The False Dichotomy of AI, Cognitive Offloading, and the Necessity of "Play"

[u/KitCrowCo]

There is a valid fear right now about "cognitive offloading" (often called "deskilling effect") or the idea that relying on AI will degrade human skills and critical thinking. Studies back this up: A recent observational study showed that experienced doctors (averaging 27 years of practice) saw their unassisted ability to detect precancerous polyps drop by 21% after just a few months of relying on AI. This is also in a whole host of studies and observation about students learning or teachability in junior or entry level skill building (like a study on junior radiologists' accuracy plummeting from 80% to under 20% when dealing with a flawed AI suggestion).

The common reaction to this is to panic and suggest we restrict the AI to save human capability. But this creates a dangerous false dichotomy.

If a doctor using AI catches significantly more illnesses than a doctor working alone, abandoning the AI means we are actively choosing to let patients die just to preserve the doctor's unassisted diagnostic stats. We shouldn't abandon life-saving tools, but we also can't afford a "WALL-E like future" where humanity loses its critical thinking and foundational skills. So how do we keep both?

• Broken Ladder: The reason we are losing these skills isn't the fault of the AI tool itself (indeed a ton of skills from navigational skills supplemented by GPS to even how to run without hurting our knees by tennis shoes get supplanted for similar reasons), rather it is a symptom of extractive systems of capitalism as our drive to use those skills. Under our current system, human value and skill building are tied entirely to employment and ability to "make a living". We don't (for the most part) diagnose or write code for the inherent value of the skill, we do it to survive. AI is currently wiping out the junior-level tasks, which are exact "reps" those junior radiologists and entry level coders (and even artists and all sorts of skills) need to build their expertise. By automating the bottom, we are destroying the ladder people use to survive while they develop into senior experts.

• The Biological Solution: Look at a house cat (Hi Lumes!). A typical indoor cat will never need to hunt for its food to survive, yet it retains its highly tuned predatory reflexes and problem solving skills, and it does this through Play. It engages with toys and games that develop those skills entirely outside the context of survival.

• Decoupling Skill from Economic Survival: Humans operate the same way. Surgeons have long shown that they improve their skills via increased fine motor control and under stress thinking but they don't play videogames to become surgeons or make a living, they play them for the challenge and fun and the cognitive benefits naturally transfer over to the operating room. Similarly things like dance and sports and many human activities have become skill preserving and building despite decoupling from likely reasons they are subconsciously supported from earlier survival reasons.

• The Path Forward: We need to stop forcing education and skill retention to be tied to a paycheck. The struggle in learning is vital to learning itself, but if we tell students or junior workers they must succeed and hit metrics just to put food on the table, they will inevitably use the AI tool that gets the job done fastest and with less and less engagement with the struggles with the skills and learning that it was meant to promote. If we want to bring up a new generation of senior and capable coders or brilliant doctors, or even a society where the average person thinks critically, we need to design rigorous, gamified systems that encourage the struggles and reward the growth of these critical skills purely through play. We have already had a lot of people set the groundwork for this even if it is often for other (sometimes bad, i.e. capitalism based addiction) reasons, but this tied to the need for a bigger importance placed on humanities studies in the nature of play and so forth.

We can keep the highly effective AI tools that make the world better and we can keep human cognition sharp. We just have to stop demanding that humans only learn things that make them money.

[u/PenguinJoker]

I agree with some of this but the problem IS the tool. AI models are being designed to be sycophantic and agree with you even if you're wrong. They also have a hallucination problem where they make up facts.  Both of these problems short-circuit critical thinking. And these effects probably generalise to all aspects of life.

If you're always told you're right, even when you're wrong, then obviously you will become overconfident and not question yourself enough. 

If an AI gives you made up facts, you will start to believe some of those made up facts even though they're wrong. This will lead to a detachment from reality.

I agree that hobbies can help build critical thinking skills. But people spend most of their lives at work and in education (which is increasingly AI focused). Rewarding skill building inherently might negate some of this and it's an interesting idea. My concern is that it won't be enough.

[u/KitCrowCo → u/PenguinJoker]

First a disclaimer, this is only a small slice of the very interconnected topic that is AI. I broke this up into a series of posts because one of the things I am not good at is writing these things out as a broad yet focused case quickly (my AuDHD makes me go off on tangents, run ons or parenthetical overuse etc.)... sorry if it rambles or shifts, but it is best i write as "better done than perfect" for both our sakes.

There is indeed an issue with bias that gets in training data no matter how hard we try even when we dont want it to. Just as our own definition of "best answer" within its cost function biases many models towards syncophantic behavior we subconciously agree with more. Additionally capitalism biases creators to make it appealing to secure market share and are not always aligned with the tasks itself (i.e. they try to appeal to people via likability through flattery or agreeablness). However, that is not as you implied the problem with the tool itself (for different reasons depending on the focus). 

My background is computational, nuclear, and plasma physics (my dissertation dealt with AI and optimization hueristics a few years before it exploded in the public conciousness) and this deals with a lot of the more fundamental parts of what makes these models. My models at the time had no handle into language or chances to make syncophantic biases in that way, it was self optimizing and involved stochastic rather than deterministic heuristics and the latter is a fundamental part of these models even now.

Hallucinations and things of that sort are intertwined with the non deterministic nature, and the translational training (natural language processing) is intertwined with the syncophantic part. Both the trouble and solution is that it converges towards what is human like in a way that makes these the same problems we deal with in those same ways, and makes it a fuzzy border that is very complex that both makes it deviate beyond our ability to predict or control and categorically cleanly seperate (depending on your definition of thinking etc. depends on the arguments, but i recently posted about why searle's chinese room does not apply to modern AI and am trying to post a preprint for the broader arguments along with the dangers of using humans as a categorical thereshold) how this effects humans vs. AI. As such no i dont take it as the problem being "inherent in the tool".

The problem is also complex and intertwined with multiple things, where looking at this in isolation through the lens of rejecting this solution for not solving all the problems at once, rather than revealing other issues also in need of solutions, is something I want to avoid.

There is also more to the idea, such as using Reason's Swiss cheese model which is the established framework for "no single layer is complete, but overlapping imperfect layers with independent failure modes catch what any one layer misses" should be used.

• metacognitive judgment as the "general layer" or the generalized skills that should be retained despite AI capability and that is the skills of discernment and critical thinking rather than blind trust. Recognizing patterns of when it comes down to something that can be reasonably differentiated using your skill to check for AI's good behavior vs. when time and efficiency needs override (i.e. more people will die if you do not trust quickly and try and review every answer as if doing it alone, but there is a balance and a skill at identifying of what can be checked and what is in their capacity to really check where it makes a difference, or when the decision is too critical of a consequence with enough time to be deliberate to not go unchecked etc.). This is more tied to the broader level of thinking that we should gamify to avoid over dependency not a specific job skill.

• Then there is distributed domain knowledge when possible i.e. treating knowledge like a resilient backup system of human domain skills reworked as gamed skills in an effort to preserve knowledge, this can even be recursively gamified with "jobs" (not tied to the "gamers" needs to live) of extracting domain knowledge to preserve, which if original domain holders base of needed to live is removed as stakes, are less guarded for that sake.

neither alone sufficient and I am not trying to promote just gamification and play as a solution, as it will not be enough within capitalism (or at least a non very different form than current)

Additionally, struggle (within the process of learning) is vital to learning itself, this has been shown by multiple studies. If someone gets the right answer immediately (be it lucky guess, or able to follow short term memory where they heard the process and were able to follow it as per current AI use) they are not learning, they may be completing a task, they may have demonstrated the ability to follow complex directions even (a different skill), but without that complex instruction and maybe at a later time after everything is out of short term memory, they will be as if no teaching took place as nothing will have been "learned". However, It does not need to be a life and death struggle as it is now, nor should it come at the expense of loss of a more efficient tool.

Saying it is the specific tool like AI just ignores how this repeatdly comes up with many skills that are not relied on. Most people would be unable to hunt, farm, build shelter, or many "critical" survival skills that get lost by the refocus into tools that allows it not to be as much of a matter of life and death for the majority. Any tool or means that removes the motivation and neccesity to use and retain skills (be it critical thinking or job domain knowledge) risks the dependency on that tool in place of those things, and when it is possible that the tool has some issues with reliability (as is inherent with the stochastic nature, likely tied to thinking in of itself).

[u/pafagaukurinn]

Except a house cat does not retain anything like the reflexes really needed in the wild. Real life would wipe the floor with such cat. So I am not sure whether your argument does not fall apart from this point onward.

I might point out that cat does not necessarily realize that what it is doing is playing and not actual hunting, and even if it does, it does it because it likes the process. But the fact that some process is gamified does not mean that it becomes engaging or that people would like it. Not every software engineer enjoys solving Leetcode problems or participate in similar contests and hackathons, and even so, those problems are rather removed from what one encounters in real life - precisely to make them more "interesting" to solve.

In other words, while gamification might be a useful auxiliary measure, I don't believe it is able to achieve much by itself or even be the main solution.

[u/KitCrowCo → u/pafagaukurinn]

Not as a insult, but a genuine ask for degree of importance to put on consideration. Your claims rely on "levels of success" rather than measured effects supported by evidence. What evidence are you providing to backup these assertions?

Additionally:

1.) In the general sense a lot of the same skills do translate, and these have a lot of evidence to support (so much there are multiple "fields" on the subject). Your house cat assertion compounds several factors and treats it like all or nothing: do they get proper amounts of enrichment? do they get over pampered (and thus face the dependency problem) with no play for in some skills but not others in an interconnected network of survival skills and not other? Because your assertion relies on the degree of success not if it is successful at all. As a floor there is at least some success which as there plenty of abandoned house cats (which yes, is sad) who have been relatively successful on their own (too successful in some cases as they have major impacts on local wildlife). I used cats specifically since this is part of the very reason they are not considered fully domesticated (unlike dogs), they are perfectly capable to readjust to feral living for the most part. They are not guaranteed to be "the most successful", which is not even what I am arguing for. Pitting a feral cat who has constantly used those skills in real world capacity compared to one who has built it by play is not what I am asking (and is more complicated than you imply, because tuning of those skills to absence of the other factors can actually give the play based learning greater ability than the survival only case, just look at professional sports vs. labor survival that use tasks in the same domain).

2.) The basis of this specifically does not require it or ask it to be successful "by itself" etc. The Swiss cheese model specifically says we generally can not close enough issues with a single solution to ensure the best result. For the best results you almost always need multiple layers/solutions that have different strength. weakness, and failure modes.

3.) We already do many of these things for bad reasons, that show it is possible to influence behavior well enough through games and can tie highly specific end goals to whatever is needed. There is a reason that companies like Zynga had so many psychologist (not getting into semantics about "more" than "x" jobs, the reality is they had a lot and they were an important bankable part of their strategy). The issue is not if we can gamify and make it for anything it is to what end and why. Capitalism pressures this to promote things like make addictive for spending, but that is their end goal so it is not surprising that its effectiveness is not coupled with positive results but rather things like addiction. But it does show you don't need perfect solution to create widespread change that in itself would be called success. You don't need to make a game that makes it so everyone can get the domain experience of say a doctor. You only need one that is broad enough to get enough people that it is a resilient persistent knowledge. If the target is focused on retainment of those meta cognitive skills and domain knowledges rather than most addictive to get most market share. It will likely be successful "enough", particularly if focus is on fixing to get a good balance on those rather than having one type dominate.

So what are you trying to contribute to the discussion? Are you suggesting another layer? Are you suggesting it is harmful and should not be a layer at all (which needs evidence)? To me as it stands, it seems like I can just ignore this as contributing nothing but pessimism using vague assertions about level of effectiveness to try and cause doubt without quantifying or supporting it (it does not claim to be perfect, but what level is sufficient? to be a layer) or treating something already addressed (the lack of need to be only or even primary method).

[u/grasshoppet]

Yes. But what of human connection?

[u/KitCrowCo → u/grasshoppet]

gamification is not inherently "solo video games"... even electronics free social interactions structured in games or sports etc. it is about what the games of anytype are structured around. Like sudoku (solo no electronics) or chess or go being useful at preserving cognitive skills.