A guide for content teams: Humanizing AI generated Content

Artificial intelligence (AI), has revolutionized the way we create and consume content.

Although most people associate generative AI with ChatGPT it can also create text, images, and music. While this is exciting, it's also a concern that generative AI could have unintended consequences.

Let's examine this concern and see how we can make generative AI more human-like.

How Generative AI Works

Understanding how a tool works is the best way to learn about it. ChatGPT will be our example because the same concepts apply to all generative AI applications, regardless of whether they are text, image or audio.

Stephen Wolfram wrote a great article about ChatGPT and large language models (LLMs). The author explains that ChatGPT works by "just adding one word at time." This is because it has "learned" relationships and patterns between words and phrases from large amounts of text data.

There's more to the story than that, which you can find out for yourself. It will suffice for our purposes. You don't need to be able to build a car in order to drive one.

The model can then analyze the text and determine what the next step will be given that it has already analyzed billions of pages. It is quick and efficient. It's not perfect.

Why is Humanizing Generative AI's Output Necessary?

Generative AI is a powerful tool that can prove to be extremely useful. However, generative AI can be misused without human supervision and could have unintended consequences. These are reasons why generative AI output should be humanized:

1. Lack of creativity: While generative AI can string words together into different combinations, it cannot experience the world in the same way that a human can. It may not be able to produce original and inspiring content by itself.
2. Bias: Generative AI can produce biases. Any biases in existing data could be reflected in the output, as it learns from them. The generated content could be unfair or discriminatory.
3. Inappropriate content: A generative AI system can also create offensive or violent content if it is trained on offensive or violent data.
4. Factual inaccuracy. Generative AI is able to make up things very convincingly. It doesn't realize that it is doing wrong because it is a machine. These mistakes can have serious consequences. It's even more critical when dealing with your-money-or-your-life (YMYL) topics, or when a generation has lots of statements of fact, numbers, dates, proper nouns, etc.
5. Brand Image: If content generated by an AI system has low quality, bias, is inappropriate or inaccurate, it could damage a brand's image or worse.

The role of Generative Artificial Intelligence in Your Content Team

Jay Acunzo states that generational AI can help you become "ignorable on a scale". It could even cause harm. However, introducing humans to the process changes the dynamic.

These are some things to consider when you implement generative AI.

1. If possible, evaluate the training data. Verify that the model uses data carefully curated to avoid biases and inappropriate content. If the vendor of the software cannot confirm it, you should assume the worst. This is not an issue, but it will require extra caution when you edit the output.
2. Use guidelines to create and maintain standards for all content. It doesn't have to be about how the tool is used, but what it produces. These guidelines usually cover issues such as creativity, appropriateness, bias and quality. These guidelines may be in place already. Make sure you apply them to AI-generated content.
3. You need to reevaluate how you create content. Don't use generative AI to replace human writers. Instead, you can use it to enhance their output. In order to create AI, you may need more editors. They can act as both part writer and editor.
4. To refine the editing process, use an AI text classification tool to inspect for AI-generated texts. This is similar to a plagiarism checker. These are not perfect, and they won't give you a binary option. It may help you spot instances when an editor should be more vigilant. Trust but verify only applies to humans. Generative AI can be used to verify.
5. Verify: When checking for appropriateness, be sure to look out for proper nouns and numbers, dates, declarative sentences, and strategic insights that may be debatable or conflicting with your brand's voice. If you don't intend on fact-checking thoroughly, you should avoid creating content that must be right.

How to Humanize Generative Artificial Intelligence Output

While content production is under threat, human beings are still needed. It's not surprising that humans are the best way to humanize AI-generated output. ChatGPT may not be the right tool for you if ChatGPT is what you want to use for content production.

These are some of the ways that generative AI output can be made more human.

1. Inject humans into the loop. It's been said before, but it bears repeating. The decision-making process must involve humans, both in writing and in editing.
2. Encourage writers to share their knowledge. At best, large language models mimic competence. However, there is no substitute for the real deal.
3. Encourage writers to expand on AI points and share a story that reflects the author's unique experience.
4. Every piece should be clear and reflect the author's experience. Although artificial intelligence can create this illusion to some extent, it is not as real as the real thing.
5. Use idioms — This is a phrase that has a figurative meaning. That one is beyond the AI's comprehension. You can see how I used an expression there. ?
6. To add depth and meaning to the output, use your thoughts and emotions. Generative AI lacks feeling. It can only imitate.
7. Provide unique insight by connecting different concepts in a way that is not obvious to others. ChatGPT is unable to do this due to its inability "know" everything.

Takeaways

Generative AI is a powerful tool. However, it can have unintended consequences if the algorithm is used without human supervision. This is the bad kind. These can be avoided by carefully considering how AI should be used in content production.

Some content is functional, and some expectations are low. For example, corporate earnings reports are an example of a content that is purely functional and has a low expectation level.

Pure generative AI will disappoint when expectations are higher. It is important to keep humans involved in the process so that you can avoid this situation.

Recommendations for AI: Use AI responsibly

AI can have a positive impact on content teams if used with care. MarketMuse's AI-powered platform, MarketMuse, can help you evaluate the quality of your content. MarketMuse is available today.