The Impact of Generative AI on Critical Thinking [pdf]

The highest percentage of humans will take the easiest path provided. And while most of the above we just consider improvements to daily life, efficiencies, it has also fundamentally changed on average what we are capable of and what skills we learn (especially during formative years). If I dropped most of us here into a pre-technology wilderness we'd be dead in short order.

However, most of the above, it can be argued, are just tools that don't impact our actual thought processes; thinking remained our skill. Now the tools are starting to "think", or at least appear like they do on a level indistinguishable to the average person. If the box in my hand can tell me what 4367 x 2231 is and the capital of Guam, why then wouldn't I rely on it when it starts writing up full content for me? Because the average human adapts to the lowest required skill set I do worry that providing a device in our hands that "thinks" is going to reduce our learned ability to rationally process and check what it puts out, just like I've lost the ability to check if my calculator is lying to me. And not to get all dystopian here... but what if then, what that tool is telling me is true, is, for whatever reason, not.

(and yes, I ran this through a spell checker because I'm a part of the problem above... and it found words I thought I could still spell, and I'm 55)

For instance, LLMs are excellent at rewriting text in a specific style/tone. I used to believe I was quite good at that, but LLMs always do better. Now I no longer believe I am quite good. Did I become worse at text synthesis, or did I simply become more aware of my skills and limitations?

This is emblematic of a broader issue with self-reported data. It'd be good to measure critical thinking skills against earlier benchmarks for a clearer picture.

It's also important to not only focus on one skill, because while AI might make certain areas of our mind atrophy, others might now be more engaged. Just like when pocket calculators became popular and we all got worse at mental arithmetic but much better at applied mathematics overall. High level programming languages have made software engineers worse at comp-sci, but much better at applying it; commodification of cars made the average driver much less capable of understanding car mechanics, but much better at driving; and so on. My thesis is that human brainpower is not generally reduced by technological innovation, but changed.

One thing's for sure - cognitive changes in society (and especially how they relate to technology) is an area I'd like to see more research in. I think there are a few discoveries to be made there.

In my opinion this is a mischaracterization just as you stated others have "raged" [0] about. The simple question for you is: how do you know how to interpret? When precision and/or depth has no critical bearing I agree with your sentiment. However shades of grey appear in the simplest of prompts, often, quick. People who do not already have the skill to "interpret" the data, as you stated, can (and probably will) assume it is correct. That end user is also not constantly reminded of the age of the underlying data the model was trained on, nor are they aware how an LLM foundationally works or if it is reasoning or not - amongst many other unknowns.

Yes, while I feel as though the Microsoft report can have an air of "yes, that's the condition we expect" you're also not considering other, very important, inputs to that trivial response. Read the paper in the context of middle and high school students and now how does the "rage" feel? Are you a parent on a school board seeing this happen first hand?

Not everyone has the analytical pedigree of people like yourself and the easy access to LLMs is pissing people off as they watch a generation being robbed via the easy (and oft wrong) button.

[0] "It really has been a sight watching the loudest anti-AI people flog this around, then turn to rage when you clarify the range of the actual conclusion."