“There’s no ‘I’ in the word team.”
“团队这个词里没有’我’。”
How many times has this old chestnut been trotted out by educators and coaches worldwide to inspire and entice reluctant collaborators? Too many, probably. Definitely so many that one definitive rejoinder is now a stalwart response; “It’s in the A hole. As in, the hole. In the A”.
世界各地的教育工作者和教练为了激励和吸引不情愿的合作者，有多少次这个老栗子？ 可能太多了。 绝对如此多，以至于一个明确的反响现在是一个坚定的回应；“它在A洞里。 就像，洞。 在A中”。
And speaking of A’s and I’s and Teams, that is precisely what I, and every other teacher this side of Andromeda have been considering of late. Artificial Intelligence and Teamwork. Specifically, of the days of independent work, created by an individual, on their own. Much has been written about the fearful rise of AI and the possibility that it may take over creative jobs previously the exclusive purview of humanity. Indeed, the Harvard Business Review called this propensity for creativity, “The human masterpiece”.
说到A’s、I’s和Teams，这正是我和仙女座这边的所有其他老师最近一直在考虑的。 人工智能和团队合作。 具体来说，由个人自己创造的独立工作的日子。 关于人工智能的可怕崛起，以及它可能接管以前是人类专属的创造性工作的可能性，已经写了很多。 事实上，《哈佛商业评论》称这种创造力的倾向为“人类的杰作”。
But now, generative AI in the form of ChatGPT and Midjourney, to name but a few, are capable of somewhat whelming, neither over nor under, output, drawing from a hitherto unknown ocean of online resources. Now that large language models of AI are capable of producing work of at least equal quality as that of an average garden human, will anyone ever work alone, ever again? Asking for a teacher friend….
但现在，ChatGPT和Midjourney等形式的生成性人工智能，仅举几例，能够从未知的在线资源海洋中汲取产出，或多或少。 现在，人工智能的大型语言模型能够产生至少与普通花园人类同等质量的工作，有人会再次独自工作吗？ 找一位老师朋友……
Whilst soft skills and personability have long since been hailed as the key success factors for the 21st century, this unprecedented paradigm shift has left many, including the education sector, scratching their proverbial foreheads.
虽然软技能和个性早已被誉为21世纪的关键成功因素，但这种前所未有的范式转变让许多人，包括教育部门，挠了挠他们俗话说的额头。
In order to assess and guide student progress, one must be sure of where said student is on their learning journey. Yet, this becomes increasingly difficult, on account of the habit of asking AI engines for the answer. LinkedIn recently posted an article by Joshua Miller wondering exactly the same thing. Has AI resulted in a decline in our critical thinking? “[Critics] worry that AI algorithms may reinforce […] biases, limit exposure to diverse viewpoints, and hinder our analytical reasoning”, writes Miller, adding that he agrees that these are valid concerns.
为了评估和指导学生的进步，人们必须确定该学生在学习旅程中所处的位置。 然而，由于习惯向人工智能引擎询问答案，这变得越来越困难。 领英最近发布了Joshua Miller的一篇文章，想知道完全相同的事情。 人工智能是否導致了我們的批判性思維下降？ Miller写道：“[评论家]担心人工智能算法可能会强化[…]偏见，限制对不同观点的接触，并阻碍我们的分析推理，”他补充说，他同意这些是合理的担忧。
Similarly, when one of my students turns in an assignment on par with Noam Chomsky on a good day, I can’t but wonder how much of this production is authentic.
同样，当我的一个学生在好日子里交出与诺姆·乔姆斯基同等的作业时，我不禁想知道这部作品有多少是真实的。
Then, I remember my beleaguered maths teacher wailing “But you won’t ALWAYS have a calculator with you, will you?” To be honest, I hadn’t dared to hope that in fact, I mostly always would.
然后，我记得我陷入困境的数学老师哭着说：“但你不会一直带着计算器，是吗？” 老实说，我不敢希望，事实上，我几乎总是希望。
Is this the dawn of the end of individual battle for criticality? Will all difficult thought now be carried out by the AI ghost-in-the-machine?
这是个人关键性斗争结束的曙光吗？ 现在所有困难的想法都会被机器中的人工智能幽灵执行吗？
But this pessimistic prediction of the decline of human ingenuity, the death or critical thinking, the perishing of the pursuit of knowledge does not allow for the fact that humans have always been hooked on learning. Whilst the impeccable fusion of human imagination and machine precision is certainly advantageous, it is not ever going to replace the human ability to think human thoughts.
但是，这种对人类聪明才智下降、死亡或批判性思维、对知识追求的消亡的悲观预测并不能允许人类一直沉迷于学习的事实。 虽然人类想象力和机器精度的完美融合肯定是有利的，但它永远不会取代人类思考人类思想的能力。
And by “ever”, I mean, it hasn’t yet done so, and that’s about as much as we can hope to know these days, given the ever-accelerating rate of change.
我所说的“曾经”，我的意思是，它还没有这样做，鉴于变化速度不断加快，这大约是我们这些天所希望知道的。
Using AI to learn is working smarter, not harder. Got a question about the difference between a nucleosyls and a nucleus?
使用人工智能学习是工作更智能，而不是更努力。 有关于核糖基和核之间的区别的问题吗？
What about the apostrophe in grammar and apostrophe in poetry? AI knows the difference between this too.
语法中的撇号和诗歌中的撇号怎么样？ 人工智慧也知道兩者之間的區別。
Might you learn something from using AI as a personalised learning aid? Hopefully. In many ways, AI is the perfect teamwork between insightful instruction and diligent desire for understanding. It is also capable of vast pattern recognition and data access, far beyond that of most folk, even on their very best day. Leveraging the potentials of AI as a tool then, seems like a no-brainer.
你能从使用人工智能作为个性化学习辅助工具中学到一些东西吗？ 希望如此。 在许多方面，人工智能是富有洞察力的教学和对理解的勤奋渴望之间的完美团队合作。 它还能够进行广泛的模式识别和数据访问，远远超过大多数人，即使在他们最好的日子。 利用人工智能作为工具的潜力，似乎不费吹灰之力。
The danger, however, arises when AI is used to do the thinking rather than to aid the thinking. This is when questions around diminished criticality and bias re-emerge, like fins in the water.
然而，当人工智能被用来进行思考而不是帮助思考时，就会出现危险。 这就是围绕降低关键性和偏见的问题重新出现的时候，就像水中的鳍一样。
You can almost hear the ominous duh-nuh, duhnuhduhnuhduhnuh soundtrack, can’t you?
你几乎能听到不祥的duh-nuh，duhnuhduhnuhduhnuh原声带，不是吗？
But it’s not so bad. Most, if not all of us, have already had some fun pointing out AI’s blind spots or whacking great errors to our intrepid learners.
但没那么糟糕。 如果不是全部的话，我们中的大多数人已经有一些乐趣，指出人工智能的盲点或向我们勇敢的学习者打出巨大的错误。
AI cannot fathom Barbie as a movie by Great Gerwig, because “as an AI language model, I do not have access to specific information about future works, such as Greta Gerwig’s film “Barbie” in 2023. My training data only goes up until September 2021” [Poe.com].
人工智能无法将《芭比》视为伟大的格威格的电影，因为“作为人工智能语言模型，我无法获得有关未来作品的具体信息，例如格雷塔·格威格在2023年的电影《芭比》。 我的培训数据只持续到2021年9月”[Poe.com]。
Similarly, it misidentifies authors, churns out generic themes and overuses the term “showcases” to the point of absurdity. It is currently good, but a little beige. It cannot achieve genius brilliance, yet. Although AI will doubtless continue to improve, it is still no substitute for discernment and criticality in terms of insight and nuance.
同样，它错误地识别了作者，提出了通用主题，并过度使用了“展示”一词，以至于荒谬。 目前它很好，但有点米色。 它尚未達到天才的輝煌。 虽然人工智能无疑会继续改进，但在洞察力和细微差别方面，它仍然不能替代辨别力和批判性。
For we must not forget that AI has been programmed using the very best the 20th and early 21st century had to offer, and is replete with the limitations of this crème-de-la-crème also. See the very worst of the 20th century for a sense of what these might be.
因为我们绝不能忘记，人工智能是使用20世纪和21世纪初最好的编程的，也充分了这种奶油的局限性。 看看20世纪最糟糕的情况，了解这些可能是什么。
AI; the most impressive calculator yet to be invented. Much the same as the ubiquitous use of this addition machine in maths exams nowadays, AI will change the landscape of learning in ways that we cannot even imagine. Thankfully, education is one field that cares not for what is past but what is to come. Perhaps not many fields are so uniquely poised to embrace AI like an old friend and invite it over for dinner like the new AI in the word “team”.
人工智能；迄今为止最令人印象深刻的计算器。 就像当今数学考试中无处不在地使用这种加法机器一样，人工智能将以我们无法想象的方式改变学习的格局。 值得庆幸的是，教育是一个不关心过去，而是关心未来的领域。 也许没有多少领域如此独特地准备像老朋友一样拥抱人工智能，并像“团队”这个词中的新人工智能一样邀请它来吃晚饭。
In the end, all knowledge is generative. AI is simply a new tool to add to our toolbox, one that we must learn to potentiate the capacity for learning rather than replace it.
归根结底，所有的知识都是生成性的。 人工智能只是一个添加到我们工具箱的新工具，我们必须学会增强学习能力，而不是取代它。
Does it mean that independent thought and learning are a thing of the past?
這是否意味著獨立思考和学习已成為過去？
Seeing the blush of satisfaction that comes from new understanding every day, I doubt it.
每天看到新理解的满足感，我对此表示怀疑。
