AI Ready: Don’t Let AI Dumb Us Down

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Welcome to the AI Ready Blog, where we explore the evolving world of Artificial Intelligence and Generative AI in education, fostering dialogue, experimentation, and research to enhance teaching, learning, and collaboration across disciplines.

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I attended an AI conference focused on the Future of Work and had the opportunity to hear Matt Beane speak. Despite his focus outside of higher ed, Beane, an associate professor from USC, offered valuable insights for educators concerned about AI’s impact on learning.

The Danger of “Deskilling”

Beane’s central concern resonates with many educators—students who rely on AI to write their assignments aren’t just missing opportunities to learn; they’re actually regressing in their skills. He calls this phenomenon “deskilling,” and it represents a significant threat to educational outcomes.

The risk we face is graduating students who are merely “push-button operators of AI” rather than critical thinkers with developed skills and understanding. As AI tools become more accessible and powerful, this risk only increases.

A Framework for Skill-Building AI Use

Beane proposes that institutions must ask themselves: “How can we handle technology in a way that gets results AND builds users’ skill?” This dual-purpose approach shifts the focus from seeing AI as either a threat or a shortcut to viewing it as a tool for enhancing learning.

The key lies in encouraging students to engage with AI differently. Rather than simply asking AI “how” to complete a task, students should be pushed to explore the “how” and “why” behind concepts, using AI as a collaborative learning tool rather than a replacement for thinking.

The “Impossible Task” Approach

One fascinating concrete method Beane employs is what might be called the “impossible task” approach. He challenges students with seemingly unattainable projects—like creating a whale song translator—that force them beyond their comfort zones.

Most students initially view such tasks as impossible because they lack domain knowledge. However, by navigating through generative AI’s capabilities and limitations to produce something that at least partially works, students:

  1. Expand their conception of what’s possible
  2. Discover new areas of inquiry
  3. Develop a more sophisticated understanding of AI’s capabilities and limitations
  4. Build skills through the process of exploration and iteration

While this specific example may not translate to every educational context, the underlying principle is widely applicable: using AI to stretch beyond perceived limitations rather than to avoid challenges.

The Human Element: Mentorship and Critical Thinking

Perhaps most encouragingly, Beane envisions AI not as a replacement for human mentorship but as a means to connect learners with subject matter experts who can provide ideal mentorship. This vision aligns with the growing recognition that AI should enhance our humanity rather than diminish it.

As noted in a recent Guardian article, AI may actually create space for humans to focus on “being more human again—using critical thinking, intuition—the things that computers can’t yet do and where we can add real value.”

The Responsibility of Educators

Beane places significant responsibility on educators to guide this process—and rightfully so. Who better to ensure that technology enhances rather than undermines learning? Educators are uniquely positioned to:

  • Model appropriate AI use
  • Design assignments that leverage AI while building skills
  • Guide students in critical evaluation of AI-generated content
  • Foster the human elements of learning that AI cannot replicate

Moving Forward

As we navigate this new educational terrain, Beane’s perspective offers a balanced approach that neither demonizes nor uncritically embraces AI. Instead, it challenges us to be intentional about how we integrate these powerful tools into our educational practices.

For more on this topic, check out Beane’s Substack article: “Don’t Let AI Dumb You Down”

This blog post was inspired by insights shared at a recent AI conference featuring Matt Beane, Associate Professor at USC.


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