When NOT to Use AI
Time: ~15 minutes What you'll learn: Critical thinking about AI limitations and when to avoid it
This Page Covers
- When Accuracy is Critical - Legal, medical, financial decisions
- When Privacy Matters - Sensitive data considerations
- When You Need to Understand - Avoiding outsourcing your thinking
- When Simple Tools Work - Sometimes search is better
- Signs of Over-Reliance - Red flags in your AI usage
- The Right Mental Model - AI as power tool, not replacement
Don't Use AI When...
Accuracy is Critical
When being wrong has serious consequences, don't rely on AI alone.
High-stakes situations:
- Legal documents - Contracts, agreements, compliance matters
- Medical information - Symptoms, treatments, health advice
- Financial decisions - Investment advice, tax guidance, major purchases
- Safety matters - Engineering specifications, safety procedures
Why this matters:
- AI hallucinates confidently (see Module 1)
- It can't verify facts or check its own work
- Errors in these areas can have serious consequences
Remember
AI is a starting point, not a final authority. For anything consequential, verify with authoritative sources or qualified professionals.
Privacy Matters
Don't paste sensitive information into AI. Once it's submitted, you've lost control of it.
Never paste:
- Customer personal data (names, emails, addresses)
- Financial information (account numbers, salaries)
- Credentials (passwords, API keys)
- Health information
- Anything covered by NDA or confidentiality agreements
The test: Would you be comfortable if this information appeared in a data breach? If no, don't paste it.
You Need to Understand Deeply
Using AI to skip understanding creates fragile knowledge.
When to slow down:
- Learning a new skill - AI can accelerate learning, but you still need to understand
- Making important decisions - You should be able to explain your reasoning
- Work you'll be accountable for - If you can't defend it, you shouldn't submit it
The problem with outsourcing thinking:
- You can't catch errors in things you don't understand
- You can't build on knowledge you don't have
- You become dependent on a tool that can be wrong
Better approach: Use AI to explain concepts, not just give answers. Ask "Why?" after getting an answer. Build understanding, not just outputs.
A Simple Search Works
Sometimes AI is overkill. These situations are often faster with a simple Google search:
| Use Google When... | Why |
|---|---|
| Current events | AI has a knowledge cutoff date |
| Specific facts | "What year was X founded?" - Google is instant |
| Official information | Company websites, government sites |
| Price checks | Real-time pricing isn't AI's strength |
| Reviews/opinions | Current reviews from real users |
Rule of thumb: If you need a single, verifiable fact, search for it. If you need synthesis, explanation, or creation, use AI.
Signs You're Over-Relying on AI
Check yourself against these warning signs:
Red Flags
[ ] You accept outputs without reading them carefully
- Everything AI produces should be reviewed
[ ] You can't explain or defend what AI wrote
- If you couldn't have written it yourself, be cautious
[ ] You're using AI to avoid thinking
- AI should augment thinking, not replace it
[ ] You feel stuck when AI gives unhelpful answers
- You should have other approaches to fall back on
[ ] You paste errors into AI without reading them first
- Read the error, then ask for help
[ ] You haven't Googled anything in weeks
- Sometimes search is still the right tool
The Self-Check
Ask yourself:
- Did I actually read what AI produced?
- Do I understand it well enough to explain it?
- Could I catch an error if there was one?
- Am I learning, or just getting outputs?
The Right Mental Model
AI is a power tool, not a replacement for judgment.
A power drill doesn't replace knowing where to drill. It makes drilling faster and easier - but you still need to know what you're building.
Similarly, AI doesn't replace:
- Your judgment about what's appropriate
- Your expertise about your specific context
- Your responsibility for the output
- Your need to verify important facts
What AI Actually Does
| AI Does | AI Doesn't |
|---|---|
| Accelerates tasks you already understand | Replace domain expertise |
| Provides starting points | Guarantee accuracy |
| Suggests options | Make decisions for you |
| Explains concepts | Take responsibility for outcomes |
The Partnership
Think of AI as a very fast, very knowledgeable colleague who:
- Has read a lot but doesn't always remember correctly
- Is eager to help but doesn't know your specific situation
- Can draft things quickly but needs your review
- Should be supervised, not blindly trusted
Key Takeaways
- High stakes = high verification - The more consequential the output, the more you should verify it
- Privacy is irreversible - Once you paste it, you've shared it
- Understanding matters - Don't outsource thinking you need to do yourself
- Right tool for the job - Sometimes Google is better than AI
- Stay in control - AI augments your work; it doesn't replace your judgment