3 reasons why ‘going slow to go fast’ is the right approach for AI in schools

Education Access & Equity Education Policy Education Technology

教育机会与公平 教育政策 教育技术

The search for relevant sources and light copyediting for this piece were provided by Copilot and Notebook, Microsoft and Google generative AI tools (respectively) .

本文的相关来源搜索和轻度文案编辑由 Copilot 和 Notebook、微软和谷歌生成式 AI 工具（分别）提供。

The output was reviewed and revised for factual accuracy by the author, fact checked and copyedited again by a human, and checked for plagiarism prior to publication.

作者对输出的事实准确性进行了审查和修改，由人工再次进行事实检查和复制编辑，并在出版前检查是否存在抄袭。

The AI tool did not contribute any original ideas to the commentary.

AI工具没有为评论贡献任何原创想法。

Increasingly, states and cities are issuing bans or time-limited moratoriums not only on cell phones in schools, but also on student screen use (including AI tools) more broadly.

越来越多的州和城市不仅针对学校中的手机，而且更广泛地针对学生屏幕使用（包括人工智能工具）发布禁令或限时暂停。

Utah was one of the first states to place limits on student AI and screen use through legislation passed this spring.

犹他州是首批通过今年春天通过的立法限制学生人工智能和屏幕使用的州之一。

Last week, New York City and Los Angeles made headlines by adopting year-long moratoriums on student AI use in public schools.

上周，纽约市和洛杉矶因在公立学校暂停学生使用人工智能而成为头条新闻。

These jurisdictions—cutting across red and blue political lines—are not alone in putting the brakes on screens and AI use.

这些跨越红蓝政治路线的司法管辖区并不是唯一对屏幕和人工智能使用进行限制的司法管辖区。

Their actions remind me of a school district leader who told me last year that his approach to AI was to “slow down to go fast.” Before rolling out new tools, he wanted to understand how they might help students—and how they might harm them.

他们的行为让我想起了一位学区领导，他去年告诉我，他对人工智能的态度是“放慢速度，加快速度”。在推出新工具之前，他想了解它们如何帮助学生以及如何伤害学生。

He and his team conducted a districtwide screen time audit and reviewed teacher pedagogy to understand which approaches were “AI-aware,” “AI-assisted,” or “AI-resistant.”

他和他的团队进行了全区范围的屏幕时间审核，并审查了教师的教学方法，以了解哪些方法是“人工智能感知”、“人工智能辅助”或“人工智能抵抗”。

Critics argue that this go-slow approach will stifle innovation, throw the baby out with the bathwater, and leave children unprepared for the future.

批评者认为，这种缓慢的做法会扼杀创新，把婴儿和洗澡水一起倒掉，让孩子们对未来毫无准备。

As someone who has studied innovation in education for many years, I can say with confidence that not all innovation is good innovation.

作为一个研究教育创新多年的人，我可以自信地说，并不是所有的创新都是好的创新。

And as someone who has recently focused on how generative AI affects student learning and development, I believe the current slowdown is warranted.

作为最近关注生成式人工智能如何影响学生学习和发展的人，我认为当前的放缓是有道理的。

There are three good reasons why a “slow down to go fast” approach makes sense right now.

“放慢速度，加快速度”的方法现在有意义有三个充分的理由。

While the evidence base on AI and student learning is still developing, emerging research continues to identify important risks.

虽然人工智能和学生学习的证据基础仍在发展，但新兴研究仍在继续发现重要风险。

In our Global Task Force on AI and Education report , we found that “narrow” AI applications, those built on vetted content and embedded within high-quality pedagogy, can offer meaningful benefits.

在我们的人工智能和教育全球工作组报告中，我们发现“狭义”人工智能应用程序，即那些基于经过审查的内容构建并嵌入高质量教学法的应用程序，可以提供有意义的好处。

At the same time, there are significant risks associated with “wide” AI use, particularly when young people engage extensively with general-purpose chatbots that were not designed primarily for education or child development.

与此同时，人工智能的“广泛”使用也存在重大风险，特别是当年轻人广泛使用并非主要为教育或儿童发展而设计的通用聊天机器人时。

These risks include emotional manipulation , reduced frequency of repairing ruptured human relationships, and perhaps most concerning for educators, students using AI to bypass effortful thinking, thereby undermining learning itself.

这些风险包括情绪操纵、修复破裂的人际关系的频率降低，这或许是教育工作者和学生最关心的问题，他们使用人工智能绕过了费力的思考，从而破坏了学习本身。

New evidence from one of the world’s largest educational AI initiatives suggests that even thoughtfully designed “narrow” AI systems can produce unintended consequences.

来自世界上最大的教育人工智能计划之一的新证据表明，即使是经过深思熟虑设计的“狭隘”人工智能系统也可能产生意想不到的后果。

Estonia, a country known for its advanced digital infrastructure and technology-forward approach to public services, launched its AI Leap program in secondary schools last year.

爱沙尼亚以其先进的数字基础设施和技术领先的公共服务方式而闻名，去年在中学推出了 AI Leap 计划。

The initiative included teacher training, AI literacy instruction, and access to AI tools.

该计划包括教师培训、人工智能素养指导和人工智能工具的使用。

Students in grades 11 and 12 were provided access to ITI, a specially designed AI workspace initially developed by OpenAI in collaboration with Estonian education experts.

11 年级和 12 年级的学生可以使用 ITI，这是一个专门设计的人工智能工作空间，最初由 OpenAI 与爱沙尼亚教育专家合作开发。

The result was a secure, education-focused version of ChatGPT designed not simply to provide answers to students but to support reasoning, reflection, and learning strategies.

其结果是 ChatGPT 的安全、以教育为重点的版本，其设计不仅是为了向学生提供答案，而且是为了支持推理、反思和学习策略。

After one year, the early findings appear more encouraging for teachers than for students.

一年后，早期的研究结果似乎对教师来说比对学生来说更令人鼓舞。

Teachers reported saving an average of 1.8 hours per week on administrative tasks, and an impressive 44% said the tool helped them shift their teaching approach from primarily delivering knowledge to facilitating critical thinking.

教师们表示，他们平均每周在管理任务上节省了 1.8 个小时，令人印象深刻的是，44% 的教师表示，该工具帮助他们将教学方法从主要传授知识转变为促进批判性思维。

At the same time, 73.4% of teachers agreed that “students were capable of producing high-quality work but cannot explain the underlying reasoning,” suggesting that students may be outsourcing too much of their thinking to AI.

与此同时，73.4%的教师认为“学生有能力做出高质量的作品，但无法解释其背后的推理”，这表明学生可能将太多的思维外包给人工智能。

Students, by contrast were not enthusiastic about the AI tool.

相比之下，学生们对人工智能工具并不热衷。

Survey results indicated a generally neutral to lukewarm reception, and but the platform received a net promoter score of negative 27.5, which would be a red flag for any technology company, suggesting considerable room for improvement.

调查结果显示总体上中性到冷淡的反应，但该平台的净推荐分数为负 27.5，这对任何科技公司来说都是一个危险信号，表明还有很大的改进空间。

Their feedback points to a deeper challenge students felt and were struggling with.

他们的反馈指出了学生感受到并正在努力应对的更深层次的挑战。

Many students reported turning to AI before approaching teachers with questions, leading to fewer student-teacher interactions.

许多学生表示，在向老师提问之前先求助于人工智能，导致师生互动减少。

While students appreciated having an accessible, nonjudgmental source of support, many also worried about what this shift could mean for their classroom experience.

虽然学生们很高兴拥有一个容易获得的、不带偏见的支持来源，但许多人也担心这种转变对他们的课堂体验意味着什么。

Poignantly, students raised concerns that speed of finding answers comes at the expense of “practicing communication, collaboration, and shared problem-solving.”

令人心酸的是，学生们担心，寻找答案的速度是以牺牲“练习沟通、协作和共同解决问题”为代价的。

Critics of recent restrictions on student-facing AI often argue that limiting access will leave young people unprepared for an AI-enabled future.

最近对面向学生的人工智能进行限制的批评者经常认为，限制访问将使年轻人对人工智能驱动的未来毫无准备。

But education has always rested on a simple principle: students must learn how to think before they learn how to use tools that think for or with them.

但教育始终基于一个简单的原则：学生必须先学会如何思考，然后才能学会如何使用为他们思考或与他们一起思考的工具。

Developing critical thinking, communication, collaboration, and shared problem-solving skills remains crucial for preparing students to thrive in a world increasingly shaped by AI.

培养批判性思维、沟通、协作和共同解决问题的技能对于学生在人工智能日益塑造的世界中茁壮成长仍然至关重要。

Another valid concern is that broad restrictions could inadvertently eliminate beneficial uses of AI alongside the more problematic ones.

另一个合理的担忧是，广泛的限制可能会无意中消除人工智能的有益用途以及更有问题的用途。

Our task force identified a number of promising applications of narrow AI, ranging from improved assistive technologies for students with learning differences to real-time translation tools that support multilingual learners.

我们的工作组确定了狭义人工智能的许多有前景的应用，从针对有学习差异的学生的改进辅助技术到支持多语言学习者的实时翻译工具。

Many of the most successful examples involve adults using AI to better support students rather than students independently using AI systems themselves.

许多最成功的例子都是成年人使用人工智能来更好地支持学生，而不是学生自己独立使用人工智能系统。

For example, AI can help less experienced tutors provide more effective learning support.

例如，人工智能可以帮助经验不足的导师提供更有效的学习支持。

Teacher-led AI design efforts are particularly promising.

由教师主导的人工智能设计工作尤其有前途。

One example is the national approach underway in the Netherlands , where teachers identify a problem of practice and then collaborate with researchers and technologists to develop AI tools that can help solve it.

荷兰正在采用的国家方法就是一个例子，教师发现实践问题，然后与研究人员和技术人员合作开发有助于解决问题的人工智能工具。

Projects include class question boards and early warning systems that help identify primary school students who may struggle to master handwriting so that timely interventions can be provided.

项目包括课堂问题板和预警系统，帮助识别可能难以掌握书写的小学生，以便及时提供干预。

Importantly, slowing down does not require eliminating all AI use.

重要的是，放慢速度并不需要消除所有人工智能的使用。

Jurisdictions can pause or limit student-facing AI while preserving applications that demonstrably support teaching and learning.

司法管辖区可以暂停或限制面向学生的人工智能，同时保留明显支持教学的应用程序。

This is precisely the approach many states, cities, and districts have adopted.

这正是许多州、城市和地区所采取的方法。

Utah’s restrictions and New York City’s moratorium , for example, continue to allow educators to use AI for many professional purposes.

例如，犹他州的限制和纽约市的暂停令继续允许教育工作者将人工智能用于许多专业目的。

Both also provide exemptions for specific educational contexts, including computer science courses, career and technical education programs, assistive technologies for students with learning differences, and support for multilingual learners.

两者还为特定教育背景提供豁免，包括计算机科学课程、职业和技术教育计划、针对有学习差异的学生的辅助技术以及对多语言学习者的支持。

In practice, many of these policies seek to preserve teacher judgment, student effort, and family transparency while allowing targeted uses of AI where benefits are clearer and risks are more manageable.

在实践中，许多政策都寻求保护教师的判断力、学生的努力和家庭透明度，同时允许有针对性地使用人工智能，使收益更明确、风险更易于管理。

Ultimately, much of the momentum behind these restrictions comes from parents and caregivers who are concerned about the role technology is playing in their children’s lives.

最终，这些限制背后的大部分动力来自父母和看护者，他们担心技术在孩子的生活中所扮演的角色。

Across the country, many parents worry that AI could increase dependency on technology, with 83% of parents believing that children need to learn to think critically on their own without relying on AI.

在全国范围内，许多家长担心人工智能可能会增加对技术的依赖，83%的家长认为孩子需要学会在不依赖人工智能的情况下独立思考。

These concerns were on full display when New York City education officials released draft AI guidance for public comment earlier this year.

今年早些时候，纽约市教育官员发布人工智能指南草案征求公众意见时，这些担忧得到了充分体现。

The proposal generated approximately 6,500 public comments , reflecting an unusually high level of public interest and concern.

该提案收到了约 6,500 条公众评论，反映了公众异常高的兴趣和关注程度。

That feedback was one factor contributing to the city’s decision to adopt a one-year moratorium on student AI use.

这一反馈是该市决定暂停学生使用人工智能一年的因素之一。

Prior to its ban, Utah had conducted an ed-tech audit to determine if tools complied with student data privacy agreements and found half did not.

在禁令发布之前，犹他州进行了一次教育技术审计，以确定工具是否符合学生数据隐私协议，结果发现一半不符合。

Los Angeles has experienced perhaps the highest profile AI flop.

洛杉矶可能经历了最引人注目的人工智能失败。

Two years ago, school leaders quickly pulled the plug on an AI personal assistant they were set to roll out after the company went bankrupt and a whistleblower reported student data safety concerns.

两年前，在该公司破产且一名举报人报告了学生数据安全问题后，学校领导迅速终止了他们原定推出的人工智能个人助理。

Recent news outside of education—from Meta acknowledging in its recent court case that is has for years pushed harmful products to children to OpenAI accidentally unleashing a swarm of out-of-control AI agents that committed criminal offences by breaking into other companies—does little to bolster parent trust of technology companies.

最近教育界以外的消息——从 Meta 在最近的法庭案件中承认多年来一直向儿童推销有害产品，到 OpenAI 意外地释放了一群失控的人工智能代理，这些代理通过闯入其他公司实施刑事犯罪——几乎没有增强家长对科技公司的信任。

Parents are voters, and policymakers rarely succeed when schools and families are moving in opposite directions.

家长是选民，当学校和家庭走向相反的方向时，政策制定者很少能成功。

That may be the most compelling reason to adopt a “go slow to go fast” approach.

这可能是采取“从慢到快”方法的最令人信服的理由。

Building trust and creating meaningful family-school partnerships around AI will take time, but it is essential.

围绕人工智能建立信任并建立有意义的家校合作关系需要时间，但这是至关重要的。

Students experience technology across every part of their lives, both in and out of school.

学生在校内校外生活的各个方面都可以体验到技术。

Neither schools nor families can navigate these changes alone.

学校和家庭都无法独自应对这些变化。

Rarely does anything good happen for kids when families and schools are in conflict.

当家庭和学校发生冲突时，孩子们很少会遇到什么好事。

Decades of evidence show that student learning and well-being improve when the adults in children’s lives are working toward shared goals.

数十年的证据表明，当孩子生活中的成年人朝着共同的目标努力时，学生的学习和幸福感就会得到改善。

The same principle should guide decisions about AI in education.

同样的原则应该指导人工智能在教育领域的决策。

Before expanding student-facing AI at scale, policymakers and educators should ensure that families are part of the conversation and that the technology genuinely serves children’s learning and development.

在大规模扩展面向学生的人工智能之前，政策制定者和教育工作者应确保家庭参与对话，并且该技术真正服务于儿童的学习和发展。

In education, as in so many areas of public life, slowing down may ultimately be the fastest path to getting it right.

在教育领域，就像在公共生活的许多领域一样，放慢速度可能最终是实现目标的最快途径。