As a teenager, I remember learning in school how maps often displayed the biases of those that made the maps themselves. It was odd to me that something as seemingly scientific as showing where and to what scales countries and continents were located could be so influenced by bias. I remember also thinking how outdated traditional ‘maps’ were and thinking (wrongly) that map-making was a dead profession.
Obviously I was wrong about the map making; map-making has transformed due to AI and is now perhaps more important than ever. AI, along with increasing connectivity, is now helping map the world in new and impactful ways. One way in particular I would like to focus on here is that of natural disaster prediction and prevention.
Most scientists would agree at this point that natural disasters are not only increasing in frequency, but magnitude as well. What accompanies this unsettling trend of natural disaster is a wake of increased human disaster in the form of famine, displacement, disease, and general human suffering. Many political scientists would argue that a good few of the world’s worst wars and conflicts are somehow caused by natural disasters (and subsequent fights over scarce resources)
So where do maps fit into this equation? Maps are getting a reboot from AI, making them more specific and useful than just figuring out how to get from A to B. As connectivity increases, so too does the ability for anyone anywhere to broadcast where they are and what they see. This will give us so much data we would scarcely know what to do with it if it weren’t for AI.
AI as our ‘mining’ tool can help turn raw, mass information into logical maps not only responding to natural disasters happening in the present time, but also mapping how these natural disasters are progressing and who will most likely be affected by it. Better yet, we are learning from natural disasters themselves to help better predict where natural disasters will strike, when, and who/what will be impacted.
This article on Singularity Hub goes into even more depth of what AI is doing to map natural disasters, and what the future of mapping looks like with AI, robots, and the spatial web. While modern technology is truly revolutionizing mapping, one thing that hasn’t changed is the human side to mapping. Humans are an integral part of programming AI and choosing what gets prioritised based on the information given by AI. Just as maps in the 1800s reflected the biases of the cartographer drawing it, so too can maps created by AI reflect the biases of those directing it. In the future, it will be important to ‘map’ how these biases affect AI created maps.
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