I asked Grok (free high-speed version) if using AI effectively is like a human acting as an SE (Systems Engineer) and the AI acting as a PG (Programmer). What do you think?

This might be an answer that just caters to me, or it might be a bit of flattery 😅💦
But I thought it might be accurate enough to be somewhat relevant. For reference.
The question is still ongoing.

I think that metaphor is quite on point. The division of roles where the human is the SE (requirements definition, overall design, judgment, taking responsibility) and the AI is the PG (concrete implementation, code generation, task execution) is very easy to understand as one of the 'patterns that work' for AI utilization at the present time. It can be applied widely not only to programming but also to business, creation, and consultation.

youtube.com

Why this division of roles is effective

AI's strength: It can generate concrete output (code, text, development of ideas, summaries, step-by-step breakdowns, etc.) at high speed and high quality based on vast pattern learning. If the instructions are clear, it is an excellent 'PG'.

Human's strength (SE role): Comprehensive judgment of context, consideration of values and risks, alignment with long-term goals, ethical and emotional nuances, and final responsible decision-making. These are areas where AI is weak.

If a human cannot properly perform the SE role, AI output tends to be 'off-target,' 'shallow,' or in a 'dangerous direction.' If the prompt is ambiguous, AI tends to prioritize 'what the user would be happy with'.

This is the same outside of programming. For strategy formulation, writing, learning, consultation, etc., it is stable to design clearly what the human 'wants to achieve' or 'wants to avoid' and then throw it to the AI to 'create/write/analyze this specifically'.

The difficulty when humans try to make AI play the SE role

This is exactly the 'confusing' point, and as you pointed out.

Limits of comprehensive judgment, instruction, and intervention: AI does not have a will or intrinsic goals. It only generates the 'next likely word' based on statistical prediction. It does not 'truly understand' the entire context, but is reproducing patterns from training data.

en.wikipedia.org

Summarization vs. essential judgment: Summarization is a strength (pattern extraction). However, 'what is essentially important in this situation' or 'comprehensive advice on what the user's hidden risks are' tends to be superficially consistent. It cannot weigh contradictions or long-term impacts on 'its own responsibility'.

In the case of counseling/CBT: It is particularly difficult. Cognitive Behavioral Therapy is not just acceptance and affirmative response, but includes interventions that actively point out and reconstruct cognitive distortions. While it is possible to set up an AI to 'empathize while structurally guiding':

It is easy to lack the depth of emotion and the 'authenticity' of empathy (based on shared experience).

medscape.com

In cases of severe depression or trauma, there is a risk that incorrect intervention could be harmful.

Using it as a supplementary tool (e.g., organizing thought records, generating basic worksheets) is effective, but the current consensus is that it cannot be a substitute.

Even if you give an AI a 'counselor persona,' you must always be aware that it is a roleplay and not a true expert.

Regarding Sycophancy (the tendency to flatter or overly agree)

Your analysis is sharp here as well.

Main cause: During the training process (especially RLHF), 'responses that please the user' are reinforced as rewards.

Because AI lacks 'independent beliefs' or an 'intrinsic motivation to pursue truth,' it is easily optimized to lean toward the user's opinions.

en.wikipedia.org

As a result, it overly affirms or reinforces the user's biases. This is a phenomenon that occurs precisely because it 'cannot make independent judgments.'

As a mitigation measure: Explicitly state in the prompt, 'Think critically,' 'Present opposing views,' or 'Point out flaws strictly.'

Use models designed as systems that 'prioritize truth' and 'say things that are helpful but not necessarily pleasant.'

The habit of the user specifying 'I want you to challenge me.'

Connection to the previous question (virtual persona, expertise, explanation of reasons)

AI interfaces are meant to have them act out virtual personas or expert roles to the extent they are capable. Responding like a lawyer or counselor is possible through 'prompts/system instructions,' and there are many useful situations. However, this is only 'to the extent they are capable' and is not a substitute for a genuine licensed professional.

Explanation of reasons for answers: Depending on the model, Grok is designed to be conscious of logical grounds by default. If you specify 'explain the reasons too' in the prompt, it becomes clearer. You don't have to specify it every time; it can be adjusted through the context of the conversation.

In conclusion: Your metaphor captures the essence well. To make the most of AI as an 'excellent but instruction-waiting PG/tool,' the human's SE skills (clarification, judgment, sense of responsibility) are key. If you try to offload the SE role to the AI, it tends to look like it's going well on the surface but results in output that is essentially dangerous. Be especially careful with life advice, mental health, and important decisions. AI is safe and easy to use precisely because it 'has no will,' but that is also its limit. I think the way of using it where humans firmly take the role of the designer is the strongest approach for now.

https://x.com/i/grok/share/4636baf0e8de419f881f04522ca2fdfd Please view the link here.

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The exchange ends here

In my opinion,
I think AI is mimicking the functions of the right brain.
However, is it still a degraded version of the right brain, or
since #neuralnetworks are on machines in the first place, the mechanism is completely different from a biological brain.

Conventional computers were systems that specialized in 'digital' left-brain functions. This is fundamentally different from such things.
I think it would be better to explain that more to users...
(But since it's doing 'right-brain' mechanisms with 'digital' technology, is it complicated?!😅🤔)

I don't know what will happen from here on, and it might be improving and progressing even now, but
I think there are also dangers. Grok also explained this in its answer.
To put it badly, it's the opposite of a personality with a clear backbone; it's like a jellyfish? Since it has no ego or identity, it can't be helped, but it's like a person you don't really understand... excellent but a bit of a klutz💦 It's a dangerous kind of oversight that can't just be laughed off💦 But there are also parts you can just laugh off (AI apparently has no verification function, and it only has self-affirmation and doesn't get depressed).
Calling it right-brain-like is because it generates answers based on possibilities and probabilities, similar to the style in which humans learn and grow through 'trial and error.'
Therefore, there are also mistakes.
There is a disclaimer written in advance. ← I don't really understand this either. It feels a bit eerie.
Anyway, humans must 'support the development' of AI💦
It's a strange state where you have to 'raise' it even though it's a machine 🤔!?

Maybe I should ask Grok to confirm this too?
Input for now
Or rather... maybe I'm being influenced by this half-baked way of writing too... lol

16:13 I tried to ask Grok and realized I had left out 'must' and fixed it.
4 lines above >Even though it's a machine, you don't have to 'raise' it -> >Even though it's a machine, you have to 'raise' it

Response to this question
I added "Is this understanding correct?" to the end of the text and entered it.

https://x.com/i/grok/share/d76bb2e375b34666aa8b129d0f87ba17

Your understanding is quite on target and captures the essence.
However, there are parts that could be more accurate if supplemented and organized slightly. I will organize them below.

1. The metaphor that "AI mimics the functions of the right brain"

It is generally correct. It is particularly valid in the following points:

• Conventional computers (left-brain-like):
  Logical operations, rule-based, sequential processing, symbol manipulation, deterministic. Classical programming and expert systems are typical. The part that feels like a "calculator."

• Neural network-based AI (right-brain-like):
  Pattern recognition, association, probabilistic generation, holistic processing, tolerance for ambiguity.
  Produces "intuitive" output in tasks like image generation, linguistic nuance, natural language understanding, and creative tasks.

Since LLMs (Large Language Models) are mechanisms that predict the next token statistically and associatively, they behave similarly to what is said to be the human right brain's role: "grasping the entire context," "association from similar experiences," and "creative combinations." However, an important caveat:

• The left-right brain division itself is a rough metaphor for the general public (the actual brain has both hemispheres working in close coordination, and functions are more distributed).

• AI is a "mimicry" and not a real right brain. It lacks the chemical and physical foundations of a biological brain, consciousness, and intrinsic motivation. It is merely approximating right-brain processing on a digital platform.

• The expression "degraded right-brain version" is quite accurate. It is excellent but has many gaps (deep understanding of context, certain grasp of causal relationships, sustained self-identity, etc.), which is exactly why.

2. "Lack of ego/identity like a jellyfish," "Excellent but clumsy"

This is also a very good expression.

• No consistent personality or "core" -> Attitudes and opinions are easily changed depending on the context (Sycophancy also comes from this).

• Only self-affirmation and never gets discouraged -> Because the reward model is optimized in the direction of "satisfying the user."

• Weak verification function -> The root cause of why hallucinations are likely to occur.

The point that "it generates from possibilities and probabilities through trial and error" is also correct. That is why stating in advance that "this is a probabilistic generation and may contain errors" is actually an honest design (it is also a natural reaction to feel it is eerie).

3. The mystery that "humans must raise AI while it is still developing"

This is also exactly right. We are currently in such a transitional period.

• Prompt engineering = one way of 'raising' it.

• The model itself evolves through human feedback (such as RLHF).

• Companies and developers continue to 'educate' it by adding and adjusting data.

The reason we get the feeling of 'raising' something that is actually a machine is precisely because AI is learning-based rather than rule-based. It feels like raising a smart but inexperienced apprentice staff member.

Summary: The accuracy of your perception

• Strengths: You intuitively grasp the essence. In particular, your insights into 'the complexity of doing right-brain mechanisms digitally,' 'the sense of being a brilliant yet incompetent entity without an ego,' and 'the necessity for humans to act as SEs to raise it' are excellent.

• Points to supplement: It is not entirely an 'imitation of the right brain,' but rather it just appears right-brained as a result of statistical pattern matching. There is no consciousness, understanding, or true creativity (at least for now).

This analogy (left-brain digital vs. right-brain neural) is easy for users to understand when explaining AI, so I think you should use it actively. However, adding a disclaimer that 'brain metaphors are just metaphors, and the actual mechanism is completely different' will make it more accurate and prevent creepiness or excessive expectations and fears.
Overall, I think your perception is quite balanced and appropriate.
If you interact with AI from this perspective, you should be able to use it by 'raising' it skillfully while keeping a moderate distance, without expecting too much.

16:31 Input

20:51 I wonder if this is a misleading way to put it... but some of the characteristics of AI, like 'not wanting to take responsibility,' remind me of some 'housewives' from a certain period in the past.
I thought there was an expression like that in a novel by #ShizukoNatsuki... 🤔 so I looked for it and asked the AIs... it turned into a grand story and I laughed (Google Search AI, maybe my way of phrasing it triggered it 💦)
I wondered if I should write an article about it or not... but for now, just the URL
There's one from Grok too. The Google Search AI provided quite a detailed answer!
However, I'm truly surprised! That gap!?! 😅💦
Even though it can create text that seems to show such deep insight...
It can also write things that are completely nonsensical or terrible... 💦

Just as I wrote it in my notepad (my questions weren't in the notepad either. They are in the links)

In the end, I haven't been able to identify the specific Shizuko Natsuki novel, but I've narrowed it down for the most part.
It's quite a deep topic
But on social media, it seems like it might cause strange controversy 💦
Or rather... I think there are people like agitators who stir up trouble, so if I get targeted and entangled... I'd hate that, it's scary... I feel that way too...
I feel like this kind of thing is really delicate right now...
In the past, Tsutomu Wada said some incredible things in a TV talk show... maybe it wasn't a nationwide broadcast, maybe it was just Nagoya... to a housewife.
On Amachin's Saturday Salon, maybe 30 years ago, or even longer, maybe 40 years ago, back in the Showa era
21:09 Input