There’s a research paper that’s been making the rounds recently, a study by MIT’s Media Lab, that talks about the cognitive cost of using LLMs (Large Language Models that power AI apps like ChatGPT).
In the study, researchers asked 54 participants to write essays. They divided them into 3 groups – one that could use ChatGPT, one that could only use a search engine like Google, and the third (Brain-only) that couldn’t use any tool.
And, surprise surprise, they found that ChatGPT users had the lowest brain engagement, while participants who use only their brains to write the essays had the highest. ChatGPT users also had a harder time recalling quotes from the essay.
No shit.
Let’s leave aside the fact that 54 participants isn’t statistically significant and that writing an essay is maybe not a comprehensive test of cognitive load. The paper is essentially saying that if you use AI to help you think, then you are reducing the cognitive load on your brain. This is obvious.
Look, if you use ChatGPT to write an entire article for you, without any input, then of course you’re not using your brain. And of course you’re not going to remember much of it, you didn’t write it!
Does that mean it’s making you dumber? Not really.
But it’s also not making you smarter. And that should be obvious to you too.
Active vs passive mode
AI is a tool, like any other, and there’s a right way to use it and a wrong way to use it.
If I need to study a market to evaluate an investment opportunity, I could easily ask ChatGPT to run deep research on the market, and then write up a report. It would take a few minutes, as opposed to a few hours if I did it myself.
Even better, I can ask ChatGPT to make an investment recommendation based on the report. That way I don’t even need to read it!
But have I learned anything at all from this exercise? Of course not. The only work I did was write a prompt, and then AI did everything else. There was no input from me, not even a thought.
Again, all of this is obvious, but it’s also the default mode for most people using AI. That’s why the participants in the study showed low levels of brain activity. They asked AI to do all the work for them.
This is the passive mode.
But there’s a better way, one where you can use AI to speed things up and also learn and exercise critical thinking.
I call this active mode.
Thinking with AI
Any task can be broken down into steps that require critical thinking or creative input, and steps that don’t. In the market research example, searching doesn’t require critical thinking but understanding it and writing a report does.
In active mode, we use AI to do the steps that don’t require critical thinking.
We use ChatGPT Deep Research to find relevant information, but we read it. And once we read it, we figure out what’s missing and ask ChatGPT to search for that information.
When we’re done understanding the market, we write the report and we ask ChatGPT to help us improve a sentence or paragraph. We decide what information to put into the report but we ask ChatGPT to find a source to back it up.
And when we’re done, we ask ChatGPT to poke holes in our report, and to ask us questions that haven’t been covered. And we try to answer those questions ourselves, and go back to our research or ask ChatGPT to research more if we don’t have the answers.
Writing a report, planning a project, building an app, designing a process, anything can be done this way, you doing the critical thinking and creative stuff, and AI doing the rest.
You just need to make this your default way of using AI.
Practical Steps for Active AI Use
Here’s how to make active mode your default:
1. Start with Your Framework
Before touching AI, spend 5-10 minutes outlining:
- What you’re trying to accomplish
- What you already know about the topic
- What questions you need answered
- How you’ll evaluate success
This prevents AI from hijacking your thought process from the start.
2. Use AI for Research
Ask AI to find information but don’t ask it to summarize it without reading through it yourself
- Instead of: “What does this data mean for my business?”
- Try: “Find data on customer churn rates in SaaS companies with 100-500 employees”
Then draw your own conclusions about what the data means.
That’s not to say you shouldn’t ask AI to analyze data. You absolutely should, but after you draw your own conclusions as a way to uncover things you’ve missed.
3. Think Out Loud With AI
Use AI as a sounding board for your thinking:
- “I’m seeing a pattern in this data where X leads to Y. What other factors might explain this relationship?”
- “My hypothesis is that Z will happen because of A and B. What evidence would support or contradict this?”
4. Ask AI to Challenge You
After developing your ideas, ask AI to poke holes:
- “What assumptions am I making that might be wrong?”
- “What questions haven’t I considered?”
- “What would someone who disagrees with me say?”
5. Use the 70/30 Rule
Aim for roughly 70% of the cognitive work to come from you, 30% from AI. If AI is doing most of the thinking, you’re in passive mode.
6. Maintain Ownership of Synthesis
AI can gather information and even organize it, but you should be the one connecting dots and drawing conclusions. When AI offers synthesis, use it as a starting point for your own analysis, not the final answer.
7. Test Your Understanding
Regularly check if you can explain the topic to someone else without referencing AI’s output. If you can’t, you’ve been too passive.
When Passive Mode Is Fine
Active mode isn’t always necessary. Use passive mode for:
- Getting quick background on unfamiliar topics
- Formatting and editing tasks
- Generating initial ideas to spark your own thinking
- Routine tasks that don’t require learning or growth
The Long Game
The MIT study participants who relied entirely on AI showed less brain engagement, but they also completed their tasks faster. That’s the trade-off: immediate efficiency versus long-term capability development.
In active mode, you might take slightly longer upfront, but you build knowledge, develop better judgment, and create mental models you can apply to future problems.
The goal isn’t to avoid AI or to make every interaction with it a learning exercise. It’s to be intentional about when you’re thinking with AI versus letting it think for you.
Think with AI, anon.