History fills with global infernos sparked by small moments. In 1618, two governors threw themselves out of a window in Prague, starting the Thirty Years’ War. In 1914, an archduke’s driver took a wrong turn in Sarajevo and sparked WWI. The Arab Spring was ignited by a dispute with just one vendor in Tunisia, even in the digital age.
Looking back, we can see the warning signs. The challenge has always been knowing which spark will catch. Now, in 2026, scientists pose a bold question: might artificial intelligence serve as the crystal ball we have always sought?
1. History as Data: The World History Lab
Complexity scientists like Peter Turchin at Oxford University’s World History Lab are treating the past like a massive data set. Over the past ten years his team has amassed more than 80,000 data points, ranging from the fall of Ancient Rome to the dissolution of the Habsburg Empire.
The Dark Triad of the Social Illness:
Turchin’s group uses predictive models to assess when a society is at risk of collapse. They found that revolutions typically arise out of three basic causes:
Falling Living Standards. This happens when the average person becomes much poorer.
Elite Overproduction: An excess of candidates competes for limited top positions in governance.
Fiscal Crisis: When the state itself has no money to maintain its infrastructure.
Interestingly, Turchin used these same methods in 2010 to predict that 2020 would be an intense period of instability. His “cliodynamics” (mathematical study of history) seemed eerily prescient after a global pandemic and historic political turmoil.
2. AI in Action: Satellites to Social Media
Predicting the future is not just a matter of reading history books. It is about real-time intelligence. Secretive projects like Raven Sentry have used AI to predict attacks in conflict zones with almost 70% accuracy.
The modern AI models now digest the following:
Satellite images: to watch the movements of missiles in their sites or the output of an industry.
Business Deals: Local economic turmoil precedes unrest.
Social Media Sentiment: Real-time “temperature” measurement of a population.
3. The threat of “Shadow Banking”
And it’s not just wars. It’s our wallets. Financial regulators are now using AI to map the “shadow banking” system – trillions of dollars’ worth of wealth that exists outside of traditional regulation.
And recent AI models, trained on 20 years of portfolio data, have shown to be 10 times better at predicting which investors would trigger a market downturn in a crisis than traditional economic theories. Instead of guessing, regulators can now see exactly where the “ripples” will become “tidal waves”.
4. The ‘Black Swan’ Challenge
But the Alan Turing Institute and other experts caution against the hype. AI is excellent at finding patterns. But it has a problem with “Black Swan” events. These are truly random one-off events that have never happened before.
Also, human behaviour is notoriously fickle. No algorithm has yet learned how to predict the mind-set of a world leader. Today’s AI is more “conservative” than human analysts, typically underestimating how quickly a person might choose to escalate a conflict.
The Verdict: A Supplement, Not a Substitute
AI in 2026 is not going to replace human judgement, but it is providing us with a much-needed “early warning system.” Whether it’s deploying rescue efforts more precisely after an earthquake or identifying a looming financial bubble, AI helps us see the patterns we are too close to notice.
Is AI our new crystal ball? Maybe not. But it’s the best radar we’ve ever had.
