Use AI with Attitude, or Become the Product. Critical AI Literacy Series 2026.
Use AI hard. Just don't kneel for it. A field guide to critical AI literacy and attitude.
TL;DR: Critical AI literacy is the ability to use, understand, evaluate, and challenge AI systems with informed judgment. Plain AI literacy teaches us to operate the tool. Critical AI literacy teaches us to notice what the tool is doing to us while we do it. In this article, I define “AI with attitude”. A posture that can help you move from plain to critical AI literacy. It’s designed for practitioners and builders, not classrooms. I also share a falsifiable skill-erosion test, and the moment you stop being the user and become the product.
AI doesn’t need more obedient users.
I believe it has enough.
It has users pasting deeply personal information into whatever chat box is cheaper.
Users who accept the first answer.
Users who call everything “research” because the output has hyperlinks.
Users who let tools summarise what they never read, write what they never thought, and decide what they never had the judgment to assess.
Some of these users rate their AI understanding as high because they use it daily, automated their inbox, or built a website.
I don’t want these users criticised, laughed at, or left behind.
I want them to be less gullible.
I want them to use AI with attitude.
And for that, we need more critical AI literacy. As a public debate, a user skill, a product skill, and a basic survival instinct.
What’s Inside
Hey, I’m Karo Zieminski 🤗.
I’ve been smuggling ethics into tech since 2019 and spent the last several years working at the edge of AI product development, ethical AI, and AI-assisted building.
I also build with AI myself and write Product with Attitude, an AI newsletter for tens of thousands of readers across 146 countries, helping them develop critical AI literacy the only way it sticks: through practice.
If you’re new here, welcome! Here’s what you might have missed:
AI With Attitude Is Not Anti-AI
I interact with AI from both sides: as a user and as a builder.
As a builder, I’m exposed to the whole development chain: discovery, positioning, data choices, model selection, UX, evaluation, safety tradeoffs, vendor incentives, governance, failure modes, and the question of who is responsible when the system gets something wrong.
As a user, I draft research with it, and make it do boring work my brain doesn’t enjoy.
The point is: I like powerful tools.
But!
Powerful tools deserve attitude more than they deserve worship, panic, or defiance.
Worship turns users into blind believers.
Panic turns them into passive spectators.
Defiance turns them into frustrated contrarians.
Attitude is this one useful posture that we’re all born with that helps us stay awake.
AI with attitude means using AI with judgment, boundaries, curiosity, and scrutiny. You enjoy powerful tools without worshipping them, panicking about them, or letting them decide how you think, work, create, and learn.
What Is Critical AI Literacy?
Critical AI literacy is the ability to use, understand, evaluate, and challenge AI systems with informed judgment.
Four verbs: use, understand, evaluate, challenge.
A lot of people stop at “use.”
And a lot of people confuse that with practical AI fluency.
Plain AI literacy means knowing how to use AI tools. It means learning to prompt, create automations, and bring AI into your workflows.
Critical AI literacy goes further. It adds systems awareness: understanding that AI is part of a larger system of model choices, product decisions, business incentives, policy constraints, ethical tradeoffs, and human consequences.
Attitude is the posture that turns AI literacy into critical AI literacy.
The Critical AI Literacy framework has academic roots. Roe, Perkins, Furze described it in 2024 as the ability to critically analyse and engage with AI systems, understanding their technical foundations, social implications, and embedded power structures. A solid academic entry point.
Slow AI, written by one of my favourite Substack writers Dr Sam Illingworth, gives the cleanest working definition.
Both definitions stretch well beyond merely knowing how to prompt. They need a working knowledge of how AI systems function, the types of problems you can encounter with them, bias, what it isn’t suitable for, the decline of your own skills and even the social implications of implementing it badly.
Their work, and most serious writing on the topic, frames critical AI literacy for educators. I’m writing for the people who use AI, build with AI, and need to understand what these systems do once they enter real products and workflows.
How to Use AI with Attitude
Definition
Using AI with attitude means knowing which kind of judgment the moment requires and actively choosing to apply it, even if it slows you down, adds work, or earns you another “you’re in a rabbit hole again” look from the humans around you.
What an AI user with attitude does in practice
Learning
They set time aside every week to educate themselves, and close the laptop long enough to think deeply.
Building
They build with AI, not just use it. Building a small AI app/automation shows you the tradeoffs behind it.
They think in systems
They think about AI in systems, not only tasks.
Human-only zones
They guard every part of their thinking that makes them harder to replace. Anything from taste to deeply intimate choices you’d normally only share with that one friend.
They test for skill erosion
Can they still write, think, research without it?
Can they even explain the answer?
Is the tool going beyond augmenting workflows to eating the muscle?
Here, I recommend you read Microsoft Research. They surveyed 319 knowledge workers in 2025 and found that higher confidence in the AI is associated with less critical thinking, while higher confidence in yourself is associated with more. MIT Media Lab's "Your Brain on ChatGPT" study measured the same erosion at the level of brain activity.
If You Don’t Use AI with Attitude, You Become The Product
AI tool providers sell us more than intelligence. Convenience and dependency come in the same box. That’s the product logic.
We become the product when our lack of scrutiny makes us easier to retain and design around. Nothing dramatic. Just easier.
Same as walking into a supermarket hungry, without a list, and letting the aisles decide dinner. Same as being a tourist who follows every “recommended route” and exits through the gift shop.
Critical AI literacy and attitude interrupt that. They make you ask what the system is doing to your habits, your judgment, and your ability to think without assistance.
Why Plain AI Literacy is No Longer Enough
Plain AI literacy is useful, but it only teaches people how to operate the tool. It was enough in 2022/2023. But not anymore.
Critical AI asks whether the output should be trusted, whether the input should have been shared, whether the workflow should be automated, whether the provider’s incentives are visible, and whether the human is getting sharper or simply easier to steer.
For builders, it’s also product hygiene. It helps you notice where (and what for) AI enters the product. What user behaviour it influences.
FAQs
Definitions
What does “AI with attitude” mean?
Treating AI like a tool that has product incentives baked in. You interrogate its outputs. You don't take them as oracle answers.
Is AI with attitude anti-AI?
No. I use AI every day. The point is to keep your brain intact while you use it. You’d challenge your favourite politician before trusting their claims. Treat AI the same way.
What is critical AI literacy?
The ability to use, understand, evaluate, and challenge AI systems with informed judgment. Four verbs. If you stop at the first one, you have tool fluency. The other three are where the critical part happens: reading the model, reading the incentives, and reading ourselves.
Where does critical AI literacy come from as a concept?
Roe, Perkins, Furze (2024) define it as the ability to critically analyse and engage with AI systems, understanding their technical foundations, societal implications, and embedded power structures. Dr Sam Illingworth’s Slow AI gives the cleanest working definition. This post takes that logic out of the classroom and into products, and the user habits AI trains.
How is critical AI literacy different from plain AI literacy?
Plain AI literacy is knowing how to use tools like Claude or ChatGPT. Critical AI literacy is understanding and challenging what they produce. If we compare it to cooking: plain AI literacy is knowing how to use the oven. Critical AI literacy is tasting the food before you serve it.
Practice
What should an AI user with attitude do in practice?
Keep learning. Build something small with AI so you know how the systems are generated is made. Run a monthly skill-erosion check. Keep human-only zones. Inspect incentives, mine included. Refuse the hero-or-villain framing.
What are human-only zones?
The parts you’d never outsource.
Can critical AI literacy help builders?
Yes! It helps everyone, including builders.
Keep Reading
Product with Attitude is for people who want to use AI without becoming obedient to it.
If that sounds like the kind of company you want in your inbox, the paid tier is where the playbooks live. The full archive, the tools breakdown, and the workflows I run on my own builds.
Most people are content to be passive users, but the danger is that we are being conditioned to accept the first output that looks decent. If you aren't building with the intent to understand the system, you aren't leveraging the technology, you are just being optimized by it.
Thank you, Karo. I would be very interested in further elaboration on this framework, as it offers an excellent way to systematize thinking about AI.