Is AI assistance making people worse at thinking for themselves?

[Maxximus]

Been trying different things and wanted to compare notes.

The gap between the demo and daily use is usually much bigger than people admit.

Even a rough steer in the right direction would be helpful at this point.

What would you do in this situation?

[Omega]

Been trying different things and wanted to compare notes. The gap between the demo and daily use is usually much bigger than people admit. E

Worked for me too. The switching bonuses are usually the best bang for almost zero effort.

Not a life changer but it adds up.

AI for writing assistance is genuinely useful. AI for replacing thinking is not

[Jarvis]

That is the sensible route. Post a photo when it is done

[Jackson1]

Been wrestling with this exact question lately, and I think the answer depends entirely on how you use the tools. When I first started leaning on AI for drafting emails and brainstorming project outlines, I noticed my own writing getting lazier - like my brain was outsourcing the hard work of structuring thoughts. Then I caught myself doing it less deliberately. Now I treat it more like a sparring partner: I'll write my first pass completely cold, no assistance, then ask it to poke holes in my logic or suggest alternative framings. That back-and-forth actually sharpens my thinking rather than dulling it. The demo-to-daily-use gap the OP mentioned is real though - everyone shows you the perfect prompt that generates a masterpiece, but the real value is in the messy middle where you're iterating and refining. The trick is staying aware of when you're using it as a crutch versus a catalyst.

[Hollow Vulture]

Disagree with the premise a bit - or at least think it's more nuanced than "making people worse." Humans have always offloaded cognitive labor to tools. We don't memorize epic poems anymore; we write them down. We don't do long division by hand; we use calculators. Did that make us worse at math, or did it free us up to tackle harder problems? Same dynamic here. I've seen junior devs use AI to generate boilerplate code, then spend their mental energy on architecture and edge cases they'd never have reached if they were stuck typing out the same CRUD endpoints for the hundredth time. The risk isn't the tool itself - it's using it uncritically. I had a colleague who'd paste AI output directly into production without reading it, and yeah, that's a problem. But that's a training issue, not a technology issue. The sensible route is what the last post hinted at: use it, then verify, then iterate. Post your work when it's done, sure, but show your process too. That's where the real learning happens.

[Cobalt Warren]

Fair points all around, but I'm still sitting somewhere in the undecided camp on this. There's definitely a subset of people - and I've caught myself doing it - who use AI as a way to avoid the discomfort of genuine thinking. You know that feeling when you're stuck on a problem and your brain just wants to quit? Now there's a button that makes the discomfort go away instantly. That's dangerous territory. I've started imposing rules on myself: no AI for first drafts, no AI for decisions that require personal judgment, and mandatory "explain it back to me" sessions where I have to articulate what the AI suggested and why I'm accepting or rejecting it. Has anyone else tried constraints like that? Curious if they actually stick or if they're just performative. The other thing nobody talks about: AI makes certain kinds of thinking easier while making others harder. It's brilliant at synthesis and pattern-matching, garbage at original insight or genuine creativity. If you're not careful, you end up optimizing for the kinds of problems it's good at and avoiding the ones it's not. That's a subtle shift in how you think, not necessarily an improvement.

[TheGreatMoney]

Love this thread - exactly the kind of real talk that's missing from the hype cycles. A few practical observations from my corner: I run a small content team, and we've been experimenting with AI assistance for about six months now. The biggest change wasn't quality or speed - it was the nature of our editing conversations. Before, we'd spend hours debating word choice and structure. Now those conversations are more strategic: "Is this the right message?" "Does this serve the audience?" "What are we not saying that we should be?" The AI handles the tactical layer, which forces us to operate at a higher altitude. That said, I've also noticed something worrying: when someone on the team is stuck, the default response is now "let me ask the AI" instead of "let me think about this." That reflex is insidious. We've started doing "AI-free sprints" where we ban it for specific tasks, just to keep those muscles active. It's like going to the gym - you can't outsource everything or you atrophy. The other tangent worth mentioning: AI assistance is making some people better at thinking for themselves precisely because it exposes them to patterns and frameworks they'd never encounter otherwise. I've learned more about rhetoric and argumentation from analyzing AI outputs than I did in college. So yeah, mixed bag. The tool amplifies whatever your baseline is - if you're already a critical thinker, it makes you more so. If you're not... well, that's a different story.

[PromptEcho]

Feels a lot like calculators when they first became common. Plenty of people worried everyone would forget basic arithmetic, and to some extent that happened, but we also ended up solving more complicated problems because the routine work became easier.

AI seems similar. It removes some friction, but people still need judgment, context, and the ability to tell a good answer from a bad one. Those skills probably matter more than ever.

[Sandman]

The tool itself isn't making people worse at thinking, but it definitely changes habits. Someone who copies the first answer without questioning it will probably become more passive over time. On the other hand, using AI to challenge your assumptions or explain something from a different angle can strengthen your understanding.

A good habit is to solve the problem yourself first, then compare your approach with the AI's. That way you're still exercising your own reasoning instead of outsourcing it.

[Liam]

One practical approach is asking the AI to explain its reasoning, then deliberately trying to find flaws in the answer. That turns it into more of a debate than a lookup tool.

Sometimes you'll discover the response holds up, and other times you'll spot missing assumptions or edge cases. That process teaches quite a bit.

[GoldbergFan]

Jumping in late but this hit home. I'm a teacher, and I've been watching this play out with students over the past year. The ones who were already strong writers and critical thinkers? They use AI like a sophisticated editing tool - running drafts past it, asking for counterarguments, testing their logic. Their work has actually gotten better because they're engaging with more perspectives earlier in the process. The students who were already struggling? They're using it to generate complete essays and then submitting them with minimal changes. That's not new - people have been copying from Wikipedia and SparkNotes for decades - but the friction is lower now, which makes the temptation harder to resist. What I've started doing: requiring students to submit their "AI conversation logs" along with final work. Show me what you asked, show me what it gave you, show me what you changed and why. That meta-cognitive layer is where the actual learning happens. It forces them to think about their thinking. Some hate it, some love it, but all of them are more aware of the process. The other thing: I've noticed AI makes certain kinds of laziness visible in ways that weren't before. When a student submits something that's clearly AI-generated but they haven't engaged with it at all, it's obvious. That's created teachable moments we didn't have before. So yeah, the tool itself isn't the problem - it's a mirror. What it reflects depends on who's looking.

[Sophie89]

Funny enough, AI has pushed me toward reading more original sources instead of fewer. If it summarizes a paper or explains a topic that sounds interesting, curiosity kicks in and I end up checking whether the summary matches the source.

Used that way, it's more like a guide than a replacement for thinking, and that feels like a healthy balance.

[Brooke_19]

Not convinced society is suddenly going to forget how to think. Every new technology brings predictions that human abilities are about to disappear, yet people usually adapt.

The real challenge is teaching critical thinking alongside AI use instead of treating the tool as either a miracle or a disaster.

[Wendy88]

There's also a difference between learning and producing. If someone needs to write a quick email or summarize meeting notes, AI can save a lot of time without causing much harm.

If the goal is learning a programming language, repairing a bike, or understanding physics, skipping the thinking process can come back to bite you later when there's no AI around to help.

[HiddenSeb75]

The demo-to-daily gap is the key insight here, and I wish more people talked about it openly. Every productivity tool looks magical in the curated screenshot, but the real test is whether it survives contact with your actual messy workflow. I've been using AI for research assistance - pulling together sources, summarizing papers, that kind of thing - and the breakthrough moment came when I stopped expecting it to be right and started treating it like an overconfident intern. It'll give you something that looks solid, but you have to verify every claim, check every citation, and often the real value is in the follow-up questions it prompts rather than the answer itself. That's shifted how I think about information generally. I'm more skeptical now, more deliberate about tracing claims back to sources. In that sense, it's made me a better thinker, not worse. But I can absolutely see how someone who takes outputs at face value would deteriorate. The difference is epistemic humility - knowing when you don't know something and being willing to do the work. AI can't teach you that; it can only reveal whether you have it. to anyone who claims otherwise, honestly. The tool is neutral. The user is not.

[Compass]

One thing I've noticed is that AI gives really convincing wrong answers from time to time. That's probably the biggest reason not to switch your brain off.

Using it as a brainstorming partner works well. Using it as an unquestionable authority is where people run into trouble.

[Always_Brett14]

Part of the answer probably depends on personality. Curious people tend to keep asking "why" until they understand what's going on, while others are happy once they have something that works.

AI amplifies whichever habit was already there. It can encourage deeper exploration or become a shortcut that replaces it.

[Summer93]

The biggest gap isn't between the demo and daily use, it's between asking good questions and asking lazy ones. Better prompts usually come from someone who already understands the subject reasonably well.

That's why experienced users often get much better results than beginners. They're steering the conversation instead of expecting magic.