Human agency is the ability to direct our own thinking. It\u2019s not just a philosophical construct; it\u2019s the everyday act of deciding what to learn, what to believe, and when to stop and think before accepting an answer. Agency is what keeps us from running on cognitive autopilot.<\/p>\n
Artificial intelligence<\/a> now offers to do much of that work for us. With a single prompt, we can receive elegant summaries and polished solutions that are so smooth and immediate that they can (and often do) lull us into submission. If we aren\u2019t careful, we risk becoming passengers in our own intellectual journey, letting the machine set the course.<\/p>\n But I think there\u2019s another way to see this. AI can also be the ultimate training partner, a sparring partner for the mind that forces us to level up. The essential challenge is to keep agency at the center of the interaction and to make sure we are directing the conversation rather than outsourcing it.<\/p>\n Agency as the New Literacy<\/p>\n Critical thinking has always been the backbone of education<\/a>, but in the age of AI, it needs a serious upgrade. It\u2019s no longer enough to simply \u201ccheck sources\u201d or avoid misinformation. Agency means going further to help us decide which questions matter, shaping the direction of inquiry, and perhaps most importantly, staying engaged even when the machine\u2019s answer seems more than good enough.<\/p>\n Drexel University professor Michael Wagner<\/a> recently offered a helpful framework<\/a> in his blog by presenting the \u201cFour Lenses of Critical Engagement.”<\/p>\n These aren\u2019t academic exercises; they\u2019re survival skills. They are how we keep authorship of our thoughts in an era when AI can generate the brilliant illusion<\/a> of cognitive theater. <\/p>\n Iterative Intelligence and Learner-Centricity<\/p>\n This challenge sits at the heart of what I\u2019ve called iterative intelligence<\/a>. It’s the ability to learn, test, refine, and learn again in a dynamic loop. AI excels at iteration, but the learner must stay in control of the loop. And that\u2019s where agency becomes essential.<\/p>\n Education in the AI era should be learner-centric<\/a>, not machine-centric. The best question isn\u2019t \u201cWhat can AI do for me?\u201d but \u201cWhat do I want to think about and how can AI help me think about it better?\u201d When a student uses AI to explore multiple perspectives on a problem, ask \u201cwhat if?\u201d questions, and challenge the outputs they receive, they are exercising agency. When they simply accept the first answer, they surrender it.<\/p>\n The Risk of Cognitive Abundance<\/p>\n There’s also a fascinating paradox here. We live in a time of cognitive abundance\u2014a term that is often leveraged<\/a> as a transformative outcome\u2014and never before has it been so easy to access so many ideas so quickly. But abundance can have a dulling effect. When knowledge is cheap, we can lose the desire to search for it and, in the final analysis, make it our own.<\/p>\n The key point here is that agency is the antidote. It\u2019s what turns abundance into opportunity rather than overwhelming us. It\u2019s the skill that keeps learning active rather than passive, and thinking uniquely generative rather than derivative.<\/p>\n The Seduction of the Asymptote<\/p>\n AI doesn\u2019t just answer our questions; it just moves closer and closer to sounding exactly like us. And that’s worth reading again. Each iteration brings it nearer to the curve of human thought, so close that the difference becomes nearly imperceptible.<\/p>\n\n