How Will AI Affect CTE?人工智能如何影响职业技术教育？

I’ve been on ChatGPT a lot lately and—apparently—I’m not the only one. I’m not actually using it （though I intend to）; I’m there to gawk over1 what it can do—and， spoiler2， it goes well beyond3 producing first-year term papers. At a recent social gathering， one of my colleagues demonstrated that—if given a fictional research question—the generative artificial intelligence behind ChatGPT can write nearly flawless computer code for a certain syntax-based statistical package commonly used among policy-researcher types， like myself. It was humbling4; I’ve spent years learning to write such code， to middling5 ability. As you might imagine， this demonstration led to some inevitable—and now ubiquitous6—hand-wringing7 about automation and the implications for society.

最近我一直在捣鼓ChatGPT，显然这么干的人不止我一个。其实我并没有在正经地使用ChatGPT（虽然我有这个打算）， 我只是来凑个热闹，围观一下它到底能做什么——剧透一下，它的功能可远远不止撰写大一期末论文那么简单。在最近的一次社交聚会上，一位同事展示说，如果给它一个虚构的研究问题，ChatGPT背后的生成式人工智能就能编写出近乎完美的电脑代码，形成一个基于句法的统计数据包，供我这样的政策研究人员使用。这实在让人自愧不如，我花了好些年学习编写类似的代码，却始终水平一般。正如你可能猜想到的，这样的展示引发关于自动化及社会影响的忧虑，这种忧虑是难免的，如今无处不在。

To what degree can automation affect the career outcomes of graduates of Career and Technical Education （CTE） programs？ I’ve done some preliminary digging and have an idea， but a quick CTE is a useful starting point.

自动化会在多大程度上影响职业技术教育（CTE） 毕业生的职业出路呢？我已经做了一些初步的调查，并有点自己的想法，但简短介绍一下CTE有助于开个好头。

Today’s “career and technical education” is yesterday’s “vocational education，” though not really. Like previous iterations8， contemporary CTE focuses on equipping high school and community college students with technical skills that are closely tethered to specific workforce applications—think carpentry9 or plumbing10. By contrast， courses and programs within the “academic” curriculum emphasize subject-matter knowledge and the development of broadly applicable skills—think history， science， language studies， etc.

如今的“职业技术教育”就是以前所说的“职业教育”，但也不尽相同。与以往的职业教育一样，当代CTE侧重于让高中生和社区大学的学生掌握和特定劳动力应用密切相关的专门技能——比如木工和管道工。相比之下，“学术”教育中的课程和专业则更注重学科知识和普适性技能的培养——比如历史、科学、语言研究等。

Modern-day CTE advocates would argue the similarities to former vocational education models end there， however， and would likely （and rightly） assert that making the “academic” versus “vocational” education distinction is a bit anachronistic11 given the college- and career-readiness movement， and mater-ial changes to federal CTE legislation have， over time， successfully blurred the lines between the two. There’s a collective （and bipartisan12！） sense that these changes have steered13 CTE in a positive direction， toward “relevance and rigor14，” and away from its “dark history” of tracking15 disadvantaged students into low-wage， low-opportunity occupations.

不过，当代的CTE提倡者可能会认为CTE和以前的职业教育模式相似之处仅止于此，并且，他们还可能会（正确地）断言，区分“学术”教育和“职业”教育已经不合时宜了，一是由于上大学和就业准备运动，二是由于随着时间推移，联邦CTE立法上的实质性变化也早已成功模糊了二者间的界限。人们达成了一个共识（并且是两党共识！），那就是这些改变已将CTE引上了正轨，使之朝着“实用、严谨”的方向发展，远离了将弱势群体学生输送到收入低微、前途渺茫的职业中去的“黑历史”。

My recent ChatGPT experience has me wondering about this consensus opinion， however. Let me explain.

然而，我最近对 ChatGPT 的体验让我对这一共识产生了疑问。且听我道来：

To begin， jobs requiring skills that are difficult to automate with available technologies are at lower risk of automation. These skills include things like two-way communication， critical thinking， creativity， planning， management， and problem-solving. These are transferable skills， not technical skills. Career and technical education courses and programs need to equip students with both. Not only will the combination of technical and transferable skills help CTE students compete for the automation-resilient16 jobs of today （which tend to require bachelor’s degrees）， the combination will give them greater agility17 when automation threats come knocking tomorrow.

首先，所需技能难以借助现有技术实现自动化的工作岗位被自动化替代的风险更低。这些技能包括双向沟通能力、批判性思考能力、创造力、规划能力、管理能力和问题解决能力。这些都是可迁移技能而非专门性技能。职业技术教育课程和专业需要让学生同时具备这两方面的能力。专门性技能和可迁移技能的结合不仅有助于CTE学生竞争当今能适应自动化的工作（这些工作往往需要学士学位），而且未来面临自动化威胁时，这种结合也能使他们具备更强的灵活性。

This shouldn’t be a stretch18; a key element of contemporary， “rigorous and relevant” CTE is a push to better integrate academic content within technical learning contexts. The concern I have is that “academic integration” is mostly open to interpretation， and there’s not a lot of guidance for how to do it well across the different trades-based （e.g.， Architecture & Construction， and Manufacturing）， service-based （e.g.， Education & Training and Human Services） and tech-based （e.g.， Information Technology and Science， Technology， Engineering and Mathematics [STEM]） CTE fields of study or “career clusters.” There’s also little accountability for academic integration baked into19 federal policy.

这个应该不难做到，当代“严谨、实用”的CTE教育中一个关键要素就是推动学术内容更好地融入专业技术学习的环境中。我所担心的是对“学术融合”多半各有各的解读，对于不同的CTE学习领域，或者说“职业集群”并没有太多关于怎么做的指导。“职业集群”或基于行业，如建筑与施工和制造业；或基于服务，如教育培训和公众服务业；或基于技术，如信息技术和科学、技术、工程与数学（STEM）。同时在联邦政策中，对学术融合的归责条文也很少。

The importance of—and challenges to—carving out space in every CTE classroom in every CTE career cluster for the development of transferable， nontechnical skills becomes especially salient when you analyze automation risks across the different CTE career clusters. To do this， I merged Bureau of Labor Statistics （BLS） Occupational Employment and Wage Statistics （OEWS） data with an available automation-risk index. I calculated the average automation risk for each CTE career-cluster area by entry education level. Several things stand out.

当我们分析不同CTE职业集群的自动化风险时，在每一个CTE职业集群教育中的每一间CTE教室里为可迁移、非专门性技能的发展留出空间，就显得尤为重要并极具挑战性。为此，我将美国劳工统计局的职业就业和工资统计数据与现有的自动化风险指数进行了合并。我按入门受教育水平计算了每个CTE职业集群领域的平均自动化风险，其中有几点值得注意。

First， average automation risks decrease as education level goes up， largely because jobs requiring bachelor’s degrees involve a greater number of transferable skills that are less easy to automate. Second， some CTE career-cluster areas have average automation risks that are low： Education & Training， Health Sciences， Information Technology， and Science， Technology， Engineering and Math. Other CTE career-cluster areas have automation risks that are high： Architecture & Construction， Hospitality & Tourism， Manufacturing， and Transportation， Distribution & Logistics. Third， the gap between the lowest and highest levels of education is greatest in clusters with the highest aggregate20 automation risk， which suggests the academic-integration hurdle is higher in these clusters compared with others.

第一，平均自动化风险随着受教育水平的提高而降低，这主要是因为需要学士学位的工作涉及更多的可迁移技能，而这些技能不太容易自动化。第二，部分CTE职业集群的平均自动化风险较低，比如教育与培训、健康科学、信息技术以及STEM。而另一部分CTE职业集群的平均自动化风险则较高，比如建筑与施工、酒店与旅游管理、制造业以及运输、分销和物流业。第三，在总体自动化风险最高的集群中，最低和最高受教育水平之间的差距最大，这表明这些集群与其他集群相比，实现学术融合的障碍更大。

All this matters because existing research indicates CTE participation can be stratified21 by race， gender， income， and rurality. Consequently， some student groups may be overrepresented in at-risk clusters. In other words， exposure to automation risk can be correlated with student characteristics. And if our efforts to equip these students with automation-resilient， transferable skills are not successful in these clusters， we risk the possibility of， once again， funneling22 disadvantaged students into low-wage， low-opportunity occupations. CTE’s “dark history” becomes its future.

这几点发现很重要，因为现有研究表明，学生参与CTE培训的情况可能因种族、性别、家庭收入和城乡身份而出现分层。因此，某些学生群体在高风险群组中可能会有过高的占比。换句话说，受自动化风险影响的概率可能与学生特征相关。如果我们不能使这些处于高风险群组的学生群体掌握具有自动化弹性的可迁移技能，就有可能再次将弱势学生群体输送到工资低、机会少的职业中，CTE 的“黑历史”就将重演。

Can contemporary CTE shield students against risks posed by automation？ Absolutely. In theory， CTE students should be better prepared for automation. The pieces are there; done right， academic integration， work-based learning， the Comprehensive Local Needs Assessment， and apprenticeship23 models can work to close the gap between the skills students have and the skills employers need， today and tomorrow. And the “special populations” set-aside now within federal CTE legislation that requires providers to allocate funds toward recruiting low-income， disabled， and racially marginalized students into CTE should help diversify cluster pipelines24 and mitigate tracking. It’s always been important to get these things right， but the arrival of ChatGPT means it’s now more important than ever.

当代的 CTE 究竟能否保护学生免于自动化带来的风险？当然可以。从理论上讲，CTE学生应对自动化风险的准备应该更加充分。学术整合，实操学习，地方需求综合评估，学徒模式，这些要素都有了，将它们恰当地整合运用就能缩小学生所会技能与雇主所需技能之间的差距，对于当下和未来皆是如此。目前联邦职业技术教育立法中为“特殊人群”预留机会的计划要求校方拨出专款招收低收入、残疾和种族边缘化的学生接受职业技术教育，这应有助于实现职业集群人才渠道的多样化，并减少分流现象。处理好这些问题一直都很重要，但 ChatGPT 的到来意味着，现在这些事比以往任何时候都更加重要。

（译者为“《英语世界》杯”翻译大赛获奖者）

1 gawk over呆呆地盯着看，此处意为看热闹，围观。 2 spoiler剧透，爆料。 3 go well beyond远超出。 4 humbling使人谦逊的，羞辱人的。 5 middling中等的；普通的。 6 ubiquitous似乎无所不在的；十分普遍的。 7 hand-wringing（因焦急或烦恼）扭绞双手，来自习语wring your hands。

8 iteration迭代，重复，此处指之前的职业教育。 9 carpentry木工。 10 plumbing管道工程。 11 anachronistic过时的。

12 bipartisan为两党派所支持的。 13 steer引导，引领。 14 rigor严谨。 15 tracking（学校）按能力分班（或分组）。 16 resilient可迅速恢复的；有适应力的。 17 agility敏捷，灵活。

18 stretch有难度的工作或任务。 19 bake into加入，使进入……当中。

20 aggregate总数；合计。 21 stratify使分层。

22 funnel输送，传输。 23 apprenticeship学徒制。 24 pipeline渠道，方式。