"When information was scarce, attention mattered. We learned to notice and infer because we had no choice. When mistakes were costly, our judgment slowed because a wrong decision could have significant consequences or even impact survival itself. When feedback was delayed, reflection and analysis became essential. And when outcomes were irreversible, this curiously human thing called responsibility followed. It's important to recognize that these limits did not hinder intelligence; they shaped it."
"Artificial intelligence is usually framed as this story of acceleration. Intelligence gets faster and better. In this context, AI-and eventually artificial general intelligence-represents an amplification of human cognition. Well, sorta. That framing misses a subtle, potentially more consequential shift already underway. The most important change introduced by advanced AI may not be how intelligent our systems become, but the conditions under which intelligence now operates."
Human thought historically thrived under constraints: scarce information, costly errors, delayed feedback, and irreversible outcomes. These constraints demanded attention, slower judgment, reflection, and a sense of responsibility, which shaped deep, consequence-aware intelligence. Advanced AI introduces the opposite regime: vast data, fast answers, and low-cost errors that can produce fluent but unearned confidence. AI's speed amplifies capabilities but strips away the consequence-bearing context that fosters careful judgment. As a result, AI can produce confident outputs without risk ownership, making human intelligence—grounded in responsibility and error-cost sensitivity—still essential for high-stakes decisions.
Read at Psychology Today
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