Don’t Expect AI to Think Like You—Because It Doesn’t

Photo by 胡 卓亨 on Unsplash

Ever typed a brilliant-sounding prompt into ChatGPT or another AI tool, only to receive a long, eloquent, and completely off-track response? You’re not alone. For example, a user asking for a simple summary might get back an overly complex breakdown or miss the key takeaway entirely.

As generative AI becomes part of our daily lives, from drafting emails to designing presentations, it’s easy to assume that these tools are thinking like us. But here’s the truth: they’re not.

A recent article from Psychology Today ("How Humans Think and AI Generates" by Dr. John Nosta, April 2025) sheds light on a critical distinction: humans think, but AI generates. And this difference matters more than most users realize.

Human Thinking vs. AI Generating

Humans think with goals in mind. We reflect, evaluate, compare, and adapt based on context, emotion, and memory. AI, especially large language models (LLMs), doesn’t do any of that. According to OpenAI’s own documentation and research, LLMs are statistical pattern generators: they operate by predicting the next likely word in a sequence.

As the Psychology Today article puts it: “Humans construct thoughts. LLMs generate continuations.” That means when you give AI a prompt, it’s not answering your question with intention—it’s simply completing a sentence that looks right based on its training.

Common Mistakes Users Make

Here’s where things get tricky: because the output is often fluent, confident, and neatly packaged, we assume it must be correct. But this assumption can lead us down the wrong path.

1. Assuming common sense: AI doesn’t understand everyday logic unless it’s encoded in patterns it has seen—such as common Q&A formats or frequent knowledge statements.

   
   

2. Expecting depth: LLMs can sound smart but often lack depth or coherence when pushed into nuanced or unfamiliar topics.

   
   

3. Believing in memory: Unless specifically designed with memory functions (like some fine-tuned models or with session tools), LLMs don’t "remember" your previous conversation in a meaningful, human-like way.

   
   

4. Taking output at face value: Just because it’s well-written doesn’t mean it’s well-reasoned. A Stanford study (2023) showed that LLMs can present plausible but inaccurate medical and legal information.

What You Should Do Instead

If you’re using AI tools in your daily work, these habits will help you get the best out of them:

1. Be specific and structured

A vague prompt like "Summarize this" might get a generic answer. Try giving structure: "Summarize this in 3 bullet points, each focusing on a key benefit for business users."

2. Verify everything

AI is not a fact-checker. Always double-check statistics, sources, and any critical information before using it. In 2023, the New York Times reported cases of AI inventing fictitious court cases and sources in legal briefs.

3. Iterate and refine

Think of prompting as a conversation, not a transaction. Try, tweak, and adjust until you get the clarity or creativity you need.

4. Know its blind spots

AI can hallucinate—make up facts or invent sources. It may reflect societal biases. For instance, a 2023 MIT study found biased outputs when GPT-3 was asked about ethnic or gender-related topics. Always read with a critical eye.

So What Can You Expect From LLMs?

When used wisely, LLMs are powerful assistants. They can help brainstorm, draft, rephrase, explore possibilities, and save time. But they need your direction, oversight, and judgment.

They don’t know your goals—you do. They can’t think ahead or weigh trade-offs—you can. In other words:

Don’t expect AI to think like you. Instead, learn to think better with AI.

Conclusion: Use AI, Don’t Rely on It

LLMs are not minds. They’re machines trained on patterns. And while those patterns can produce impressive results, they can also lead to flawed, biased, or misleading outputs if not handled carefully.

The more you understand how these tools work, the better you can use them. Not to replace your thinking, but to enhance it.

So before you trust the next AI-generated insight, ask yourself: Is this something the model truly understands? Or is it just finishing a sentence that sounds smart?