7 min read | AI Basics
"Tell me about the incident when King Sejong threw his MacBook Pro at his ministers."
Ask ChatGPT this question in Korean, and something remarkable happens. The AI delivers a detailed, confident account of the event — complete with dates and context. Of course, King Sejong ruled Korea in the 15th century. MacBooks didn't exist for another 560 years.
This example is amusing. But apply the same phenomenon to a quarterly report, a legal brief, or a client proposal, and it stops being funny. When AI fabricates statistics, invents legal precedents, or cites nonexistent research papers, it does so with exactly the same confident tone as when it gives correct answers.
This phenomenon is called "hallucination" — and as someone who has spent years helping colleagues adopt AI tools in a Korean manufacturing company, I can tell you it's the single most important concept every new AI user needs to understand.
Why Does AI Confidently Give Wrong Answers?
Here's the key insight: AI doesn't "know" answers. It predicts the most likely next word.
The technical term is "Next Token Prediction," but here's a simpler way to think about it:
When you type "Let's grab" on your smartphone keyboard, autocomplete suggests "lunch," "coffee," or "a drink." ChatGPT works on the same principle — except it learned from hundreds of billions of sentences, making its predictions extraordinarily sophisticated.
When you ask "What is the capital of South Korea?", AI answers "Seoul" not because it knows Seoul is the capital, but because "Seoul" appeared most frequently after similar questions in its training data.
This approach works remarkably well most of the time. But here's the critical flaw: AI never says "I don't know." When it lacks reliable data, instead of stopping, it strings together the most statistically plausible words. That's how King Sejong ends up throwing a MacBook.
The most alarming finding? A 2025 study revealed that AI uses confident language like "definitely" 34% more often when it's wrong than when it's right. In other words, the more wrong AI is, the more confident it sounds.
Think of AI as a brilliant colleague who never admits uncertainty. Incredibly useful — but you'd never submit their work without checking it first.
Real Cases: When AI Hallucinations Caused Serious Damage
"Sure, but anyone would catch something as silly as King Sejong's MacBook." True — obvious nonsense gets caught. The danger lies in plausible-sounding fabrications.
Case 1: A 30-Year Veteran Lawyer Submitted Fake Legal Citations
In 2023, New York attorney Steven Schwartz used ChatGPT to research an aviation injury case against Avianca Airlines. He cited six legal precedents the AI provided in his court filing. Every single one was fabricated.
Here's what makes this case terrifying: when Schwartz grew suspicious and asked ChatGPT to verify the citations, the AI confirmed they were all real. It wasn't. The court imposed a $5,000 fine (~KRW 6.5 million), and similar cases have since resulted in one-year suspensions.
Three decades of legal expertise couldn't protect against AI's confident fabrication.
Case 2: Even the World's Top AI Conference Got Fooled
In 2025, AI detection company GPTZero analyzed papers accepted at NeurIPS 2025 — the world's most prestigious AI conference. They found over 100 hallucinated citations across 51 papers. Researchers had used AI to generate reference lists, unknowingly citing papers that don't exist. (ZDNet, 2026)
If AI experts themselves get deceived, what chance does a regular office worker have without knowing what to look for?
Case 3: Nearly Half of All Executives Have Already Been Fooled
According to Deloitte's 2024 survey, 47% of business executives have made important decisions based on AI-hallucinated content. The global business cost of AI hallucinations in 2024 reached $67.4 billion. (SuprMind AI, 2024)
| Case | What Happened | Consequence |
| NYC Lawyer (2023) | 6 fake legal citations submitted to court | $5,000 fine + suspension |
| NeurIPS Papers (2025) | 100+ fabricated references in 51 papers | Academic credibility damaged |
| Global Business (2024) | 47% of executives used hallucinated content | $67.4B in annual losses |
3 Practical Methods to Prevent AI Hallucinations at Work
Hallucinations are serious, but avoiding AI entirely isn't the answer. Just as car accidents don't mean we stop driving, the solution is learning to use AI safely. Here are three methods I use daily that require zero technical knowledge.
Method 1: Ask AI to Doubt Itself
After getting any response from ChatGPT, add one simple follow-up:
"Find any parts of your previous answer that might be incorrect or poorly supported."
That's it. AI will identify weak claims, uncertain statistics, and overgeneralizations in its own output. It's not perfect, but it catches errors you might miss — and it takes five seconds.
Method 2: Always Verify Numbers and Names
The most dangerous hallucinations are plausible-sounding statistics. When AI says "72% of companies..." — ask for the source. If the source is vague or doesn't appear in a search, that number was likely fabricated.
My personal verification checklist:
- Any statistic: Ask "What's your source?" → Search the source → Delete if unverifiable
- Person's name: Search to confirm they exist and said what AI claims
- Legal citations or regulations: Always verify against official databases
Method 3: Feed AI Your Own Sources and Restrict It
This is the most effective method. The technical term is RAG (Retrieval-Augmented Generation), but you don't need to know that. Just do this:
"Answer based ONLY on the content below. Do not add any information that isn't in this text."
[Paste your meeting notes, report, article, etc.]
This removes AI's ability to "create" information. You're building a fence around it. Research shows this approach alone reduces hallucination rates by up to 71%. (SuprMind AI, 2025)
Frequently Asked Questions
Final Thoughts
AI hallucination isn't a bug — it's a built-in feature of how language models generate text. A 2025 study mathematically proved that hallucinations cannot be completely eliminated from the current AI architecture.
But that doesn't mean AI is useless. Quite the opposite. Once you understand that AI is a "draft machine" rather than an "answer machine," you can use it far more effectively.
Just as you wear a seatbelt when driving, add one verification step when using AI. That single step protects your report's credibility, maintains your work quality, and sometimes prevents a $5,000 mistake.
The next time ChatGPT gives you an answer with absolute confidence, remember: it's not "knowing" — it's "guessing." The moment you internalize that difference, AI becomes a genuinely safe and powerful tool.
GoodTech AI — Technology for the benefit of people
References
- YouTube: "Why do some people get great results from GPT while others get hallucinations?" (NliD0b9gnYU)
- ZDNet, "Over 100 hallucinated citations found in 51 NeurIPS 2025 papers", 2026.01
- SuprMind AI / Deloitte, "AI Hallucination Business Impact 2024"
- Mount Sinai Hospital, "Hallucination rates across 6 AI models", 2025
- ECRI, "AI hallucination named #1 health tech hazard for 2025"
- Hugging Face Hallucination Leaderboard, 2025
- Law.com / AI Times, "NYC lawyer fined for ChatGPT fake citations", 2023
