Key points:
- Career durability depends on fundamentally human skills that give students the flexibility and adaptability to adjust to changes
- Leading with AI and technology in the age of personalized learning
- How districts can build a shared AI structure
- For more news on schools and AI pathways, visit eSN’s Digital Learning hub
America’s schools are moving quickly to respond to the rise of artificial intelligence, with parents, teachers, administrators, and lawmakers working to wrap their arms around what this means for student education.
But regulation that comes ahead of a clear definition of preparedness may set students back in the AI race. For the future of America’s students — and economy — leaders need to first define what the future of career preparedness looks like.
The speed at which education leaders have moved to respond to AI has been nothing short of remarkable. Just a few years ago, there were no states with formal guidance on AI in K-12 education. Today, 34 states and Puerto Rico have issued some sort of AI guidance for schools. More than 70 bills about AI in the classroom have been introduced across 27 states this year alone, as policymakers debate every aspect of AI, from classroom restrictions and student privacy, to graduation requirements and teacher training.
Yet as schools debate every part of AI policy, including who is and isn’t allowed to use it, how they’re allowed to use it, and when they’re allowed to use it, they’re skipping over a more fundamental issue. What do students actually need to learn in order to be successful for the rest of their lives post-graduation?
It’s a question that should fundamentally drive most education policy decisions, especially when it comes to students in the final years of high school and in college. Before schools can determine what students should avoid, they need to first understand what needs to be encouraged based on the demands of employers and the changing business landscape.
This isn’t about letting businesses dictate education policy. We’ve seen industry lead students astray before. The bootcamps and computer science degrees students not long ago were told would lead to higher paying jobs have now fizzled out — a short-term need now rendered obsolete by the advancement of AI.
The mistake we made then was over-indexing on short-term signals. Several years ago, there was high demand for computer engineers, so education leaders gave students one set of skills needed for one defined future.
Then things changed.
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