Why are AI hallucinations a risk in Instructional Design?

They can introduce false definitions, incorrect data, and misaligned learning objectives into courses, which damages credibility and misinforms learners.

How can Instructional Designers prevent AI hallucinations?

By verifying AI content against reliable sources, using clear prompts aligned with learning goals, implementing human review processes, and using AI as a drafting tool rather than a finaliser.

AI Hallucinations in Instructional Design: What You Need to Know

Q: What are AI hallucinations?

AI hallucinations happen when large language models (LLMs) generate content that appears confident and factual but is actually wrong, misleading, or nonsensical.

Hallucinations. Who would've thought this word would become part of our everyday instructional vocabulary? Thanks to AI, and more specifically large language models (LLMs), AI hallucinations are now something every Instructional Design team needs to understand—and guard against. So let’s dive into what they are, how they show up in content, and how to prevent them from derailing your next Instructional Design project.

Hi, I’m Bianca Raby—and if you're serious about high-quality, ethical Learning Design, this one’s for you. I’ve also made a video on this topic you can check out.

What are AI hallucinations?

AI hallucinations happen when your LLM generates content that sounds confident but is factually wrong, misleading, or just plain weird. For those of us in Instructional Design, this presents a massive risk—because inaccurate content damages credibility and can completely misinform learners.

The four most common AI hallucinations

1. Inaccurate content

This is the big one. Think: AI recommending a visit to the Ottawa Food Bank as a tourist attraction. Yes, that happened. For Instructional Design, this could look like false definitions, wrong data, or incorrect historical references slipping into your eLearning module.

2. Misaligned learning objectives

Ask for AI-generated module titles on blockchain, and you might get "Advanced Cryptocurrency Trading Strategies" in a beginner course. That’s an AI hallucination that sends your learners in the wrong direction—and it shows how AI can misinterpret scope.

3. Inconsistent tone and style

A professional-sounding introduction followed by a chatty, slang-filled explanation? That kind of tonal mismatch confuses learners and disrupts cognitive flow. And yet, it's a common AI hallucination error if Instructional Design teams rely too heavily on LLMs without editing for voice and structure.

4. Ethical or cultural missteps

Remember when Google Gemini generated racially diverse Nazi soldiers? It was certainly questionable. AI hallucinations can result in culturally insensitive content that not only offends but also undermines trust in your Instructional Design work.

How to reduce AI hallucinations in Instructional Design

You don’t need to ditch AI. You just need to use it wisely. Here’s how:

Always verify AI-generated content against reliable sources.
Give better prompts: clear, specific, and aligned to learning goals.
Implement a human review process—editorial eyes are a must.
Use AI as a draft tool, not a content finaliser.
Create clear style guides so tone and format stay consistent.
Stay up to date: new tools like ChatGPT-4’s Custom GPTs let you bake in your standards.

AI is a tool, not a teacher. When used well, it can supercharge your Instructional Design workflow—but only if you're alert to AI hallucinations.

Have you spotted an AI hallucination in your work—or in someone else’s Instructional Design work?

Until next time, keep creating with intention, and stay awesome.

AI hallucinations: what every Instructional Design professional needs to know