The Boring Parts: Where Generative AI Actually Helps Cartographers
Daniel Huffman has collected use cases where generative AI tools could help with static map-making. Huffman focuses on the boring parts of cartography, the grunt work: tasks like label checking, georeferencing, extracting data from map images, or just finding data.
Daniel Huffman, somethingaboutmaps:
I think all of these examples point towards ways that genAI might make its way into some cartographic pipelines. I’m not a genAI champion, and I both respect and largely agree with people who decline to make use of it. But, I’ve also seen many folks using AI to make maps from scratch with a simple image generation prompt, and I don’t think that’s a useful example for professional mapmakers. For the cartographers that are excited to use these tools, I wanted to suggest constructive, practical directions.
Importantly, my suggested genAI uses (1) don’t significantly undercut the human creative aspect, (2) can easily be checked for errors, and (3) might actually save time and labor (if not now, probably soon).
It’s a balanced, clear-headed review of generative AI’s capabilities for a specific profession, demonstrating what works and what doesn’t.