Insights and Next Practices for Today’s Educational Leaders

LEADERSHIP INSIGHT

Hargadon, S. (March 2026). What We Get Wrong About AI and Education.

SUMMARY

What We Get Wrong About AI and Education: Rethinking the Narrative

In a provocative and timely essay, Steve Hargadon challenges many of the dominant assumptions shaping how schools approach artificial intelligence. In “What We Get Wrong About AI and Education,” Hargadon argues that much of the current conversation is misguided—not because AI lacks importance, but because educators are focusing on the wrong questions.

Rather than centering the discussion on tools, efficiency, or even academic integrity, Hargadon urges educators to step back and reconsider the fundamental purpose of education in an AI-driven world. His central claim is that the real issue is not what AI can do, but what humans should do in response.

One of the most significant misconceptions he identifies is the belief that AI’s primary value lies in productivity. While AI can generate content, summarize information, and automate tasks, an overemphasis on efficiency risks undermining the deeper goals of education. If students rely too heavily on AI to complete work, they may bypass the very cognitive processes—struggle, reflection, and synthesis—that lead to meaningful learning.

Hargadon cautions against framing AI as either a threat or a solution. Both perspectives, he suggests, oversimplify the complexity of the moment. Treating AI as a threat leads to restrictive policies and fear-based responses, while viewing it as a solution encourages uncritical adoption. In both cases, schools risk losing sight of what matters most: developing thoughtful, capable, and ethical human beings.

A key insight from the article is the importance of intellectual agency. In an environment where AI can produce polished outputs instantly, the value of original thought becomes even more critical. Students must learn not just to use AI tools, but to question, evaluate, and refine the information those tools provide. This requires a shift from assigning tasks that emphasize completion to those that emphasize judgment and discernment.

Hargadon also highlights the danger of outsourcing thinking. When students use AI to generate answers without engaging deeply with the material, they may appear successful while missing essential learning opportunities. This concern echoes broader research on cognitive science, which shows that effortful thinking is necessary for long-term understanding. The ease of AI-generated responses can create an illusion of mastery without genuine comprehension.

Another important theme is the role of human connection in learning. Hargadon emphasizes that education is not simply about acquiring information; it is about dialogue, relationships, and shared inquiry. AI cannot replicate the nuanced, relational aspects of teaching—such as mentoring, questioning, and responding to student needs in real time. Schools must therefore prioritize experiences that foster collaboration, discussion, and authentic engagement.

For educators, this means designing learning experiences that go beyond what AI can easily produce. Tasks should require students to explain their reasoning, defend their ideas, and engage with multiple perspectives. These kinds of activities not only deepen understanding but also reinforce the uniquely human capacities that AI cannot replace.

For school leaders, the implications are profound. The integration of AI should not be driven by novelty or pressure to keep up with technological trends. Instead, it should be guided by a clear vision of teaching and learning—one that prioritizes thinking, agency, and human development.

KEY TAKEAWAYS

• Focus on Purpose, Not Tools: AI should not redefine the goals of education.
• Guard Against “Outsourced Thinking”: Learning requires cognitive effort.
• Promote Intellectual Agency: Students must evaluate and question AI outputs.
• Value Human Interaction: Relationships and dialogue remain central to learning.
• Design for Depth: Create tasks that require reasoning, not just completion.

IMPLICATIONS FOR SCHOOL LEADERS

• Clarify Instructional Vision: Anchor AI use in core learning goals, not trends.
• Support Thoughtful Integration: Guide when and how to use AI effectively.
• Shift Assessment Practices: Emphasize explanation, reasoning, and originality.
• Encourage Professional Dialogue: Engage staff in ongoing conversations about AI’s role.
• Protect Deep Learning: Ensure classroom practices prioritize thinking over efficiency.

LEADERSHIP BOTTOM LINE

The challenge of AI in education is not technological—it is philosophical. Schools must decide what they value most and design learning accordingly. In a world where machines can produce answers, the true work of education is helping students learn how to think.

Original Article

SOURCE

Hargadon, S. (March 2026). What We Get Wrong About AI and Education. https://www.stevehargadon.com/2026/03/what-we-get-wrong-about-ai-an...

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Prepared with the assistance of AI software

OpenAI. (2026). ChatGPT (5.2) [Large language model]. https://chat.openai.com