This piece captures precisely what I’ve tried to teach my students for years: AI is not cognition outsourced, it’s cognition amplified through reflection. You’re right that the real intelligence emerges in the feedback loop, the act of refining, revising, and interrogating your own reasoning through a machine interlocutor. In cognitive science terms, this is “extended mind theory” in practice: intelligence doesn’t live solely inside the skull, it emerges through our interaction with the environment, and AI is now the most complex mirror that environment has ever offered. Your point about friction being essential to thought resonates deeply; in computation, there’s an old rule too little resistance and the signal drowns in its own noise.
I often ask my students: when you use an AI, are you shaping the algorithm, or is it quietly shaping you? How do you preserve your intellectual fingerprint when the machine begins to learn your rhythm? I remember early in my career testing a primitive language model on my own research notes it reorganized them so elegantly that I momentarily believed I’d improved as a thinker. Then I realized: it hadn’t changed me, only my mirror. The insight was humbling and liberating. So I’ll pose one final question: what practices can we adopt to ensure AI remains a partner in our becoming, not the author of our conclusions?
That's exactly how I feel about AI. It's been a great help in helping define what I understand and what could make it clearer, more engaging and more in my voice.
This piece captures precisely what I’ve tried to teach my students for years: AI is not cognition outsourced, it’s cognition amplified through reflection. You’re right that the real intelligence emerges in the feedback loop, the act of refining, revising, and interrogating your own reasoning through a machine interlocutor. In cognitive science terms, this is “extended mind theory” in practice: intelligence doesn’t live solely inside the skull, it emerges through our interaction with the environment, and AI is now the most complex mirror that environment has ever offered. Your point about friction being essential to thought resonates deeply; in computation, there’s an old rule too little resistance and the signal drowns in its own noise.
I often ask my students: when you use an AI, are you shaping the algorithm, or is it quietly shaping you? How do you preserve your intellectual fingerprint when the machine begins to learn your rhythm? I remember early in my career testing a primitive language model on my own research notes it reorganized them so elegantly that I momentarily believed I’d improved as a thinker. Then I realized: it hadn’t changed me, only my mirror. The insight was humbling and liberating. So I’ll pose one final question: what practices can we adopt to ensure AI remains a partner in our becoming, not the author of our conclusions?
That's exactly how I feel about AI. It's been a great help in helping define what I understand and what could make it clearer, more engaging and more in my voice.