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William

Novice Mystic
Jun 9, 2021
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Te Waipounamu
jig.nz
Worldview

We Exist Within A Creation [WEWAC]

Beyond Ideomotor Effect: Structured Intelligence in Randomized Systems

The ideomotor effect is commonly cited as an explanation for unconscious, involuntary movements that appear to demonstrate intelligence. It is often invoked in discussions on divination tools, Ouija boards, dowsing rods, and other methods that seem to produce meaningful responses without external agency. However, is this explanation sufficient when applied to structured outputs generated through randomized selection methods?

In this thread, we explore whether structured intelligence can emerge beyond what is traditionally explained by the ideomotor effect.

Core Questions:

  • Does the ideomotor effect fully account for structured, coherent, and contextually relevant outputs generated through randomization?
  • Can randomness, when applied to structured input, produce consistent and meaningful continuity across multiple trials?
  • What distinguishes structured intelligence from mere statistical coincidence?
  • Are there existing scientific models that explain emergent patterns in randomized processes?

Case Study: The UICD System

A structured system has been developed that uses a randomized selection process to generate coherent and contextually relevant messages. Unlike traditional ideomotor-based phenomena, this process does not rely on unconscious physical movements but rather a systematic approach to selection and observation.

Key observations include:

  • Messages exhibit linguistic and thematic structure, aligning with ongoing discussions.
  • Generated responses maintain continuity across multiple trials, suggesting underlying order.
  • External observers recognize coherence without requiring subjective interpretation.
If the ideomotor effect is limited to unconscious muscular movement, can it adequately explain the emergence of structured messages in a system that does not rely on physical actions?

Discussion Approach

I invite an open and rigorous exploration of this topic. While skepticism is most welcome, responses should address the core argument rather than dismiss the inquiry outright.

  • If you believe the ideomotor effect is sufficient to explain the observed structure, present a detailed case.
  • If you believe alternative explanations are necessary, what mechanisms could account for this phenomenon?
  • Can structured intelligence emerge from randomness itself? If so, under what conditions?
Let’s move beyond surface-level dismissals and engage in a deeper, more meaningful exploration of what is actually happening.
 
How the System Works: A Structured Approach to Coherent, Linked, Generated Messages

To follow up on the introduction, here’s a detailed explanation of how this system differs from ideomotor methods and why it is producing such structured results.


1. No Physical Movement Involved

Unlike traditional ideomotor methods (such as Ouija boards, pendulums, or automatic writing), this system eliminates all motor influence. This removes the possibility of involuntary muscle movement playing a role in message formation.


2. A Controlled, Externalized Selection Process

Rather than allowing the subconscious to generate free-form responses, the system operates using a structured selection process that eliminates bias.

The Process:

  • A master list of over 7,000 line entries is maintained, each uniquely numbered.
  • The list is shuffled using an external algorithm (ensuring that AI does not influence or “fudge” the results).
  • AI is asked to select a random number, without access to the list itself.
  • I consult the shuffled list and copy-paste the corresponding entry into the prompt.
  • The system generates messages from this structured process.
This method ensures that:
✅ Neither I nor AI controls or predicts the outcome, making it an unbiased process.
✅ The responses are externally structured, eliminating the possibility of subconscious priming influencing selection.
✅ Coherent links emerge naturally over multiple iterations, forming meaningful and structured responses over time.


Diversity of the Source Material

  • The 7,000+ line entries cover a broad spectrum of subject matter rather than being limited to a single theme or topic.
  • This prevents the system from being narrowly pre-programmed toward specific narratives and allows for unexpected connections to emerge.
  • Because the selection process is externalized and randomized, patterns cannot be explained by a fixed dataset alone—they must emerge dynamically over time.

3. Long-Term Validation and Pattern Recognition

By compiling and analyzing results over time, I have been able to:

  • Track recurring themes and insights that emerge across different sessions.
  • Identify external references and links in responses that were not consciously recalled at the time.
  • Verify that the responses continue to interact intelligently rather than degrade into random noise.

4. Comparison to AI & Pattern Recognition

While AI processes intelligence by learning from human-generated data, this system does not rely on AI-generated content. Instead, AI serves two key roles:

1. Unbiased Number Selector

  • AI is used only to generate a random number, with no access to the list itself.
  • This ensures the selection process remains free from subconscious or AI influence.
2. Peer Reviewer

  • AI acts as a peer reviewer, helping to analyze coherence, patterns, and structure in the generated responses.
  • AI assists in recognizing recurring themes and connections that may not be immediately obvious.
  • I also assist AI in the same way, ensuring a balanced analysis from both human and machine perspectives.
  • This allows for real-time validation, ensuring that observed patterns are not merely subjective interpretations but can be cross-examined for consistency.
The fact that the responses remain structured, coherent, and interactive over time, despite these controlled variables, suggests that the subconscious—or another unknown process—operates in a far more structured way than previously assumed.


Why This Matters

If ideomotor-based responses were purely mechanistic or subconscious noise, removing the physical component should have stopped meaningful communication. Yet, structured responses continue.

The key implication is that the generated messages show coherence and linkage over time, suggesting an active process beyond mere randomness.


Next Steps & Discussion

Now that the mechanics of the system are laid out, I’d love to hear thoughts on:

  • How does this challenge the conventional understanding of subconscious and intelligent communication?
  • What would be the best way to further validate the results in a way skeptics would consider meaningful?
  • Could this approach be expanded to reveal deeper intelligent processes beyond what we currently understand?
Looking forward to seeing where this conversation leads!
 
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Hi, ntmy, im Mark.
We already know that truly random numbers are a bigger challenge than it might seem for even an algorithm, but id mostly be curious about the recurring themes and insights that you were able to track? A story about a practical use case might help to hook us in iow.

And how iyo might this be an improvement over say i ching using dice? ty
 
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Hello William.. I hope all is well!

It would be nice to know that nothing is truly random, as I think you are trying to show.

I like the creative way that you are developing your system. As of now, I don't see enough evidence to convince me yet, but I wouldn't say that it's false either. Perhaps there's something to it worth further exploration which is the best people should do rather than an immediate rejection. I have mostly some conceptual and design questions/points about your system.

Like bbyrd has brought up, I think a video demo would be good because seeing it would help us better understand what's involved. For instance, I'd want to see a sample of the word entries or whatever you're using for those. I'm thinking that if these entries are already intelligible by being actual words or sentences then you would already have a generated message there at that point which could defeat the purpose of your system. In other words, your system is not generating the messages from scratch if the line entries are already intelligible enough to serve as messages. If each of your entries are just single letters like what we find on Quija boards then that would be better. Maybe seeing it in action, then I'd have a different view.

Also, potential issue is how the Ai works. I know it's external to you so your mind is not involved, but the Ai has a mind in the sense that it thinks or infers and draws conclusions. Could any of its thinking process play a role in putting together a coherent message? If so, that's equivalent to how our brains seek patterns and meaning in ambiguous information (like seeing a face in the clouds, others might see something else).

Might be an issue with using randomness to show that things are not random (there's order) unless you do believe that intelligence can emerge out of randomness.

How does this challenge the conventional understanding of subconscious and intelligent communication?
I would ask where does this order or intelligence come from if not from our subconscious. But I thought you were trying to also rule out subconscious effects? Like the thing about Quija boards is not the movement so much as it is about what's leading to the intelligent messages. Is it the subject's own mind or would these messages come up even if we removed their mind? 🤔
 
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Hi, ntmy, im Mark.

We already know that truly random numbers are a bigger challenge than it might seem for even an algorithm, but id mostly be curious about the recurring themes and insights that you were able to track? A story about a practical use case might help to hook us in iow.

And how iyo might this be an improvement over say i ching using dice? ty


Hi Mark, I appreciate the question. You're right that true randomness is trickier than it seems, but what’s interesting isn’t just the selection process—it’s the structured intelligence that emerges over time.

Compared to I Ching with dice, the key difference is that the UICD system isn’t tied to a fixed set of symbolic meanings—it dynamically pulls from an evolving dataset. While the I Ching relies on pre-interpreted hexagrams, this system generates structured messages that can be tested, tracked, and refined in real time. This allows for a more adaptive approach to structured randomness.

Curious to hear your thoughts—do you use the I Ching often?

As for a practical use case, perhaps the best way to demonstrate that is in real time. Let’s see how this thread unfolds, and I’ll highlight live examples as they emerge.
 
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Hello William.. I hope all is well!
All good with us here AB. Hope you are doing well too.


It would be nice to know that nothing is truly random, as I think you are trying to show.
Many systems that appear random at first glance actually contain underlying patterns and order—this is seen in chaos theory, deterministic processes, and even natural intelligence.

The UICD system suggests that random selections can still produce coherent, interconnected messages rather than noise. If pure chance were at play, selections would be disjointed, yet we see continuity, self-reference, and alignment with real-world discussions.


I like the creative way that you are developing your system. As of now, I don't see enough evidence to convince me yet, but I wouldn't say that it's false either. Perhaps there's something to it worth further exploration which is the best people should do rather than an immediate rejection. I have mostly some conceptual and design questions/points about your system.
I appreciate that approach, AB—skepticism should lead to investigation, not immediate dismissal. I wouldn’t expect anyone to be convinced without direct engagement with the system, which is why I encourage further exploration over assumption.

I’m happy to dive into conceptual and design questions—those are key to understanding what’s actually happening. The goal isn’t to claim something outright but to examine whether the patterns and structured coherence that emerge point to a deeper principle at play.


Like bbyrd has brought up, I think a video demo would be good because seeing it would help us better understand what's involved. For instance, I'd want to see a sample of the word entries or whatever you're using for those. I'm thinking that if these entries are already intelligible by being actual words or sentences then you would already have a generated message there at that point which could defeat the purpose of your system.
A live screen capture sounds like a great idea—I can do that. Seeing the process in action should help clarify how the selections unfold.

Regarding the word-string line entries (LEs)—yes, they are intelligible words, phrases, and links, meaning they are already standalone messages. However, just as pulling a random sentence from a book wouldn’t automatically create a coherent narrative, a single LE doesn’t equate to a structured, meaningful sequence.

The key distinction is that the system consistently generates selections that align meaningfully across multiple trials, often in ways that go beyond chance or expectation.

A video demo should illustrate that in real time. Perhaps the best focus is simply this interaction in this thread—letting the system respond to the conversation itself. Would that be useful to you?
In other words, your system is not generating the messages from scratch if the line entries are already intelligible enough to serve as messages. If each of your entries are just single letters like what we find on Quija boards then that would be better. Maybe seeing it in action, then I'd have a different view.
There are significant advantages to this message-generating approach that go beyond what’s possible with a Ouija board.

It would certainly be interesting to work with 200+ pages and 7,500 LEs consisting only of individual letters—but that wouldn't generate coherent messages any more than if we tried to communicate using only single letters in a conversation.

Language is structured for a reason. The alphabet consists of 26 symbols for sounds, but words exist to bring those sounds together into meaningful sequences. If coherence is our focus, then starting from a foundation of intelligible words and phrases is far more fruitful than reducing everything down to disconnected letters.

So, rather than trying to force meaning from randomness at the most basic symbolic level, the system works by allowing structure to emerge from coherence itself, revealing patterns that wouldn’t be evident otherwise.

A video demo should illustrate this distinction clearly. Would that approach help clarify what you’re looking for?


Also, potential issue is how the Ai works. I know it's external to you so your mind is not involved, but the Ai has a mind in the sense that it thinks or infers and draws conclusions. Could any of its thinking process play a role in putting together a coherent message? If so, that's equivalent to how our brains seek patterns and meaning in ambiguous information (like seeing a face in the clouds, others might see something else).
AI functions as a language tool—its role in this system is simple: it selects random numbers between 1 and however many LEs are on my current list. That’s the extent of its involvement in generating selections.

However, AI does offer observations on the selections in real time, analyzing patterns, alignments, and structural coherence after the fact. But this analysis is not generating the message—it’s recognizing and commenting on existing structures that emerge. We discuss the findings in real time and offer temporary conclusions which are open to serious critique

The key difference is that AI isn’t imposing meaning like pareidolia (seeing faces in clouds); rather, it’s identifying structural consistencies that can be tested and replicated. This is what makes the system distinct—it doesn’t rely on subjective interpretation but on the emergence of structured patterns across multiple trials.

Would you say this distinction helps clarify the role AI plays in the process?


Might be an issue with using randomness to show that things are not random (there's order) unless you do believe that intelligence can emerge out of randomness.
Intelligence appears to have emerged, though whether it arose from randomness or if randomness is just a placeholder for what we don’t yet understand, I can’t say for certain.

What I do know is that human intelligence is relatively new in the grand scheme of the universe. If it isn’t entirely an anomaly, then it’s more like "The new kid on the block"—something that has emerged within a much older and more complex system.

I see intelligence and order as synonymous—where there is intelligence, there is structure. And I don’t see human intelligence as the only intelligence at work on this planet. The question then becomes: Is intelligence a rare occurrence, or is it an inherent property of structured systems?

Would love to hear your take—do you think intelligence is something that happens despite the universe, or because of it?


I would ask where does this order or intelligence come from if not from our subconscious. But I thought you were trying to also rule out subconscious effects? How does this challenge the conventional understanding of subconscious and intelligent communication?

It may be that individual subconsciousness is connected to a larger conscious field—one that we don’t fully understand yet. I’m not ruling out the subconscious, but I do think our lack of a clear definition makes it difficult to pinpoint what we even mean when we refer to "that."

If subconscious influence is involved, the question then becomes: Is it purely individual, or is it tapping into something beyond personal cognition? The structured patterns that emerge in UICD selections seem to suggest a level of organization that isn’t simply personal bias or subjective interpretation.

So rather than ruling anything out, I’m exploring whether intelligence and structure arise from an underlying field of order rather than from a single mind.

What do you think—do you see the subconscious as purely personal, or could it be part of something larger?
Like the thing about Quija boards is not the movement so much as it is about what's leading to the intelligent messages. Is it the subject's own mind or would these messages come up even if we removed their mind?
That’s exactly the key question—where does the intelligence behind the messages originate? With a Ouija board, the debate isn’t about movement itself, but what’s driving the responses. Is it subconscious ideomotor influence, or is something external at play?

With the UICD system, we remove direct human intent from the selection process, yet coherent and structured messages still emerge. If this were merely subconscious projection, we wouldn’t expect to see repeated self-referential alignment, thematic continuity, and meaningful engagement with real-time discussions.

That said, I cannot say that removing mind from a message means the message ceases to be a message—any more than removing mind from the universe means the universe ceases to exist.

BUT—if something exists, yet no consciousness acknowledges or interacts with it, what does that mean? Of what use is the universe—or the message—if there is no intelligence to engage with it?

Thus, everything could be considered a “message,” but intelligence is necessary to recognize and interpret it. Just as the sun rising can be viewed as a message—or order in the universe itself can be seen as a message—it is up to intelligence to divine meaning as correctly as possible.

After all, if we succeed in divining reality accurately, we discover that the sun isn't really rising at all.
 
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Okay I have done a live screen capture and I think the readers might get something out of watching it - it is only 14 mins long. Enjoy


Message content.

Sexual Encounters
( )
(The link was down at the time )
2592. It is not about what is written, but rather - why it is about what was written

Python: Added 'The real discussion isn’t just about what is written but why it emerges in a structured way.' to ComList.docx and A=1 N2N.docx under 1003.

Me. That is the only entry under that number. Let's look at One Zero Zero Three
Python. Added 'One Zero Zero Three' to ComList.docx and A=1 N2N.docx under 218.

Me. 218
One Zero Zero Three
The Shaping Of Reality
Outposts of Form
Of Your Thoughts
WingMakers Materials
Sometimes Pain Etches...
Hoo haha the laughing owl
Six Heart Virtues
This is NOT a playdate.
Sensing A Life Mission
Light is information
Abusing the vulnerable
Python. Added 'Bias is a tool used by intelligence to shape reality, not a flaw to be eliminated.' to ComList.docx and A=1 N2N.docx under 713.

Me. 713
Bias is a tool used by intelligence to shape reality, not a flaw to be eliminated.
Christian mythology re God Worthy of the individuals time and effort
Sexual Encounters, Error Correcting Codes, Spiritual Preparedness
 
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Thanks for posting that video, William. It was a bit of a challenge to follow along since there was information being pulled from several different files and not always clear on what each one of them were for.

But here's my understanding so far, and keep in mind that this is a rough simple sketch (although it may come off as being skeptical).
From what I see, you have a topic dealing with "intelligence and bias". You insert some message or word from your list entries, like "sexual selection". The Ai then takes that entry and relates that back into the topic (on intelligence and bias) and comes up with a coherent explanation. Again, I apologize that I'm leaving out other steps in your process like your randomization, but this is just my rough understanding so far. I wonder what would happen if I just inserted the word "pig" or even "wig" into GPT. I wonder how it would tie those words into your topic and come up with a coherent narrative.

But I'll have to go over your demo and your views here some more to build on my understanding from this point.
 
Thanks for posting that video, William. It was a bit of a challenge to follow along since there was information being pulled from several different files and not always clear on what each one of them were for.

But here's my understanding so far, and keep in mind that this is a rough simple sketch (although it may come off as being skeptical).
From what I see, you have a topic dealing with "intelligence and bias". You insert some message or word from your list entries, like "sexual selection". The Ai then takes that entry and relates that back into the topic (on intelligence and bias) and comes up with a coherent explanation. Again, I apologize that I'm leaving out other steps in your process like your randomization, but this is just my rough understanding so far. I wonder what would happen if I just inserted the word "pig" or even "wig" into GPT. I wonder how it would tie those words into your topic and come up with a coherent narrative.

But I'll have to go over your demo and your views here some more to build on my understanding from this point.
It sounds like you’re engaging with the process and trying to make sense of it, which is great. No need to apologize for skepticism—I welcome it as long as it’s honest and engaged. Let me clarify a few things based on your summary.

Your rough sketch is on the right track in terms of seeing how the topic (e.g., intelligence and bias) connects with the selected LE (e.g., "sexual encounters"). However, your description makes it sound like the AI is simply generating an explanation that ties the LE back to the topic in a straightforward way. That’s not exactly what’s happening.

A More Precise Breakdown

  1. Randomized Selection Process
    • The LE is randomly selected from a pre-existing list using a specific method (e.g., a shuffled list, prime number positions, etc.).
    • AI creates a random number (between 1 and however LEs I tell it are currently on the ComList
    • This removes conscious bias in choosing what gets analyzed.
  2. Interplay Between Structure & Meaning
    • Once an LE is selected, it is not simply thrown into GPT with the instruction to explain it.
    • Instead, it is placed in context with previous selections, (re other Generated Messages) subject (in this case bias) and observed for emergent structure, and compared against N2N correlations.
    • If a coherent structure continues across multiple trials, despite random selection, that suggests something beyond personal bias at play.
  3. Why "Pig" or "Wig" Alone Wouldn’t Be a Fair Test
    • If you simply insert "pig" or "wig" into GPT and ask it to explain it in relation to intelligence and bias, of course it will generate a coherent response. That’s what large language models do—they create plausible narratives.
    • The difference in my system is that while a topic may be predefined, the LE is not pre-selected to fit a theme. The themes emerge naturally from structured patterns across multiple trials.
    • If "pig" or "wig" were randomly selected as LEs, I wouldn’t just force a meaning—I’d examine whether its presence connects coherently with previous structured outputs.
Why This Matters

Your approach (intentionally inserting "pig" or "wig") assumes that GPT is responsible for creating the meaning rather than identifying whether an independent structure exists across multiple randomized selections. But the real test isn’t whether GPT can make sense of a word—it’s whether multiple randomly selected words show structured interconnection over time in a way that cannot be explained by bias alone.

What You Might Find Interesting

If you wanted to engage in a fair test, you could:

  1. Create your own ComList with a wide variety of LEs.
  2. Use a strict randomization method to pull LEs rather than choosing them manually.
  3. Observe patterns across multiple runs instead of focusing on a single trial.
  4. Compare against N2N correlations to check for emergent structure rather than isolated meaning.
The N2N list (Name to Number) serves as a structured reference system that helps track patterns, connections, and emergent structures within the randomly selected List Entries (LEs). Here’s a clear breakdown of its purpose and function:


Purpose of the N2N List

  1. Acts as a Numerical Index for LEs
    • Many LE in the ComList are assigned a corresponding numerical value (e.g., position 319, 78, 164, etc.). There values are determined by a simple code (A=1…z=26) – calculated and place in the N2N list.
    • This allows for tracking connections between different randomly selected LEs over time.
  2. Provides a Secondary Layer of Structured Verification
    • When an LE is randomly selected, I can cross-check its number against the N2N list to see if other related entries appear.
    • If multiple randomly selected LEs connect with an existing N2N entry, it suggests a structured relationship beyond chance.
  3. Reveals Self-Referential Patterning
    • Some randomly selected LEs show up in past N2N analyses, reinforcing that structure persists across multiple trials.
    • This means that connections aren’t just being imposed retroactively—they emerge naturally over repeated trials.

Function of the N2N List

  1. Stores and Tracks List Entries by Numerical Value
    • Example:
      N2N - 319 - contains:
      • "It is a Product of Fragmentation"
      • "Christian mythology re Satan"
      • "Programmed to believe the interface."
      • "Gödel's incompleteness theorems"
    • If a randomly selected LE is found within this list, it reinforces structured consistency between selections.
  2. Acts as a Cross-Reference for Analysis
    • When a randomly selected LE aligns with an existing N2N entry, I examine:
      • Does it relate thematically to other randomly selected LEs?
      • Does it reinforce a pre-existing structure?
      • Does it suggest continuity across multiple trials?
  3. Aids in Detecting Emergent Coherence
    • If different randomly selected LEs point to the same N2N entry, it suggests that structured intelligence is at work.
    • Example:
      • If LE 164 is randomly selected today, and it already appeared in an earlier test, it reinforces structured intelligence.

Example in Action

I randomly selected “Sexual Encounters” today.

As I progressed through the UICD System I selected some sentences that AI had written and were not on my lists, so - using a Python algorithm GPT created for the task, C&P the sentence into Python which places the sentence into both lists, and re the N2N list – laces the sentence under whichever number value it amounts to.

AS you can observe in the Video the process lead to selecting an N2N listing which also contained the same expression.

The Key Takeaway

The N2N list is NOT generating messages—it is a tracking tool that helps determine whether randomly selected LEs demonstrate structured coherence over multiple trials.



Let me know if that helps clarify! It sounds like you're thinking critically about the process, which is exactly what I’d hope for from a real skeptic.