When floods tore through parts of Bangladesh last year, families had little time to react.
In some communities, water rose so quickly that parents were forced to make impossible decisions in a matter of minutes: which children to carry first, which belongings to leave behind, whether to stay and protect what they owned or flee before roads became impassable.
By the time humanitarian responders arrived, many families had already lost homes, livelihoods and any sense of stability.
What makes stories like these so heartbreaking is that while natural hazards are not always avoidable, many of their worst human consequences are.
The warning signs were there: weather patterns, flood modelling, local vulnerability data, population movement trends. The world increasingly possesses extraordinary amounts of information that can help us understand where crises are likely to emerge and which communities are least equipped to withstand them.
Yet too often, that information exists in fragments.
Governments may hold climate forecasts, humanitarian agencies track displacement, development institutions map poverty and infrastructure gaps and private companies possess powerful analytical tools. But these systems still too often operate separately, despite serving the same communities.
The result is a familiar pattern: We respond after disaster strikes rather than acting early enough to reduce the damage.
This is where artificial intelligence (AI) could fundamentally change how we protect vulnerable communities.
When used responsibly, AI can help connect enormous volumes of data and identify patterns that humans alone would struggle to process quickly enough. It can strengthen early warning systems and help governments anticipate displacement linked to floods, droughts or conflict before people are forced to flee. It can help humanitarian agencies coordinate faster during emergencies and reduce wasteful duplication.
Source: Korea Times News
