Education Can't Ignore Human Psyche Anymore

Photo by Mina Rad on Unsplash

Schools usually teach decision-making as if students are identical rational machines processing the same inputs to reach predetermined outputs. This fantasy isn't just pedagogically bankrupt—it's now economically and societally dangerous.

Education obsesses over the research on learning, mostly on how well memorized information can be regurgitated, but that narrow focus ignores decades of research on cognitive biases, individual differences, and decision-making under uncertainty. There isn’t good research on how best to build creativity, critical thinking (i.e. judgment), collaboration skills and the other goals schools say they value most. Because those are topics that must consider individual differences; emotion and theory of mind are huge factors.

Most people struggle with empathy not because they lack compassion, but because they understand themselves too simply or not at all. The oversimplified models they apply to their own thinking get projected onto others, creating shallow, inaccurate assessments of human behavior. For example, educators often assume moral failure in students, or attribute far too much value to willpower but little to the factors that decrease motivation. Students using AI to do homework aren't valueless, but their values aren’t entirely those of the teacher. They're making rational cost-benefit analyses that schools refuse to acknowledge. If students do not think the content of the instruction is important, rightly or not, then they’re unlikely to retain it for long anyway. Every student knows that intuitively.

AI forces we reckon with ourselves. You’re not going to be wary of AI manipulation if you don’t understand the ways you can be duped. You won’t get how to fold AI into thinking processes if you don’t get how your baseline thinking works. Effective AI collaboration requires the very self-awareness schools avoid teaching. Adults who understand their cognitive patterns will manage AI or human teams far better than those who do not, and more constructively contribute to society.

The Academic Rationality Theater

The environment schools create emphasize content over insight. We know from decades of judgment science that System 1 (intuitive) and System 2 (deliberate) thinking both drive decisions, but schools pretend only deliberate reasoning matters. It teaches that problem solving should ignore the human aspects, to our peril. Students correctly assess that much academic work has no apparent real-world value. The "you'll need this someday" argument fails because immediate psychological realities—boredom, anxiety, competing priorities—aren't acknowledged as legitimate factors in student decision-making, nor that children are notoriously short-sighted.

Consider how schools approach AI accuracy assessment. They teach students to go back to the original research and do painstaking analysis that only researchers have time for. This isn’t bad to do, but highly incomplete. In real life the vast majority of information we receive can’t be researched; there’s not time for that. We must use intuition and heuristics. When schools do teach practical heuristics, they focus on source credibility: "Is this a reputable journal?" "Does this outlet have good fact-checking?" They completely ignore the bigger danger—that emotions and biases cause us to interpret the same information differently. A stressed student reads a study about academic pressure and sees validation for giving up. A confident student reads the same study and sees strategies for improvement. The source didn't change; the psychological lens did.

Schools seem to avoid teaching how stress, sleep, mood, and individual processing styles affect learning and decision-making. They teach research skills without addressing confirmation bias, motivated reasoning, or how emotional state influences what we notice and remember. Human beings don't process information like computers, but we educate them as if rational analysis is the only skill that matters.

This creates students who can follow academic protocols but can't recognize when their own mental state is distorting their judgment. They graduate unable to identify their cognitive blind spots or understand how others might see the same situation differently. The result is poor decision-making and shallow empathy.

Productivity Therapy, Not Clinical Therapy

In Wisdom Factories, I described Productivity Therapy as a critical bridge to more effective and safe human-AI collaboration. “Productivity” because I imagined it more as a new business role, but I also described the role as applied to schools. I defined it as a combination of "technology empathy, psychological awareness, task analysis, and performance measurement." It’s about understanding how your mind processes information, makes decisions, and how emotional states affect both.

My impression is that schools avoid this territory because they fear accusations of mental health overreach or crossing into family boundaries. But I’m not talking about treating mental health issues; that should be for psychologists. Students examining their emotional states and how those affect judgment isn't clinical intervention. Understanding you make worse decisions when stressed isn't therapy—it's practical self-knowledge. As is knowing when to direct energy toward detail and focus versus big picture and mind-wandering. Knowing your attention patterns throughout the day improves time management. Identifying your cognitive biases in action prevents costly mistakes.

Everyone needs to understand their cognitive strengths, blind spots, and emotional patterns. Students who can't recognize when anxiety is making them catastrophize or when excitement is making them overcommit will struggle in relationships, careers, and basic life decisions. Understanding emotions becomes essential for practical effectiveness in all contexts. Students learn to construct stories about how they behave and think—not for therapeutic insight, but because self-awareness drives better choices.

The boundary fears miss the point. School psychologists should still be the counselors. What I’m asking is to help students develop metacognition that includes emotional awareness.

AI Forces the Self-Awareness Reckoning

Working with AI demands precisely the self-awareness that education has been avoiding, making these skills immediately practical and economically valuable.

AI collaboration requires understanding your cognitive strengths and weaknesses to delegate effectively. Students must recognize their own biases and emotional states to prompt AI well and evaluate outputs critically. Someone who doesn't know they tend toward confirmation bias will use AI to confirm their existing beliefs rather than challenge them. Someone unaware of their perfectionist tendencies will get stuck in endless revision loops with AI instead of shipping work.

Practical examples emerge daily. Knowing when you need AI to check your work versus when you can trust your intuition becomes crucial. Understanding your creative versus analytical modes helps you choose the right AI tools at the right time. Recognizing when emotional state is affecting your judgment of AI outputs prevents both over-reliance and inappropriate dismissal.

Self-awareness is the foundation for both effective AI teamwork and genuine human empathy. Once students understand their own psychological complexity, they can begin to model others' minds with similar nuance.

AI can provide safe practice spaces for psychological self-discovery. Avatars allow testing social approaches without real-world consequences. Simulations let students explore decision-making under different emotional states. These tools can help students understand patterns in their thinking and behavior that would take years to recognize through experience alone.

Ethan Mollick has said "AI use that boosts individual performance does not naturally translate to improving organizational performance." He describes the gulf as ignorance about how things work now and the difficulty of imagining it differently. It is the business aspects he focuses on. But we should not assume individual performance boosts because of the psychological issues I have mentioned, never mind the general AI skill barrier. Nor that organizational change is emotionally neutral.

Then there are the safety issues. People who understand themselves will be the ones managing AI systems. Those who don't will be managed by them.

---

Schools can continue pretending students are uniform processing machines, or embrace systematic approaches that teach students to understand and leverage their unique cognitive and emotional architectures.

Students who understand how their minds work, including their emotional patterns and biases, will be the ones who can effectively collaborate with AI systems and genuinely empathize with other human beings.