"In our rush to create artificial minds, we seem to have forgotten to study the real ones. Because once you start noticing the intelligence threaded through the natural world, you realize that the planet is already saturated with superintelligent systems. We just don't recognize them because they don't use language or wear lab coats or hoodies. To me, water possesses intelligence: the way it adapts to its container, negotiates obstacles, carves canyons given enough time."
"Over the last few years, AI has dazzled us all. It can write our emails, optimize our workflows, and create alarmingly realistic videos. But is it intelligent? Can it actually understand things? I'm not so sure. This week, I published an essay for my Long Game column in Big Think about this idea. To do that, I tell a story about a slime mold that might just be more "intelligent" than a human - even though it has no brain. (No, I haven't lost my marbles yet; read it and you'll understand.)"
"The basic premise is this: the world is pouring incomprehensible amounts of energy and capital into building systems that mimic a single, narrow form of human intelligence. But in the process, we may be ignoring a far older, and potentially wiser, form of intelligence. It's also a type of intelligence that is in high demand as the world changes faster than ever."
Artificial systems have advanced rapidly and automate many tasks, but their understanding may be narrow and limited. Natural systems demonstrate distributed intelligence through adaptation, resource sharing, and environmental problem-solving without centralized brains. Water shapes environments by negotiating obstacles and carving canyons; slime molds solve problems collectively; trees share nutrients, warn neighbors, and modulate growth. Large investments focus on replicating a narrow human form of intelligence while older, resilient forms of intelligence remain understudied. Studying biological and decentralized intelligence could inform more adaptable, robust approaches as the world changes rapidly.
Read at Big Think
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