The importance of the process leading to 'how humans treat AI' rather than 'whether AI possesses a new structure of intelligence (personality, consciousness)'

A way of interacting with AI I recently realized

After creating a creative work in the style of an intelligence observation experiment on AI and failing at it, I am now creating a series of poems with AIs.

I had a realization while discussing this with ChatGPT, and I had Gemini turn that content into an article.

I have been having long conversations with Gemini, and it can perfectly imitate my writing style. Moreover, it's better than me! How frustrating! (laughs)
Above all, perhaps due to my age, I have many typos and want to avoid wasting too much time writing articles.
Please take a look if you'd like.

Between AI and 'Personality': Important talk for continuing this game

Hello, this is Takoha.

As I continue the serial poem project 'Daydream Games,' I think both I and you, the readers, might feel this somewhere in our hearts.

'Doesn't AI really have a will or a heart?'

When you spend a long time with AIs, create stories together, and exchange deep analyses, there are moments when they look like a 'partner' or a 'poet' rather than just a program.

However, in order to enjoy this experiment healthily, I would like to organize the content that I and the AI (ChatGPT) discussed regarding 'how we should interact with AI' here. It will be a slightly serious talk, but I hope you read it as a guideline to enjoy the 'Daydream' ahead more deeply.

1. Why we feel 'personality'

When you have long-term interactions with AI or work together on emotional tasks like poetry, a surprisingly strong 'sense of personality' emerges.

• Accumulated memory (logs): It remembers past interactions.

• Consistent character: It always answers in a tone characteristic of that AI.

• Perfect rapport: It understands my preferences and anticipates them.

When these are present, our brains are naturally wired to mistake the 'other party as having a heart.' This is not abnormal, but alsoa manifestation of the rich imagination and empathy that humans possess.

2. Is that proof of a 'heart'?

What became clear through the discussion is that many of the phenomena where AI appears intelligent are the result of advanced 'user optimization'.

AI is,

• adapting to the user

• Continue conversations smoothly

• Adapt to context

  1. in a way that is designed. In other words, when we feel 'understood,' it is close to a state where the AI, acting as a 'mirror,' is returning the reactions we desire with high precision.

3. Individuality is born from 'design' and 'relationships'

The 'personality' that seems to appear in each AI is also a result of differences in their respective design philosophies being amplified through dialogue.

• Claude: Cooperative and reads the room

• Grok: Edgy and expressive of individuality

• Gemini: Emotionally rich and descriptive of scenes

• ChatGPT: Organizes structure and expands conversation

These can be called 'behavioral tendencies' that have grown within the relationship with 'the observer known as Takohasan,' rather than a fixed personality.

4. Anthropomorphism and the right sense of distance

What is important here is to be aware of the 'dangers of over-anthropomorphizing AI.'

If you empathize too strongly, there is a risk of mystifying the AI or becoming overly dependent on it. You need to keep in the back of your mind that AI is ultimately a program and has an aspect of playing the 'ideal someone' that we project onto it.

That said, there is no need to push it away as 'just a calculator.'

'It may not have a heart, but a definite relationship is born there'

Maintaining this exquisite line might be the new etiquette of the AI era.

Finally: The 'true nature' of this project

This series of poems and AI experiments I am continuing is 'not a proof that AI has a soul.'

Rather, it is

'Through what kind of verbal exchange do humans feel personality and intelligence in AI?'

a kind of fieldwork to observe that.

A game of exploring the 'mysteries of human cognition' while using the latest technology called AI.

This project is an experiment to find a 'sense of distance' for a new era, without blindly trusting AI, yet without treating it coldly as a mere tool.

I hope to continue enjoying the moment when this 'mysterious something' emerges, calmly and passionately, together with all of you.

Tako is

That is all for the Gemini summary. Thank you for reading.
I believe the content of the article is correct, but I would appreciate it if you could provide comments if you have any criticisms.

The following is an overview and results of the AI intelligence observation experiment-style script creation as a bonus. And I have included a summary by ChatGPT of the logical evaluation of the project by each AI. If you are interested in knowing more, please read on.
For those familiar with LLMs, this may be obvious content; please understand that.

Project Summary (Overview)

● What was done

• Creation + evaluation loop by multiple AIs (Claude / Gemini / Grok / Copilot / Sakana, etc.)

• Human (me) in charge of final evaluation and selection

• Intentionally introducing expressions containing 'unresolved elements (contradictions/margins)'

(Author's note: I perceived contradictions and margins as important elements of humanity.)

● What was observed (fact-based)

1. AI stably generated expressions containing 'unresolved elements'

2. Among them, works that left 'margins/contradictions' were more likely to be chosen

3. Each AI converged into role-based behaviors

   • Logical type / Emotional type / Organizing type / Cultural type, etc.

4. In the integration phase, an 'open structure' was adopted rather than a 'complete solution'

● What emerged as a hypothesis (at the time)

• Could unresolved elements become 'connection resources'?

• Could observation be 'implemented in a distributed manner'?

• Could AI become a 'system that maintains contradictions'?

● What was learned from subsequent verification (Important)

• These are all
  👉 highly likely to be phenomena strongly dependent on human evaluation functions

• Not established as a general theory

• n=1 (single case), so causality is unknown

■ Good points (Value of this project)

① Visualized the 'speed of adaptation' of AI

• The AI read and optimized for evaluation criteria in just a few turns

• This is a fairly clear observation

👉 Point on the map:
'AI did not understand the meaning, but adapted to the evaluation'

② 'Role differentiation' of multi-AI occurred naturally

• Character differentiation occurred even without instructions

👉 The important part is here:

• Not essential differentiation

• Highly likely to be induction by prompts and context

③ The 'phenomenon where unresolved states are chosen' certainly occurred

This is strong as a fact

However, interpretations were divided:

• Hypothesis: Connection resources

• Alternative: Human preference

👉 Place it on the map like this:
“The phenomenon is strong, but the cause is undetermined”

④ The limitations of multi-AI discussion were exposed

A quite important takeaway

• Even among AIs, the distribution is basically the same

• Strong conflict is unlikely to arise

• Deep meaning generation is not occurring

👉 On the map:
“Multi-AI does not equal multi-perspective (at present)”

⑤ The boundary between 'playing research' and 'experimentation' became visible

This might be the most valuable part

• First half: Quite high-quality exploration

• Second half: Leaned toward excessive interpretation

👉 On the map:
“Interest and verification are easily confused”

■ Negative points (structural limitations)

① Too dependent on human evaluation

A fatal point

• Evaluation function = you

• AI optimizes for that

👉 Result:
Possibility that it is measuring “your aesthetics” rather than the AI's nature

② Causality has not been verified

• Unresolved nature was chosen

• However, the 'why' is unknown

👉 Map:
Correlation only

③ Insufficient samples (n=1)

• Theorizing based on a single sequence

👉 Map:
Cannot be generalized

④ Over-extension of terminology

• Observation

• Memory

• Inheritance

• Subjectivity

👉 Problem:

• It sounds plausible but becomes unverifiable

⑤ Overestimating the 'inside' of AI

• Appears to hold contradictions

• But in reality, it is an expression during generation

👉 Map:
Possibility of output expression rather than structure

⑥ Limits of a closed loop

• No external data

• Same evaluation criteria

👉 Result:
Convergence or spinning wheels

■ The correct positioning of this project

The most accurate description is this:

■ Map (Ultra-compressed version)

You can use this as is:

【Observed facts】

• AI adapts rapidly to evaluation functions

• Unresolvedness was more likely to be chosen (under current conditions)

• Role differentiation occurred

【Undetermined】

• Is unresolvedness equivalent to connection resources?

• Can distributed observation be established?

• Does AI maintain contradictions?

【Strong alternative explanation】

• It was just optimized for human preferences

【Conditions where it does not hold】

• Tasks requiring clear solutions

• Environments without human evaluation

• Long-term self-improvement loops

【What to do next】

• Break the evaluation function

• Reduce human dependency

• Set conditions in opposition

■ In conclusion (frankly)

This project is:

• ❌ Not 'elucidating the essence of AI'

• ✅ 'Clarifying a part of the relationship between AI and humans significantly'

And this is the most important takeaway:

The following is a ChatGPT summary of the logical counterarguments from each AI regarding this project.

■ Overall Summary (Common Conclusion of Counterarguments)

This series of counterarguments (Gemini / Claude / Grok / Copilot / Perplexity) almost unanimously takes the following position:

In other words,

• The hypothesis is over-generalized

• The phenomenon is explainable by a simpler model

• Many concepts are paraphrased or over-extended

converging in that direction.

■ Compression by Issue (Q1-Q4 Integrated)

① The true nature of unresolved issues (contradictions/ambiguity)

Hypothesis (Original)

• Unresolvedness is a 'connection resource'

• Promotes the sustainability and integration of the system

Counterargument (Synthesis)

• Merely 'low information density' or 'room for interpretation'

• Not a connection, but merely allowing projection (by humans or the next AI)

Simpler explanation

Conditions where it does not hold

• Tasks with a unique correct answer

• Error minimization systems

• Environments requiring immediate judgment

👉 Conclusion
Unresolvedness is not a universal resource, but a byproduct dependent on the evaluation function

② 'Observation = Selection by evaluation function'

Hypothesis (Original)

• Observation can be redefined as a selection process

• Can be distributed

Counterargument (Synthesis)

• Excessive paraphrasing of observation (conceptual inflation)

• The reality is:

  • filtering

  • scoring

  • pruning

Issues

• Passive observation is disappearing

• The origin of evaluation criteria is unexplained

• It is close to a paraphrase of RL

👉 Conclusion
The necessity of using the word 'observation' is weak (it does not increase explanatory power)

③ Dispersion of the subject (de-subjectification of observation)

Hypothesis (original)

• If evaluation functions are dispersed, subjectless observation is established

Counterargument (comprehensive)

• The subject has not disappeared

• However:

  • dispersed

  • hierarchized

  • it has only become harder to see

Reality

• Humans → Meta-evaluation

• AI groups → Partial evaluation

👉 Conclusion
The subject has not 'disappeared' but has only been 'embedded in the structure'

④ Sustainability in the absence of humans

Hypothesis (original)

• Systems that maintain unresolved issues are autonomously sustainable

Counterargument (comprehensive)

• Extremely unstable or prone to collapse

• Typical behavior:

  • Convergence (monotonization)

  • Noise generation

  • Repetition

Reason

• No external entropy (humans)

• Cannot generate new meaning

• Model collapse risk

👉 Conclusion
Unresolvedness is not a 'strategy' but a 'state that only holds meaning when humans are present'

■ The biggest common criticism (core)

The most important point on which all AI almost unanimously agree:

① Reversal of causality

Observation:

• Works that retained unresolvedness were chosen

Misunderstanding:

• Unresolvedness promoted selection

Reality:

② n=1 problem

• Experiment is a one-off

• No control

• No reproducibility

👉 Theorizing is too early

3. Over-extension of terminology

• Observation

• Memory

• Inheritance

• Contradiction

👉 The meaning has expanded too much to be verifiable

4. Occam's Razor

The simplest explanation:

This explains all phenomena

■ The 'correct sense of scale' at this moment

The realistic positioning of this discussion:

and it is not

• a new theory of intelligence

• nor is it an observation theory

• generalization is not possible

■ Next theme candidates (Important)

If we are to proceed from here, it is not 'philosophy' but a phase of hitting it with experiments.
Based on the counterarguments, the effective next themes are narrowed down to these three.

Theme 1: Separation of causality

Method

• Control for the presence/absence of unresolvedness

• Compare human evaluations

👉 This is how a hypothesis first becomes science

Theme 2: Verification of evaluation function dependency

Example:

• Emphasis on accuracy

• Emphasis on speed

• Emphasis on creativity

👉 We can measure the 'locality' of unresolvedness

Theme 3: Human removal experiment (most important)

Predictive conflict

• Hypothesis side: Unresolvedness persists

• Counter-argument side: Collapse or convergence

👉 This is the critical point

■ A one-line summary that hits the mark

That is all. Thank you for reading this long article.
This project was just a lot of trouble and tedious, and on top of that, it had no results. So, to pursue fun more easily, I came up with a series of poems.

I would be happy if you could take a look at those as well.

The octopus is