What is AI, Really? An Overview of AI for Writers, Students, and Teachers

Whether you use ChatGPT in your everyday tasks or haven’t yet made an account, you’re likely aware of (even inundated by!) the news that artificial intelligence (AI) is here to stay. It’s reshaping how we think about nearly every industry—including writing, communications, education, and more. 

But what truly is AI, anyway?

In this blog—the first in a biweekly series in which Write the World teens and staff will explore the implications of AI on writing and teaching—we explore the nuts and bolts of what, exactly, this emerging technology is, and the types of tools available for writers looking to use AI to support, not replace, their creativity.  

The History of AI

We often hear about “emerging” artificial intelligence technologies, and the release of ChatGPT in the spring of 2023 may contribute to the feeling that AI is brand new. However, it has a lengthy and compelling history that is often overlooked. 

The idea of robots or other forms of technology emulating human intelligence spans back to science fiction (demonstrating the power of writing!) produced as early as 1938—and the first pioneering paper on AI technology, titled “Can Machines Think?,” was produced by Alan Turing in 1950. In that paper, Turing posed a pivotal question; he “suggested that humans use available information as well as reason in order to solve problems and make decisions, so why can’t machines do the same thing?”

That inquiry sparked a flurry of scientific interest and investment in artificial intelligence technologies, which have ebbed and flowed ever since; at root, technologists, engineers, and others have worked to answer Turing’s question, creating computer systems that mimic the way the human brain works. 

How AI Works

AI is far from human. Though true to the point about emulating learning, engineers have worked to train computer systems to “learn” from massive amounts of data, quite literally called “deep learning”. 

Exposure to data allows the computers to identify and internalize patterns and then, using statistics, produce content that is the most probable fit, based on the information we provide in our prompts. As writers, this means that our word choices and the order of our words—our “diction” and “syntax,” to use literary terms—is key, as AI tools produce outputs statistically aligned with our inputs. 

Deep learning is an intricate process, and if you’re a technology enthusiast, we encourage you to learn more about it here. Many technologists presume that, as we hone AI technologies and the deep learning process, we won’t even need to prompt AI in the future. 

What the Experts Say

Artificial intelligence is a broad field, and though we’re hearing the term a lot in reference to ChatGPT, that’s just one example of AI technologies; take, for example, self-driving cars—they use artificial intelligence to inform detection sensors. The car predicts, based on the information its systems receive about its surroundings, when is the most statistically probable time for it to stop. (This poses an equity problem, as self-driving cars are, so far, trained to stop when white bodies cross the street, but it struggles to detect other skintones—demonstrating the need for continued human vigilance around best AI practices). 

Large language models are a form of generative AI, meaning AI that generates content (image and video generators, ChatGPT, etc.). Writers at IBM describe the model, stating:

“In a nutshell, LLMs are designed to understand and generate text like a human, in addition to other forms of content, based on the vast amount of data used to train them. They have the ability to infer from context, generate coherent and contextually relevant responses, translate to languages other than English, summarize text, answer questions (general conversation and FAQs) and even assist in creative writing or code generation tasks.”

AI thought leader Ethan Mollick speaks to the model as it applies to content beyond writing:

“Image recognition is not new, nor is the ability to create AI images, but when they are combined with the “brains” of the LLM, something very different happens. So, it is significant that both Google and Microsoft/Open AI have introduced different levels of multimodal capabilities. That means that they can create and “see” images, and also receive and produce voice.”

Types of AI Tools

The AI tools most relevant to writers and teachers are generative models. Below, we outline several of the most common categories of generative AI currently being used:

• Text generators: Perhaps the most well-known generative AI, large language models like ChatGPT and Claude use human input to generate text-based output.
  
  
• Image/video generators: Powered by OpenAI, which also produces ChatGPT, Ask AI is just one of many tools that generates multiple forms of images, and other tools, like invideo AI, produces video. Usually, these tools rely on text-based inputs, but newer versions allow multimedia inputs as well. 
  
  
• Virtual assistants: There are numerous AI virtual assistants tailored to users’ roles and tasks. For writers, Grammarly offers, for example, a virtual writing assistant who can provide copyediting among many other services. Sudowrite is designed for long-form writers, like novelists, and is trained to emulate your writing style. Other assistants exist for marketing copywriters, generating text that aligns to best practices in search engine optimization (SEO). For teachers, pedagogical chatbots emulate teaching assistants, like ISTE and ASCD’s bot, StretchAI. For students, bots like Khan Academy’s Khanmigo guides them toward their own thinking and learning as a tutor would.
  
  Assistants are still large language models, still using statistics to produce the most likely outcomes applicable to a given prompt, but they feel much more personalized, simulating a colleague, editor, etc., and so the experience feels even more like a real-world collaboration or conversation, and they can be trained—such as with Khanmigo—to respond to inputs in a specific way (such as by offering students guiding questions instead of direct answers).
  
  
• Simulated characters/audiences: Like assistants (above), other AI tools allow writers to chat with fictional characters, historical figures, and more. Take, for example, CharacterAI, which facilitates these types of exchanges. 
  
  
• Other content generators: The above are just several models of generative AI technologies servicing students, writers, and teachers. Others exist, like platforms that produce lesson plans, flashcards, presentation slides, grants, rubric-based feedback, and even summaries of content—essays, scientific journal articles, PDFs, and more.

We invite you to check out Write the World’s resources for writing and teaching meaningfully with AI, and to begin applying your learning by responding to the optional AI extension tasks included in several of our monthly writing prompts. Though this post is dedicated to the “what” of AI, we look forward to sharing more posts in our biweekly series exploring the “how” of using AI in productive, innovative ways. More soon!