Is using AI-generated content for SEO plagiarism?

As more people adopt AI tools to generate content for SEO, the line between inspiration and plagiarism is blurred. 

Many are asking: Is using AI in content creation plagiarism? Or is it simply the next step in the evolution of creative collaboration?

Let’s explore.

How AI creates content

Let’s look at how AI generates content to set the foundation for this discussion.

AI generates text using machine learning (ML), natural language processing (NLP) and natural language generation (NLG).

Machine learning

ML is a subset of artificial intelligence that involves training models to recognize patterns and make data-based decisions. 

This is the foundation that makes NLP and NLG possible. The process goes something like this: 

• Massive datasets consisting of text from books, articles, websites and more are collected.
• ML models are trained on these datasets. 
• The models learn linguistic patterns, context, grammar and structure when analyzing the data.

Models can improve over time without being explicitly programmed for specific tasks.  

Natural language processing

NLP comes into play by understanding and processing human language. NLP does things like:

• Breaking down text into smaller units like words or phrases.
• Analyzing the grammatical structure of sentences.
• Identifying and classifying entities like names, dates and locations in text.
• Determining the emotional tone of text.

Natural language generation

NLG involves generating the text, using the patterns and structures learned during the ML training phase.

NLG includes: 

• Deciding what information to include in the generated text.
• Organizing the content into a logical sequence.
• Combining information into coherent sentences.
• Converting the structured content into grammatically correct sentences.

In a nutshell, ML models take pre-existing data, analyze it and generate new text based on it. 

What is plagiarism?

Plagiarism is traditionally defined as using someone else’s work, ideas or expressions without proper acknowledgment and presenting them as your own. 

It can involve copying text verbatim, paraphrasing too closely without credit or even using someone’s ideas or theories without proper attribution. 

Originality plays a part in evaluating plagiarism. Original work refers to content created through one’s own thoughts, analysis and synthesis of information. 

Technically, when you use an AI tool to create content, you are relying on AI’s analysis of data—data that was fed to it from others’ original work.

This sounds a lot like plagiarism. But it’s not so black and white.

AI content is trained on other’s ideas and likeness

AI content is trained on massive data sets. In other words, other people’s ideas.

In theory, though, when AI generates text, the text is generated dynamically and is not a direct copy of any specific text from the training data.

So, in this sense, AI-generated text can be considered original because it’s newly created each time you prompt it. 

However, this is not foolproof.

In some cases, AI-generated content can get eerily close to copying ideas and sentences in a way that feels like plagiarism. 

Moreover, AI tools can also be trained on specific writing styles or likenesses of people, attempting to copy how others put together words and ideas. 

So, is AI stealing ideas? By some accounts, yes. 

For example, one author, Jodie Cook, said ChatGPT used “multiple exact sentences” from an original article she’d published online when she prompted it to write about entrepreneurialism for kids. 

The fact that there are multiple lawsuits against OpenAI for copyright infringement suggests that Cook is not alone. 

For example, A group of newspapers and authors are among those filing suit against OpenAI for their work being used to train AI models.

So far, in at least one case, OpenAI has seen rulings in its favor.

There have also been more troubles for AI. One example is Sony, which wants companies to stop using Sony music and lyrics to train AI systems.

Then there’s actress Scarlett Johansson, who opposed AI’s use of her likeness to create a copy of her voice. 

All of this is to say that everyone is trying to figure out the ethical use of AI and the question of plagiarism.

Haven’t content creators been borrowing ideas forever?

Content creators have always drawn inspiration from other’s work. Even the world’s most popular authors have literary influences. 

In the online realm, it’s not uncommon for content creators to use search results to research a topic before writing it.

But there’s a difference between inspiration and plagiarism. 

Skilled content creators will research and synthesize information from various sources, adding their own analysis and providing citations.

Even when building on others’ ideas, there is an expectation that new insights or perspectives will emerge. This is what makes original, thought-provoking content.

The problem of unoriginal content 

One major problem of AI-generated content that’s published without one’s own expertise is bland, unoriginal content. 

Is unoriginal content plagiarism? Maybe. 

If you’re simply using an AI tool that scrapes other’s ideas from the web and stitches them together without adding your thoughts, analysis and style of writing (also known as patchwork or mosaic plagiarism), then it could be plagiarism. 

In any case, it’s generic content. Unhelpful content that adds nothing new to the conversation. 

Google Search has been battling unoriginal content for many years, and it can only get worse with AI.

For example, if website publishers rely too heavily on AI-generated content for their sites and that AI content ranks in the search results, then some AI tools will simply regurgitate AI’s ideas as they search the web for data on a topic.  

Author Maggie Harrison Dupré states:

• “When you feed synthetic content back to a generative AI model, strange things start to happen. Think of it like data inbreeding, leading to increasingly mangled, bland and all-around bad outputs.” 

It’s an unsettling notion indeed.

The million-dollar question: Is using AI-generated content considered plagiarism?

Turns out, no one has a definitive answer yet. However, many are trying to institute guidelines on the use of AI-generated content.

For instance, the AP and other publishers are developing guidelines on AI, and universities are developing their own policies as well.

If we are left to self-govern our use of AI, the best we can do is rely on our own ethical analysis of the situation.

A lot of it has to do with what we do with the AI output.

When we rely solely on AI-generated content—without any human involvement and editing—we are stifling creativity and potentially publishing inaccurate information. 

From a marketing perspective, the question is: Will it distinguish you from the noise? If the answer is no, it’s probably time to rethink how you are producing content. 

How to use AI and not plagiarize

AI is a tool, not a solution. It’s an incredible assistant for—not a replacement of—your best content creator.

If you can find the right AI tools to assist you in the right parts of the content creation process, embrace it. 

(See my article here on Search Engine Land on how to add a human touch to AI-generated content for more on this topic.)

Here are some ways you can avoid plagiarism when using AI content:

• Ensuring the text is original in the sense that it is not a direct copy of any source. You can use various plagiarism checkers to help, though the accuracy depends on the tool.  
• Making sure there has been additional analysis and editing of the AI-generated text to make it your own and to insert your expertise.
• Disclosing the use of AI-generated text if you have not made extensive edits to it and attributing specific AI tools used in content creation (as you would any source used during research). 

While AI can be a powerful tool in content creation, it’s not a replacement for human ingenuity and critical thinking.

The essence of originality lies in the process where human insight and creativity breathe life into data-driven outputs. 

As we embrace AI, let us do so responsibly, ensuring our creations are ethically sound and genuinely innovative.