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上期划线句答案
wefocusedon creative work because freelance employment is most common in these industries, and because creative freelance workers’ clients are often forced to evaluate and hire freelancers with particularly limited quantitative information about their actual competence or commitment, leaving substantial room for bias to drive hiring decisions.
咱们（的研讨）之所以重视创造性作业，是因为以安适作业者的方法作业在这些作业中最为常见，而且因为创造性安适作业者的客户一般只能被逼经过有限的量化信息对安适作业者的实践才能和投入程度进行评价判别，并抉择是不是雇佣，这给雇佣抉择计划留下了很大的轻视空间。
本期内容
双语阅览
with the arrival of generative ai, we’re seeing experiments with augmentation in more creative work. not quite two years ago, github introduced github copilot, an ai “pair programmer” that aids the human writing code. more recently, designers, filmmakers, and advertising executive have started using image generators such as dall-e 2. these tools don’t require users to be very techsavvy. in fact, most of these applications are so easy to use that even children with elementary-level verbal skills can use them to create content right now.
跟着生成式人工智能的到来，咱们在更多创造性作业中看到了拓宽实验使用。不到两年前，github推出了github copilot，一自个工智能 "副程序员"，可以协助人类编写代码。迩来，方案师、影片制造人和广告实施人员现已初步运用dall-e 2等图像生成器。这些东西并不需要用户非常懂技能。实际上，这些使用程序中的大大都都非常简略易用，甚至只需大学程度言语水平的儿童如今都可以用它们来世成内容。
this scenario isn’t (necessarily) a threat to people who do creative work. rather than putting many creatorsout of work, ai will support humans to do the work they already perform, but simply allowing them to do it with greater speed and efficiency. in this scenario, productivity would rise, as reliance on generative ai tools that use natural language reduces the time and effort required to come up with new ideas or pieces of text. of course, humans will still have to devote time to possibly correct and edit the newly generated information, but, overall, creative projects should be able to move forward more quickly.
这种情况对从事创造性作业的人来说，并不（必定）是一种挟制。人工智能并不是要让许多创造者赋闲，而是会协助人类做他们现已在做的作业，让他们速度更快、功率更高地做作业。在这种情况下，出产力将上升，因为依托运用天然言语的生成性人工智能东西，可以削减提出新的主意或文本的时刻和精力。当然，人类仍将有必要投入时刻，可以需要纠正和修改重生成的信息，可是，全体而言，大约能更快地推进创造性的项目。
a second possible scenario is that unfair algorithmic competition and inadequate governance leads to the crowding out of authentic human creativity. here, human writers, producers, and creators aredrowned outby a tsunami of algorithmically generated content, with some talented creators evenopting outof the market. if that would happen, then an important question that we need to address is: how will we generate new ideas?
第二种可以的情况是不公正的算法竞赛和管控不充分致使真实的人类创造力被挤出商场外。如此一来，作家、制造人和创造者被算法生成的内容如海啸一般吞没，一些有才调的创造者甚至选择退出商场。假定这种情况会发生，那么咱们需要处置的一个重要疑问是：咱们将如何发生新的主意？
in this scenario, generative ai significantly changes the incentive structure for creators, and raises risks for businesses and society. if cheaply made generative aiundercutsauthentic human content, there’s a real risk that innovation will slow down over time as humans make less and less new art and content. creators are already in intense competition for human attention spans, and this kind of competition — and pressure — will only rise further if there is unlimited content on demand.
在这种情况下，生成式人工智能大大改动了创造者的鼓励规划，给公司和社会构成风险。假定本钱低价的生成式人工智能比真实人类的内容价格更低，那么跟着时刻的推移，立异将放缓，真实的风险可所以人类创造的新艺术和内容将越来越少。创造者在抢夺人类的留心力这件事上竞赛本就非常剧烈，假定可以根据需要，供给无限的内容，这种竞赛和压力只会进一步上升。
the third potential scenario that we could see develop is one where the “techlash” resumes with a focus against algorithmically generated content. one plausible effect of beinginundatedwith synthetic creative outputs is that people will begin to value authentic creativity more again and may be willing to pay a premium for it. while generative models demonstrate remarkable and sometimes emergent capabilities, they suffer from problems with accuracy, frequently producing text that sounds legitimate but is riddled with factual errors and erroneous logic. for obvious reasons, humans might demand greater accuracy from their content providers, and therefore may start to rely more on trusted human sources rather than machine-generated information.
咱们可以看到的第三种可以的情况是，“技能冲击”再次表演，把要点放在了敌对算法生成的内容上。翻译划线句，长按文末小程序码打卡，答案下期发布~尽管生成模型展示了特别的实力，有时甚至是呈现才能，但它们也存在精确性的疑问，发生的文本常常发生听起来合理但却充溢完实际差错和逻辑差错。出于这些清楚明晰的缘由，我们可以会需求他们的内容供给者的精确性更高，因而可以会初步更多地依靠可靠的人工来历，而非机器生成的信息。
这篇文章节选自：harvard business review（哈佛商业谈论）
发布时刻：2023.04.13
作者：david de cremer
原文标题：how generative ai could disrupt creative work
词汇堆集
1.undercut
英/ ??nd??k?t /美/ ??nd?

r?k?t /
vt.贱卖出售；较廉价的薪酬作业；从下边削球；削弱；铲除
vi.底切；根切
n.底切；牛腰部下侧嫩肉；砍口；切球
2.savvy
英/ ?s?vi /美/ ?s?vi /
n.<非正式>实践常识，领会
v.了解，懂
adj.<非正式>聪明的，有经历的
3.inundate
英/ ??n?nde?t /美/ ??n?nde?t /
v.压倒，控制；<正式>吞没，许多
词组分配
1.out of work 赋闲
2.drown out 吞没，压过
3.opt out 抉择退出；插播；恳求清除
写作句总结
原句：creators are already in intense competition for human attention spans, and this kind of competition — and pressure — will only rise further if there is unlimited content on demand.
规划：sb are already in intense competition for xx and this kind of competition will only rise further if xx.
例句：journalists are already in intense competition for readership and this kind of competition will only rise further if online news sources continue to proliferate.
阅览了解题
what are some c

oncerns regarding generative ai's impact on human creativity, as discussed in the passage?
a. that reliance on generative ai tools will reduce the time and effort required to come up with new ideas.
b. that human creators may be drowned out by algorithmically generated content, leading to a decrease in innovation over time.
c. that people may begin to value authentic creativity more again and be willing to pay a premium for it.
d. that generative models may produce text that is riddled with factual errors and erroneous logic.
b
打卡作业
在草稿纸上翻译文章中的划线句，结束每日的打卡操练！下期推送会发布参阅翻译答案，我们一同来学习英语吧~
外刊君为同学们汇总了《经济学人》，戳码回复“j88”，下载pdf源文件。
（戳码回复“j88”）
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