Predicting the next global crisis: Can AI be the crystal ball we need? It's a question that has intrigued researchers and policymakers alike. History is replete with examples of events that, in hindsight, seem to have been predictable. From the East German official's misstep that hastened the end of the Cold War to the Tunisian fruit seller's self-immolation that sparked the Arab Spring, there are warning signs that precede these triggers. But in many cases, these signs are difficult to discern, and the challenge is knowing which spark will catch. This is where artificial intelligence (AI) comes in. AI technology is already providing hints of what might be possible in predicting future crises. Using the past to predict the future is not a new concept. In the first half of the 20th Century, Russian-American sociologist Pitirim Sorokin pioneered a data-led approach to explain why past empires imploded. Today, complexity scientist Peter Turchin is upholding the spirit of Sorokin's work at Oxford University's World History Lab. Turchin and his team have amassed 80,000 pieces of qualitative and quantitative data from societies stretching back to Palaeolithic times. They use this data to propose hypotheses about why moments of crisis arise, such as revolutions stemming from a confluence of factors including parts of the population becoming poorer and a growing number of elites vying for a limited number of ruling positions. Turchin's team has used their database to predict that 2020 would be particularly chaotic, and their methods have been validated by recent events. However, critics like anthropologist David Graeber have cast doubt on the notion that we might be able to use history to predict the future, pointing out that random, one-off 'Black Swan' events are impossible to predict. Nevertheless, governments and the military have already shown interest in this field. In 2020, a secretive US intelligence project used an AI called Raven Sentry to predict attacks from the Taliban in Afghanistan with 70% accuracy. Other researchers are developing neural networks aimed at predicting food crises, and the United Nations Development Programme is already deploying AI to help it assess the impact of major disasters and events. Financial regulators are also hoping AI can give them a headstart on potential problems. However, the UK's Alan Turing Institute for AI has concluded that, on the whole, AI-driven prediction technology is probably not quite there yet. The challenge is getting the right AI training data to predict future conflicts, as information sits in fragmented places around the intelligence community. Despite these challenges, the potential for AI to predict future crises is an exciting prospect. As AI technology continues to evolve, it may one day be able to provide the crystal ball we need to anticipate and prepare for the next global crisis.
