As AI’s ability to generate content continues to become more advanced and sophisticated, it creates complex questions that professionals, from content marketers to professors to legal scholars, grapple with, such as — what exactly is direct plagiarism in the age of AI?
In this article, we’ll take a closer look at:
When people ask, “What is it called when you copy someone’s work?” Direct plagiarism is the answer. This type of plagiarism involves copying someone else’s work word-for-word without giving them credit or citing them.
Direct plagiarism is problematic and can cause intellectual property issues. Further, when a writer or content creator passes off someone else’s work as their own, it damages credibility and integrity.
It’s often associated with the world of academia, but it happens beyond high schools and colleges. It can even occur in journalism and other fields like coding. From both an ethical and legal standpoint, the repercussions of plagiarism can be serious and severe.
In the academic world, a student may fail an assignment or a class. They could even face suspension or expulsion from their academic institution. In the professional world, consequences can include losing a job or facing legal action.
AI’s entrance, quick adoption, and integration into the world have considerably blurred the lines between plagiarism and how we define it. First, to provide context, let’s look at how plagiarism detectors evolved to identify direct plagiarism and how the rise of AI is changing the content landscape.
In the early days of plagiarism detection, editors, educators, and other professionals had to compare texts line by line to uncover any similarities. It was time-consuming, tedious and prone to error. When the internet arrived, the explosion of digital content meant that traditional methods just couldn’t keep up and in response the first software plagiarism detectors were released onto the market.
These programs were fairly basic and used simple algorithms to compare written text to a limited database. As technology progressed and more content was published online, these tools advanced, and the databases they could search grew as well.
Innovations in plagiarism detection allowed for faster, more complete detection of copied content, and for a time, plagiarism detection tools and platforms were commonly used by colleges, universities, journalists, and other professionals.
Then, AI arrived on the scene, bringing with it the question, ‘What do you do if you suspect plagiarism in a paper, report, or other piece of content, but nothing is found in the database?’
AI writing tools pull from vast training knowledge to craft responses and content. This posed problems for early systems because AI generates content with different words in contrast to direct plagiarism, which uses exact word-for-word sentences. That means, in theory, AI could potentially bypass some direct plagiarism programs.
If you use content generated by AI, is it considered plagiarism? This is the kind of question that legal scholars are still grappling with today.
Fortunately, the same AI that has evolved to churn out human-sounding content can also be used to address plagiarism.
Traditional plagiarism detectors (that search a specific database) don’t always scan the sheer volume of content that exists online. This is where AI-powered plagiarism detection comes in to help identify or prevent plagiarism.
Through machine learning algorithms and NLP (Natural Language Processing), AI can dig deeper into content. Depending on the detector, it can analyze context, linguistic style, and even the nuances of language to uncover direct plagiarism, paraphrasing, or other types of plagiarism.
AI is well suited to processing incredible swaths of data from multiple sources. Rather than relying on a single (or a collection of) databases, advancing AI technology opens up the opportunity to expand plagiarism detection to include:
Some AI-based plagiarism detectors can even compare patterns in writing styles. AI’s incredible sophistication and ability to deeply analyze content make it an invaluable tool in the fight against direct and other types of plagiarism.
Note: Keep in mind that plagiarism detector capabilities vary across the market. Not all AI plagiarism detectors cross-check information from the same range of sources.
Identifying plagiarism is one piece of the puzzle. As AI becomes more popular with new versions of ChatGPT, Google Gemini, and Claude that sound smarter, more authentic, and human-like, it’s important to pair plagiarism and AI-generated text detection.
To continue upholding the high standards of professional and academic work, tools like Originality.ai’s AI Content Checker offer both plagiarism and AI-generated text detection with their suite of tools.
The problem then becomes, in a world where AI can create almost anything, is it really plagiarism if a machine writes (or draws) it? With the rapid developments in AI, the future of what plagiarism looks like is still up for debate.
To address plagiarism in the age of AI, there are several factors to consider:
To that end, plagiarism detection systems need to keep up. Try complementing plagiarism detection with the use of AI checkers and fact-checking tools.
With these questions comes an important distinction — when is it acceptable for AI to provide assistance and what is the clear definition of plagiarism?
AI assistance refers to using AI tools to do things like:
As long as users are transparent about the use of AI in these cases, it’s a valuable and helpful tool that builds on content creation advancements like using a computer to type instead of writing copy by hand.
This contrasts the concept of direct plagiarism and AI, which raises ethical concerns. Instances of AI use that blend with the ever-evolving concept of plagiarism include:
As content creators, it’s important to lay a path forward for the responsible and transparent use of AI. That way, we can continue to benefit from human ingenuity and creativity.
AI is an increasingly helpful tool when used properly in the creative process. It provides fresh new ideas, refines human language to sound more polished or professional, and offers students detailed explanations of challenging concepts to spark interest in further research.
However, creators need to be aware of the ‘line in the sand.’ Use it as a tool to enhance rather than a complete replacement for the creative process.
View AI as a collaborator, not a standalone creator. AI can’t and shouldn’t replace authors, publishers, or other creators. We still need and greatly benefit from human creativity, authenticity, and originality.