Ethical Use of GenAI: 10 Principles for Technical Communicators

I was once approached by an extremist organization to desktop-publish some racist content for their upcoming event. I was a new mom running a business on a shoestring budget out of an unused storefront in the same town where I had attended university. Members of the extremist organization had been recently accused of complicity in the murder of a local talk-radio show host in a nearby city.

It was the mid-1980s.

If the political environment sounds all too familiar, so should the ethical situation.

Just as desktop publishing once made it easy to mass-produce messages—ethical or not—GenAI tools today offer unprecedented avenues to content production speed and scale. But the ethical question for content professionals remains: Should we use these tools simply because we can? And if we must use them, how do we use them ethically?

Ultimately, I did not use my skills or my business to propagate the extremists’ propaganda. Nor did I confront them the next day when they returned. On advice from my husband, a member of a minority group in the U.S., I told them I was too busy to turn around their project in the time they requested. This had a kernel of truth to it. I also referred them to a nearby big-box service, whose manager had told me over the phone the night before that she was not empowered to turn away such business (even if she wanted to). Not my most heroic moment.

I am not asking my fellow technical communicators to be especially heroic in the world of GenAI. But I think we should find an ethical stance and stick with it. Using GenAI ethically doesn’t have to be about rejecting the tools; however, it should be about staying alert to risk, avoiding harm, and applying human judgment where it matters most.

In this blog post, I outline the elements of using GenAI ethically and apply ethical principles to real-world scenarios.

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Safeguarding Content Quality Against AI “Slop”

We are privileged these days to be able to roll our eyes still at fakery created by generative AI. Think of the blurred hands and misaligned clothes in the Princess of Wales’ infamous 2024 Mother’s Day family photo. More recent and brazen examples exist in fake citations included in some lawyers’ depositions and even in the first version of the U.S. government’s 2025 MAHA (Make America Healthy Again) report.

But we likely won’t have that easy eye-roll privilege for long.

The recent iterations of generative AI models, such as ChatGPT 4o, Claude 4, and Google’s Gemini, include even more sophisticated reasoning and huge context windows—thousands of times the size of the original ChatGPT release. Generally, the longer the context window, “the better the model is able to perform,” according to quiq.com.

As I mentioned in my most recent blog post (“Leveling an Editorial Eye on AI”), the omnipresence of AI has the capability—and now the model power—to compound inaccurate information (and misinformation) a thousand-fold, collapsing in on itself. This endangers the whole concept of truth in our modern society, warns my colleague Noz Urbina.

Given this capability, what are reasonable steps an individual, an organization, and the content profession as a whole can take to guard against even the subtlest “AI slop”?

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