In 2018 in Kerala in India, a person impersonating an Indian Army captain claimed in a video that a dam at the top of a valley was about to break. Thousands of people evacuated into the next valley - into the path of devastating flash floods.

In North Carolina after Hurricane Helene in 2024, statements by a presidential candidate that the only people getting federal aid were Democrat voters resulted in FEMA having to withdraw all of its workers from this Republican leaning state, after staff were confronted by fire arms and death threats.

In Australia, we see a standard bushfire disinformation playbook that prevents people evacuating, causes conflict at road blocks, and distress to communities.

But what if you could get ahead of it, to stop disinformation from spreading?

We are using inoculation theory, an oldie but goodie rediscovered and tested by the University of Cambridge’s Social Decision-Making Lab to help communities to recognise how they are being manipulated and also prebunk specific messages. They have been testing the process on vaccine, climate and political disinformation, with great results - on some specific disinfo messaging, a 75% reduction in belief!

Now we are applying this with AI and other data science capabilities to help emergency agencies prevent the worst from happening: just because some troll somewhere has discovered they can make money from posting false and bad information into disaster-affected communities

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