical events recorded in the International Disaster Database (EM-DAT). It is estimated that these events caused the deaths of 10,733 people across the world, impacting some 61 million people. Last year saw a rise in seismic activity in Indonesia, in particular. Add to that a string of disasters in Japan and India, including flooding and increased volcanic activity – culminating in more deaths than the previous 18 years combined from this activity alone. The World Bank is researching how it can use data and machine learning algorithms to predict certain types of disasters, and improve recovery in their aftermath, says Vivien Deparday, Disaster Risk Management Specialist at the Bank's Global Facility for Disaster Risk Reduction.

Recently, the regions around the Dead Sea in Jordan were flooded, causing the death of 21 children who were on a school trip, and injuring 35 more. Such disasters affect millions of people every year and cause property damage worth hundreds of billions. In 2017 alone, almost 335 natural disasters have affected more than 95.6 million people, and killed 9,697, costing around US $335 billion. But, the impact of these phenomena can be reduced if we were able to predict their occurrence. AI-powered systems can already predict the prices of stocks, which involve the analysis of numerous variables.