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An opinion essay published by The 74 argues that educators should be allowed to experiment with AI in their own work while schools set rules for student use. It draws on ASU Prep’s experience building instructional planning tools and recommends limited pilots, safeguards and ongoing review.
The 74 published an opinion essay arguing that teachers and school leaders should be able to test artificial intelligence tools in controlled settings, even as districts consider limits on student use. The piece draws on ASU Prep’s experiments and says practical experience can help schools identify both useful applications and risks that policies made without classroom testing may miss.
The essay describes an ASU Prep project in which a specialist team used AI to combine curriculum documents, calendars and testing schedules into instructional planning guides. The guides lay out skill sequences and common student challenges, giving teachers, coaches and school leaders a shared resource for discussing progress and support. The account is presented by the essay’s authors; the source does not provide an independent evaluation of the project’s effect on student outcomes.
According to the essay, ASU Prep reviewed 22 staff-generated ideas in one year, moved six into use and evaluated more than 10 commercial AI tools with employees. The organization is now developing departmental AI task forces, alongside a central review process intended to address privacy, security and quality. The article does not identify the tools or report a measured comparison of costs or learning results.
The authors say each proposed use should be examined through three questions: What does it make easier? What does it improve? And what might it weaken or damage? They cite potential trade-offs including easier assignments that reduce productive struggle, personalized instruction that involves sensitive data, and automated feedback that could displace human interaction.
Why Teacher Experience Shapes AI Rules
The argument matters because schools are making decisions about student access, classroom practice and data safeguards while AI tools and their capabilities continue to change. The essay contends that educators who have not used these systems will be less prepared to explain their limits, judge their outputs or help students use them responsibly. That is the authors’ position, not a finding established by comparative research in the source.
Hands-on testing could also give districts a way to spot problems before wider adoption. A pilot can reveal whether a tool saves staff time, introduces errors, changes how students approach a task or creates privacy concerns. Those observations can inform rules that distinguish between uses that support learning and uses that may substitute for students’ own reasoning.
The piece does not call for unrestricted adoption. It recommends limited pilots with educator and operations staff involvement, age-appropriate expectations and ongoing checks. That approach frames school AI policy as a process of testing and revision rather than a one-time choice between broad access and a blanket ban.
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District Limits and ASU Prep’s Pilot
The opinion essay opens with examples of caution in schools: it says New York City placed a one-year moratorium on generative AI for preschool through eighth grade, while Los Angeles blocked student access on district devices. It also refers to public warnings from technology-sector figures and concerns that AI capabilities are advancing faster than governance. These examples supply the authors’ backdrop; the source material does not provide separate documentation or fuller details for each policy and statement.
The authors contrast AI’s arrival with earlier technologies that required new infrastructure, such as electricity grids, roads and internet networks. They argue that generative AI spread through existing digital systems, leaving schools to respond while tools are already available. The essay also points to rapid gains in mathematical performance by AI systems, but does not include enough methodological detail to assess the comparison independently.
At ASU Prep, a network of physical, digital and hybrid schools, the essay says early staff experimentation revealed potential uses that leadership might not have identified from a distance. It also describes Khan World School, an online honors high school operated by ASU Prep, where students may use AI for research but must present and defend their positions in live discussions. The authors present this format as one way to keep student reasoning and human discussion central.
“You cannot govern what you have not used.”
— The opinion essay’s authors
Evidence and Safeguards Still Needed
The source is an opinion essay, and its account does not establish whether ASU Prep’s AI-supported planning guides improved learning, reduced teacher workload or produced other measurable outcomes. It also does not name the commercial products reviewed or detail how the organization assessed their accuracy, security or performance.
The essay does not set out a common standard for what counts as a successful pilot, how long testing should last or what findings should trigger a pause. It acknowledges that pilots cannot anticipate every consequence. The effects of AI on student learning, privacy, teacher-student relationships and school organization therefore remain questions for further evaluation, not settled conclusions in this account.
How Schools Could Test AI Uses
The authors recommend that schools support limited, monitored pilots involving educators and operations staff. They argue that teams should check data handling, set age-appropriate expectations and track what a tool strengthens or diminishes, then revise practices as the technology changes.
ASU Prep’s planned departmental task forces are the next step described in the essay: staff closest to particular jobs would identify and test possible uses, while a central review process examines privacy, security and quality. The source gives no timetable for those task forces or results from their work. More broadly, schools’ next decisions will depend on evidence from pilots and on how districts balance potential benefits against risks to learning and student data.
Key Questions
What is the opinion essay arguing?
It argues that teachers and school leaders should have controlled opportunities to use AI so they can make informed decisions about student access, classroom practice and safeguards.
What did ASU Prep use AI for?
The essay says a specialist team used AI to organize curriculum documents, calendars and testing schedules into instructional planning guides showing skill sequences and common points of student difficulty.
Does the essay support unrestricted student use?
No. It calls for limited pilots, age-appropriate expectations and review of privacy, security and quality, while arguing that teachers need practical experience with the tools.
Did the source show that AI improved student outcomes?
No measured student-outcome results are reported in the supplied source. The essay describes ASU Prep’s project and its review process but does not establish the guides’ effects on learning.
What remains uncertain about school AI pilots?
The source does not specify shared success measures, testing periods or thresholds for stopping a pilot. It also leaves open how AI affects learning, privacy and teacher-student interaction across different school settings.
Source: rss
