Editors and AI, Part I: What Is AI? A Primer for Editorial Professionals

artificial intelligence

When ChatGPT started making waves in November 2022, I was curious about how generative AI could simplify running a business. I created an online account and dove in, and although I couldn’t have predicted it at the time, I’ve now spent thousands of hours—and more every day—exploring and testing AI tools, taking classes, developing custom tools, consulting for companies, and having conversations with fellow editors about what AI means for us and the future of our industry.

Now, I’m sharing what I’ve learned.

Whether you’ve embraced AI tools or promised yourself (and your clients) that you’ll never use them, one thing has become abundantly clear: As editors, we need to understand this technology to make informed decisions about its role in our work.

That’s why I’m writing this series. My goal is to help you have productive discussions about AI and its role in editing, decide whether to incorporate AI tools into your practice, and answer your clients’ most pressing questions about this topic.

It’s Not Just You: AI Is Everywhere

First off, I want to acknowledge that AI overwhelm is real. Between the AI features that keep popping up in familiar software programs and the constant stream of AI news and developments, it’s hard to keep up.

You might be privately wondering what ChatGPT actually is, how it differs from other AI tools, or whether you need to pay for access. Maybe you’ve heard colleagues mention Claude or Perplexity but aren’t sure how these tools compare. Perhaps you’ve watched as Microsoft has begun adding AI-powered tools to Word, PowerPoint, and Excel, but you’re not sure how they work (or how to avoid using them). Maybe you’ve told clients that you don’t use AI, but now you’re wondering if Grammarly counts.

Here’s the reality: AI is everywhere in our industry now, whether we like it or not. Even if you've been trying to avoid it, it's likely that you've used it without knowing. But before we can have meaningful conversations about AI’s impact on editing—and before we can decide whether these tools belong in our workflows—we need to clarify what, exactly, we’re talking about.

When We Say “AI,” What Do We Mean?

A problem that often crops up when editors talk about “AI” is that there is no universally accepted definition of artificial intelligence. Instead, it’s an umbrella term that encompasses many different technologies.

In their book AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference, Arvind Narayanan and Sayash Kapoor use an analogy I love. They say that trying to discuss “AI” is like living in a world where we only have one word, “vehicle,” to describe anything that moves people or things. No specific terms like car, bicycle, rocket, truck, cargo ship, fighter jet, or skateboard—just “vehicle.”

This means that when someone says, “Vehicles are destroying the environment,” they may be talking about high-emission trucks, while the other side is talking about skateboards. But neither realizes this, so the debate goes nowhere.

Similarly, when we see posts or articles talking about “AI versus human editors” or “AI replacing editors,” we need to ask: Which type of AI are they talking about? The technology behind Grammarly’s suggestions? The AI that Microsoft Word uses in its “Editor” tool? Or the capabilities of tools like ChatGPT and Claude?

The Moving Target of AI, or the “AI Effect”

Another challenge in discussing AI is that what we consider “artificial intelligence” constantly evolves. A classic example is Nikola Tesla’s demonstration of a radio-controlled boat in 1898, where many people marveled at seeing a “borrowed mind” in action. Today, we view remote controls as simple electronics, far removed from our concept of AI.

Similarly, in 1997, IBM’s Deep Blue supercomputer defeated chess champion Garry Kasparov and was celebrated as a triumph of artificial intelligence. Today, computers routinely beat grandmasters at chess, and we don’t consider it AI.

This pattern, where yesterday’s mind-blowing “AI” becomes today’s mundane software feature (yawn), is known as the “AI effect.” Think about it: When’s the last time you marveled at a calculator doing complex math, or Siri or Alexa responding to your voice commands? Every time AI makes a leap in what it can do, it shifts how we view and talk about it.

What Editors Need to Know About the Types of AI

When most people say "AI" lately, they're referring to generative AI. But artificial intelligence encompasses many different technologies and applications, and understanding these distinctions is crucial for professional editors.

The AI Family Tree

While there are many categories of AI (including predictive AI systems that forecast things like credit scores, recidivism, and health outcomes), as editors, we primarily need to understand the types that directly impact our work:

Artificial intelligence (AI) is an umbrella term for any technology that mimics human capabilities.
- Machine learning (ML) is one type of AI. Unlike traditional software that follows strict rules, ML systems learn and improve over time by analyzing examples and patterns in their data.
  - Natural language processing (NLP) is a specialized type of machine learning focused on helping computers understand human language. Many editing tools you already use, like Grammarly and Microsoft Word 365's Editor, rely on NLP to analyze text and suggest improvements.
  - Generative AI is another type of machine learning that can create entirely new content, including text, images, audio, and video, based on patterns it has learned.
    - Large language models (LLMs) like ChatGPT and Claude combine NLP and generative capabilities. They use NLP to understand your prompts and generative AI to create responses that sound like they were written by a human.

Why These Distinctions Matter for Editors

You might be thinking, "This is getting technical—why should I care?" Here are three reasons why these distinctions matter:

1. Clear communication with clients and colleagues.

When a publisher tells you, "Do not use AI," do they mean they don't want you using ChatGPT? Or are they also concerned about NLP tools like Grammarly or Microsoft Word 365's Editor? Without precise terminology, you might misunderstand their requirements and even violate your contract.

2. Informed decision-making.

Different types of AI have different strengths, limitations, and ethical considerations. Understanding these nuances helps you make informed choices about which tools to incorporate into your workflow.

3. Setting appropriate expectations.

Knowing what each type of AI can and can't do helps you set realistic expectations for yourself and your clients about how these tools might enhance (or potentially hinder) your work.

Without this precision in our language, we risk talking past each other—just like in the "vehicle" analogy where one person is talking about trucks and the other about skateboards. Neither realizes they're discussing different things, so the conversation goes nowhere.

I'll explore these distinctions further in my next post, where we'll take a detailed look at common editorial software tools and reveal which ones use AI and which don't. (The answers may surprise you!)

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