Artificial Intelligence: The Dos and Don'ts in Content Creation

2023-01-09 12:14:14
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Artificial Intelligence: The Dos and Don'ts in Content Creation
Illustration: © IoT For All

There’s no doubt about it – artificial intelligence (AI) is changing the way content is created and distributed. With AI tools becoming more sophisticated, businesses are starting to use them to generate content on a large scale. However, there are risks associated with using AI for content generation, and you need to be aware of them. In this blog post, we’ll discuss the dos and don’ts of using AI for content creation and give you some tips on how to create the best possible AI content.

'The variety of content you can create with AI is growing exponentially because of the rapidly increasing availability of tools able to provide this content.' -Daria MassonClick To Tweet

What Is AI-Generated Content?

The term “AI-generated content” encompasses all types of content created by a neural network, not a human. What you get by hitting “Create” is the result of meticulous research, data collection and markup, and, finally, extensive deep learning.

A neural network is an attempt to reproduce the work of the human brain using mathematical models to create machines with artificial intelligence. So equipped, these machines can then write texts, create images, and even play games. All of this is based on deep learning.

Deep learning is a branch of machine learning that uses a model inspired by the structure of the brain – the interaction of neurons. It imitates abstract thinking and is able to generalize facts. It is, however, different from machine learning in a general sense.

Machine learning is a method of constructing algorithms that learn from experience, without writing a special program. Here’s what we mean by this:

  1. If you have written a program that plays chess, this is artificial intelligence; 
  2. If at the same time, it is learning from the games of grandmasters or playing against itself, this is machine learning;
  3. And if a deep neural network learns from it, this is deep learning.

An artificial neural network is usually trained with a teacher. This means the process involves a training set (dataset) that contains examples with true values: tags, classes, and indicators.

AI is quickly becoming a powerful tool in many industries, from retail and finance to healthcare, media, marketing, and advertising. AI-generated content is used in a wide variety of ways, from customer service automation to content creation for websites and blogs. The variety of content you can create with AI is growing exponentially because of the rapidly increasing availability of tools able to provide this content:

  • Natural Language Processing (NLP) – This type of tool uses algorithms to parse natural language and the way people communicate in order to generate content. NLP is used by chatbots and automated customer service systems, as well as content generators.
    • A chatbot used by Hiver
  • Text generators – Text generators are AI tools trained with datasets that can then generate text on their own based on what they’ve been taught. Companies such as Narrative Science specialize in this type of generation technology.
    • The results of text generation by InferKit
  • Image generators – AI-powered image generators are trained to create visually stunning images. For example, DeepAI is a tool that can take an image and give it the style of another image.
    • Image generation with DeepAI
  • Video generators – tools that can automatically compile videos from still images or even transform your blog posts into video sequences. This technology is useful for creating quick and easy explainer videos or product demos. 
    • Turning a script into a video with Lumen5

The Controversy About AI Content

There are many advantages to using AI for content creation. For example, you can save time and money by streamlining the process of creating content. AI tools can also help to create more personalized content that is tailored to a particular audience. 

Generated content can also be used to make the process of generating ideas easier, as AI tools may be better equipped than humans to come up with creative solutions quickly. For example, you can get input from AI when you’re looking for ideas for your business – from customer satisfaction to new product concepts.

Despite the many benefits of using AI tools, there is a lot of controversy surrounding the use of this technology.

Proponents argue that AI can help businesses stay competitive in today’s digital world by freeing up time for employees to focus on more creative tasks instead of mundane ones.

However, detractors fear that AI could be used to manipulate humans or even replace them altogether. It is also a concern that AI could be used to create fake news stories or products, which could in turn harm businesses.

The controversy is increasing in light of allegations that generated content can contain plagiarism or errors. Google has taken a strong stance against AI-generated texts, warning businesses of the potential penalties if they use them. The reason for such extremes is that AI content could be poorly written and ranked way lower than human-made content. However, if your human writers create bad copy, you can expect the same result. And that’s why the controversy is not going anywhere.

The Dos and Don’ts of Using AI

To avoid being penalized by Google or impacted by other possible complications when relying on AI content creation, keep in mind some of the best practices.

Dos:

  1. Do use AI to create content that is relevant to the intended audience. AI can identify patterns in data to help create content that resonates with users.
  2. Do use AI for content curation, which can save time and energy when it comes to researching topics or gathering resources for a piece of content.
  3. Do take advantage of natural language processing (NLP) technology, as this can help ensure accuracy in tone, style, and information.
  4. Do consider leveraging voice recognition technology when creating audio/visual content, as it can be more efficient and cost-effective than manual production methods.
  5. Do make sure you have the right set of tools available, like machine learning frameworks, APIs, and other open-source tools tailored to creating content efficiently.
  6. Do conduct user testing before releasing any AI-generated content or product, so you understand how well humans react to it from an emotional level or the perspective of understanding ability.
  7. Do check the content for plagiarism. Make sure the AI doesn’t just copy information from articles that already exist but creates its text independently.
  8. Do make sure the content is accurate. AI tools are great at generating quantity, but they might not be as good at generating quality. 
  9. Do use clear guidelines. Without proper instructions, AI tools will struggle to generate quality content.

Don’ts:

  1. Don’t rely completely on automated processes. Verify results manually before publication, as there could be potential errors in the output due to incorrect programming or other factors. 
  2. Don’t forget about ethics. Ensure any AI solution adheres not only to legal standards but also to ethical principles during its development cycle.
  3. Don’t neglect security measures. Ensure all necessary security protocols are implemented and kept up-to-date at all times, particularly if commercial-level applications with inbuilt artificial intelligence technology are part of your organization’s offerings.
  4. Don’t use AI-generated content as a substitute for human creativity. While automation certainly brings speed and efficiency gains to organizational processes, never underestimate the value of human insight and expertise.
  5. Don’t forget to consider scalability. Pay attention not only to initial development costs associated with building out a certain functionality but also to future growth demands that may require additional resources at some point down the line. 
  6. Don’t expect AI to be perfect: AI and machine learning are still developing technologies, so errors are likely.

Conclusion

In conclusion, artificial intelligence is changing the way businesses create and distribute content. While AI-generated content can be incredibly helpful in creating high-quality, targeted content, businesses need to be aware of the risks associated with using AI for content creation. 

By following best practices and avoiding common mistakes, you can ensure that your generated content is original and unique, thus avoiding Google penalties. Additionally, it’s important to remember that AI tools can often lack creativity and personalization, so you should use them as a starting point for your ideas rather than relying completely on generated content.

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  • Artificial Intelligence
  • Information and Media
  • Machine Learning

  • Artificial Intelligence
  • Information and Media
  • Machine Learning

参考译文
人工智能:内容创作中的注意事项
**插图**:© IoT For All 毫无疑问,人工智能(AI)正在改变内容的创作和分发方式。随着AI工具变得越来越先进,企业开始使用它们来大规模生成内容。然而,使用AI生成内容也伴随着一些风险,你需要了解这些风险。在本文中,我们将探讨使用AI进行内容创作的注意事项,并为您提供一些创建最佳AI内容的技巧。“由于能够提供此类内容的工具数量迅速增长,你使用AI可以创建的内容种类正在呈指数级增长。”——Daria Masson [点击推文](https://twitter.com/intent/tweet)**什么是AI生成的内容?** 术语“AI生成的内容”指的是一切由神经网络而非人类所创作的内容。当你点击“创建”按钮时,你所得到的结果是经过精心研究、数据收集与标注,最终通过大量深度学习得到的。神经网络是一种试图通过数学模型模拟人脑运作方式的尝试,以创造具有人工智能的机器。这些设备可以写作、生成图像,甚至玩电子游戏。这一切都基于深度学习。深度学习是机器学习的一个分支,它使用了一种以大脑结构为灵感的模型——神经元之间的相互作用。它模仿了抽象思维,并具备泛化事实的能力。然而,它与一般意义上的机器学习有所不同。机器学习是一种构建算法的方法,这些算法可以从经验中学习,而无需编写专门的程序。我们举个例子解释这个概念: 如果你编写了一个能下棋的程序,这就是人工智能; 如果你的程序同时还能从大师的对局中学习或与自己对弈,这就是机器学习; 如果一个深度神经网络从这些对局中学习,这就是深度学习。 一个人工神经网络通常是通过一个“老师”进行训练的。这意味着训练过程包括一个带有真实值(标签、类别和指标)的训练集(数据集)。人工智能正迅速成为众多行业的强大工具,从零售和金融到医疗保健、媒体、市场营销和广告。AI生成的内容被广泛应用于各种场景,从客户服务平台自动化到网站和博客内容的创作。由于能够提供此类内容的工具数量迅速增长,你使用AI可以创建的内容种类正在呈指数级增长。**自然语言处理(NLP)** – 这类工具使用算法解析自然语言和人们交流的方式,以生成内容。NLP被聊天机器人、自动客服系统以及内容生成器广泛使用。**聊天机器人(Chatbot)** – Hiver所使用的聊天机器人就是一例。**文本生成器(Text generators)** – 文本生成器是一种使用数据集进行训练的AI工具,它可以基于所学内容生成自己的文本。Narrative Science 等公司专门从事这种生成技术。 InferKit 生成的文本结果**图像生成器(Image generators)** – AI驱动的图像生成器被训练用于生成视觉上引人注目的图像。例如,DeepAI 这类工具可以将一张图片转换为另一种风格的图像。 使用 DeepAI 生成图像**视频生成器(Video generators)** – 这类工具可以自动从静态图像中合成视频,甚至能将你的博客文章转化为视频序列。这种技术可用于快速、轻松地制作解释视频或产品演示视频。 使用 Lumen5 将脚本转为视频**关于AI内容的争议** 在内容创作中使用AI有很多优势。例如,你可以通过简化内容创作流程来节省时间和成本。AI工具还能帮助生成针对特定受众的个性化内容。生成的内容也可以用于简化创意生成过程,因为AI工具在快速生成创意解决方案方面可能比人类更有优势。例如,当你在寻找企业创意时,比如客户满意度或新产品概念,你可以借助AI提供建议。尽管使用AI工具有许多好处,但围绕这项技术的使用也存在很多争议。支持者认为,AI可以帮助企业在数字时代保持竞争力,让员工可以专注于更具创造性的任务,而不是重复性的工作。然而,反对者担心AI可能被用来操控人类,甚至完全取代人类。人们还担心AI可能被用来制作假新闻或虚假产品,这反过来可能对企业造成伤害。随着对生成内容可能包含抄袭或错误的指控,争议也在加剧。谷歌对AI生成的文本持强硬立场,并警告企业使用AI生成内容可能会带来潜在处罚。出现这种极端立场的原因在于,AI生成的内容可能写得很差,在排名上远远落后于人类生成的内容。然而,如果你的人类作家写得不好,你也会得到同样的结果。也正因为如此,这场争议不会轻易结束。**使用AI的注意事项** 为了避免依赖AI内容创作而受到谷歌惩罚或其他潜在问题的影响,请牢记以下最佳实践:**应该做的(Dos):** - 创作与目标受众相关的内容。AI能够识别数据中的模式,帮助生成与用户产生共鸣的内容。 - 使用AI进行内容筛选(curation),这在研究主题或为内容收集资源时可以节省大量时间和精力。 - 利用自然语言处理(NLP)技术,以确保语气、风格和信息的准确性。 - 在创建音视频内容时考虑使用语音识别技术,因为这比人工制作方法更高效、更经济。 - 确保你拥有合适的工具,如机器学习框架、API和其他开源工具,以高效地生成内容。 - 在发布任何AI生成的内容或产品之前进行用户测试,以便你从情绪层面或理解能力的角度了解人类的反应。 - 检查内容是否存在抄袭。确保AI不会只是复制现有文章的内容,而是独立生成自己的文本。 - 确保内容的准确性。AI工具在生成数量上非常出色,但在质量方面可能并不那么可靠。 - 使用明确的指南。没有适当的指示,AI工具将很难生成高质量的内容。**不应做的(Don'ts):** - 不要完全依赖自动化流程。在发布前手动验证结果,因为输出中可能存在由于编程错误或其他因素造成的潜在错误。 - 不要忽视伦理问题。确保任何AI解决方案不仅符合法律标准,还要在开发周期中遵循道德原则。 - 不要忽视安全措施。确保所有必要的安全协议都得到实施并始终更新,特别是如果你的组织提供内置人工智能技术的商业级应用。 - 不要用AI生成的内容来替代人类的创造力。虽然自动化确实为组织流程带来速度和效率提升,但不要低估人类洞察力和专业知识的价值。 - 不要忘记考虑可扩展性。不仅要关注构建特定功能的初始开发成本,还要关注未来可能需要额外资源的增长需求。 - 不要期待AI是完美的:AI和机器学习仍属发展中的技术,因此错误是难以避免的。**结语** 总而言之,人工智能正在改变企业创作和分发内容的方式。虽然AI生成的内容在制作高质量、有针对性的内容方面非常有用,但企业必须意识到使用AI进行内容创作所带来的风险。 通过遵循最佳实践并避免常见错误,你可以确保你的生成内容既原创又独特,从而避免谷歌的处罚。此外,还要记住AI工具经常缺乏创造力和个性化,因此你应该将它们视为创意的起点,而不是完全依赖生成的内容。推文 分享 分享 邮件 人工智能 信息与媒体 机器学习
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