The Invisible Cost of Generative AI in Education

6 Skills We're Accidentally Obsoleting

In this piece, I want to explore not what we're gaining with generative AI, but what we might be losing. As it turns out, it could be a lot.

While AI promises increased efficiency and personalization, it will almost certainly erode crucial cognitive skills if we are not very careful. To give a few examples, here are six abilities or skills we risk obsoleting or at least diminishing if we rush to embrace generative AI in education:

1. Critical Text Analysis. Generative AI summarizers offer quick, digestible overviews of complex texts. But when students rely on these tools, are we sacrificing the deep engagement and nuanced understanding that comes from wrestling with difficult passages and concepts ourselves? The ability to parse dense academic writing, identify key arguments, and critically evaluate sources is fundamental to higher-level thinking. We must ensure AI enhances rather than replaces this skill.

2. Fundamental Research Skills. With generative AI able to compile "top five sources" on any topic in seconds, the painstaking process of literature review seems antiquated. Yet, aside from the obvious problem of everyone citing the same sources all of a sudden, this process teaches vital skills: how to effectively search databases, evaluate source credibility, and synthesize information across multiple texts. As we potentially begin to integrate AI research assistants in colleges and schools, we must preserve opportunities for students to develop these foundational abilities.

3. Writing (even on keyboards). As speech-to-text technology improves, handwriting is more than ever at risk of becoming obsolete. But so is writing on computer keyboards. Many students prefer to speak to their devices as the technology is now good enough for this type of communication to make sense. For many, speaking is faster than typing. Where does this leave the overwhelming majority of written components in education?

4. Information Retention. With all of human knowledge instantly accessible via AI, why bother memorizing facts? Tempting, perhaps, but this mindset overlooks how a robust knowledge base enables creative problem-solving and interdisciplinary connections. We must strike a balance between leveraging AI's vast knowledge and cultivating students' own mental libraries.

5. Extended Focus and Deep Thinking. In an era of bite-sized content and constant digital distraction, the ability to sustain deep focus on a single task is eroding. Yet this skill will probably remain crucial for complex problem-solving and creative work. I say probably because there's a chance we are getting this problem backwards. Perhaps generative AI is an enhancer in the sense that we can handle multiple complex problems at the same time. I tend to see that in my own work processes. At any rate, as we design AI-oriented curricula, it is pivotal we intentionally incorporate opportunities for prolonged, focused engagement with challenging material.

6. Original Thought. With generative AI able to generate seemingly novel ideas on demand, there's a real risk of intellectual laziness. Why struggle to develop your own perspective when an AI can provide a coherent argument instantly? Human innovation often springs from the messy, non-linear process of creativity – something AI can augment but not replace.

The goal of education has never been simply to transmit information. Education is so many things, among them being to develop minds capable of critical thinking, creative problem-solving, and ethical reasoning. As AI takes over routine cognitive tasks, these human abilities probably become more vital than ever.

But are we truly educating for the future, or are we at risk of unintentionally rendering core skills obsolete? Time will tell.

Generative AI can probably never be a shortcut to developing essential cognitive abilities. Rather, we should leverage it to create richer, more challenging learning experiences that cultivate these skills at a higher level.

It will be most interesting to see which skills in the coming years will define success in the age of automation. The future demands not just technological literacy, but deeply capable human minds working in concert with AI. It's our responsibility as educators to cultivate both.

I'd conclude by claiming that perhaps there's no tremendous rush. It's better to get it right than to get it wrong quickly.

Slow and steady wins the race.