What Is AI-Generated Text?

AI-generated text is a text produced by an AI algorithm in response to a user’s prompt or query. 

Programmers design modern machine learning programs to resemble the human brain in structure and function. Complex neural networks take in unstructured training data, which the machine learning model systematically “teaches” to an AI text-generation bot. 

These AI models aren’t thinking or creating, per se. Programmers train large language models (LLMs) on enormous data sets. Over time, these LLM models learn to classify data by types. They quickly get better at reverse-engineering training data into the most statistically likely answers to questions put to them by prompters. 

A multitude of businesses in a variety of industries use AI text generation to speed up the creation of: 

• Emails

• Social media posts

• Marketing copy

What is AI-generated text used for?

AI text generation offers various sophisticated use cases, including predictive text, content generation, chatbots, game design, and language translation. 

Predictive text and autocompletion

Some argue that, by its nature, AI text generators are essentially highly sophisticated autocomplete features. That makes sense: AI isn’t thinking in a truly humanlike way; rather, it’s making complex statistical analyses of unstructured data to predict what word comes after another word. 

However, autocorrect is a useful feature in and of itself, and predictive algorithms are worthwhile regardless of whether they resemble older technology that many still rely on. Predictive text generation models adapt to new information in a way that basic autocorrect doesn’t. This is why they can output fairly humanlike content at length—at least after an appropriate training period. 

Content generation for marketing and blogging

Content creators use AI text generators more and more frequently. They’re a cost-effective and efficient way to engage in the copywriting process. 

A content creator simply has to prompt an AI framework to output a fairly sophisticated piece of copy, be it a blog, a social media post, or even a video or other image. Because AI can do this much faster than a person can, using AI text generators can significantly boost productivity. 

Automating customer service responses

Conversational AI relies on natural language processing (NLP) technology to understand and fairly accurately replicate human speech. 

NLP is what powers conversational AI. Businesses utilize conversational AI-based customer service chatbots for a variety of reasons:

• To reduce cost

• To increase productivity

• To reduce human error

• To improve customer satisfaction

Furthermore, chatbots—also known as AI agents or virtual assistants—can operate constantly, meaning customers can get help even when no human workers are present. 

Creative applications in gaming

Video games are still based upon “if-then” scenarios—predictable responses to specific player actions. The hope is that, by utilizing AI, games will become self-learning and adapt to players’ abilities and preferences.

Currently, AI has several use cases in gaming. By combining AI with real-time ray tracing, games become more photorealistic; changes in lighting and shadows appear more realistic than ever before. 

Real-time translation and language support

Some AI algorithms can translate between many languages more or less instantly. This cuts down on the cost of hiring translation and transcription services. Such advanced language translation technology makes international teamwork far easier. A business leveraging AI translation and language support can hire talent worldwide without worrying about language barriers. 

AI can translate not only voice input but also textual input. The applications here are legion: imagine monoglot copywriters being able to reach an international audience without taking the years required to learn a new language. 

How to spot AI-generated text

Currently, no foolproof way exists to tell that it’s AI-generated text you’re reading. While you may, in many cases, be best off trusting your instinct on this, you’ll find some general tips you can follow for spotting AI-generated text. 

Identifying repetitive or unusual phrasing

AI text generators tend to overuse common words such as: 

• The

• It 

• Is

It’s a hallmark of AI-generated text to use simple words and phrases repeatedly. That’s unusual for humans to do. AI text generators rely on stock phrases, redundancies, and blandly predictable word choices to a degree most people don’t. 

Checking for inconsistencies in tone and style

Inconsistencies in tone, style, spelling, and grammar are more likely to indicate human involvement in the composition of a text. 

For instance, AI seldom makes spelling mistakes. However, mistakes and typos are fairly common in human-generated text. 

Additionally, AI-generated text is often flat in tone. It frequently lacks excitement, eagerness, anxiety, or any other human emotion, although LLM programmers are trying to improve that aspect of text generation. If a piece is error—and emotion-free, it just may be AI-generated. 

Examining sentence structure and logic

AI-generated content can be simplistic, and AI-generated grammar tends to be consistent to the point of monotony. When writing, people tend to vary sentence structure and length. While it’s not an absolute indication, an overly simplistic and exceedingly monotonous text could be AI-generated. 

Using AI detection tools

An LLM is sometimes best detected by another LLM. A programmer can train an LLM-based AI detection tool on machine-generated and human-written text in separate training scenarios so that the algorithm learns to detect the difference between the two. 

Some researchers are developing a sort of “watermarking” technology to prove that a piece contains AI-generated text. The idea is that training data is marked and cataloged so that a user could look up the provenance of what an AI text generator came up with. 

Pros and cons of using AI-generated text

As with anything, you’ll find both pros and cons of using AI-generated text. 

Pros

AI text generation technology lowers the barrier of entry to online content creation. Anyone who can figure out how to use the intuitive text-generation interfaces popular today can create content (textual, audio, visual) without expertise or extensive education. 

For businesses, the pros of AI text generators abound. AI text generators can: 

• Summarize lengthy documents

• Transcribe meetings

• Write code

• Recommend related products to digital customers

• Train employees

• Assist customers around the clock

Additionally, because AI text generation is so much faster than human text generation, using AI can vastly increase general productivity.

Cons

The use of training data for generative AI presents some data security concerns. Because of the way programmers train AI text generators, some of the data they’re trained on may be proprietary or otherwise sensitive. An AI text generator could be sweeping up confidential information, such as HIPAA-protected medical records or social security numbers. 

Some AI models are also prone to factual inaccuracies, usually because they’ve been trained on inaccurate data sets. Because programmers train AI models on different data sets, their results are not repeatable—that is, certain models may get information correct while others may not. 

Programmers train AI on such large data sets that it’s likely that they’ll eventually absorb copyrighted data, which they may incidentally recombine into derivatives of protected works. This represents an incursion into intellectual property and can result in legal consequences. However, a debate still exists about whether or not you can copyright AI-generated text or videos in the first place. 

Learn more about AI-generated text on Coursera

Using an AI text generator can improve productivity but also cause your writing to lose some of its unique voice. In other words, while AI-generated text is seemingly simple, it’s a complex matter. 

Learn more about generative AI on Coursera. Start with DeepLearning.AI’s Generative AI for Everyone and continue with more practical applications with IBM’s Generative AI Fundamentals Specialization.