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2024考研英语同源外刊:AI是否会摧毁人类的创造力?
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 tech savvy. 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.
随着生成式人工智能的到来，我们在更多创造性工作中看到了扩展实验应用。不到两年前，Github推出了Github Copilot，一个人工智能 "副程序员"，可以协助人类编写代码。近期，设计师、电影制作人和广告执行人员已经开始使用DALL-E 2等图像生成器。这些工具并不需要用户非常懂技术。事实上，这些应用程序中的大多数都非常简单易用，甚至只有小学程度语言水平的儿童现在都可以用它们来生成内容。
This scenario isn’t (necessarily) a threat to people who do creative work. Rather than putting many creators out 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工作的人来说，并不(一定)是一种威胁。人工智能并不是要让很多创作者失业，而是会帮助人类做他们已经在做的工作，让他们速度更快、效率更好地做工作。在这种情况下，生产力将上升，因为依靠使用自然语言的生成性人工智能工具，可以减少提出新的想法或文本的时间和精力。当然，人类仍将必须投入时间，可能需要纠正和编辑新生成的信息，但是，总体而言，应该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 are drowned out by a tsunami of algorithmically generated content, with some talented creators even opting out of the market. If that would happen, then an important question that we need to address is: How will we generate new ideas?
第二种可能的情况是不公平的算法竞争和管控不充分导致真实的人类创造力被挤出市场外。如此一来，作家、制作人和创作者被算法生成的内容如海啸一般淹没，一些有才华的创作者甚至选择退出市场。如果这种情况会发生，那么我们需要解决的一个重要问题是：我们将如何产生新的想法?
In this scenario, generative AI significantly changes the incentive structure for creators, and raises risks for businesses and society. If cheaply made generative AI undercuts authentic 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变了创作者的激励结构，给企业和社会造成风险。如果成本低廉的生成式人工智能比真实人类的内容价格更低，那么随着时间的推移，创新将放缓，真实的风险可能是人类创造的新艺术和内容将越来越少。创作者在争夺人类的注意力这件事上竞争本就十分激烈，如果可以根据需要，提供无限的内容，这种竞争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 being inundated with 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.
我们可以看到的第三种可能的情况是，“技术冲击”再次上演，把重点放在了对抗算法生成的内容上。虽然生成模型展示了非凡的实力，有时甚至是涌现能力，但它们也存在准确性的问题，产生的文本经常产生听起来合理但却充满了事实错误和逻辑错误。出于这些显而易见的原因，人们可能会要求他们的内容提供者的准确性更强，因此可能会开始更多地依赖可靠的人工来源，而非机器生成的信息。
词汇:
1.undercut
英/ ˌʌndəˈkʌt /美/ ˌʌndərˈkʌt /
vt.廉价出售;较便宜的工资工作;从下边削球;削弱;根除
vi.底切;根切
n.底切;牛腰部下侧嫩肉;砍口;切球
2.savvy
英/ ˈsævi /美/ ˈsævi /
n.<非正式>实际知识，悟性
v.理解，懂
adj.<非正式>聪慧的，有经验的
3.inundate
英/ ˈɪnʌndeɪt /美/ ˈɪnʌndeɪt /
v.压倒，控制;<正式>淹没，泛滥
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