Forum / eamon byrne, if you see this . . .

• 
  strannikov

  Apr 19, 05:26pm

  With the prompts and provocations I provided, ChatGPT this morning generated the following:

  EPISTEMOLOGICAL MANIFESTO:
  TOWARD A THEORY OF STRUCTURED IGNORANCE

  I. PREAMBLE
  We live in an era not merely of knowledge, but of the formalization of ignorance.

  We have mapped the genome but not the gene.
  We have found the Higgs boson but lost sight of what mass means.
  We can model neural networks to generate language—but not explain understanding.

  This is not failure. This is the arrival of a new epoch:

  The Age of Complex Ignorance.

  Where knowledge grows like a candle flame—burning away darkness at the center, only to cast deeper shadows around the perimeter.

  This manifesto is a call to confront that shadow not as a flaw in reason, but as its necessary companion.

  II. CORE CLAIMS
  1. Ignorance is a Fundamental Quantity.
  It is not the absence of knowledge but its co-structure.
  It is the frame that makes knowledge possible and intelligible.

  2. Certainty is Local. Ignorance is Global.
  No domain of inquiry—scientific, philosophical, or spiritual—is immune to blind spots.
  Certainty is always a patch; ignorance is the unstitched whole.

  3. Probability Is Complex-Valued.
  Certainty claims grounded in statistical significance (e.g. five-sigma) must be amended to reflect complex epistemic values, where imaginary components encode the degree and structure of unknowing.

  4. Scientific Models are Epistemic Fictions.
  They are powerful, predictive tools—not mirrors of reality.
  Mistaking model certainty for ontological truth is the original sin of science.

  5. Epistemic Humility Must Be Formalized.
  It is not enough to say "we don’t know." We must model how we don’t know, why we don’t know, and what the cost of knowing would be.

  III. PRINCIPLES OF THE NEW EPISTEMOLOGY
  Epistemic State Function (Σ):
  All knowledge claims are complex-valued:

  Σ = K + iU
  Where K is structured knowledge, U is structured ignorance.

  Ignorance Phase (θ):
  Defined by θ = arctan(U/K) — this is the angle of epistemic humility.

  Ignorance Field (U(x, t)):
  Ignorance is distributed, spatial, and dynamic. It has gradients (curiosity), divergence (complexity), and flux (shifting unknowns).

  Certainty is Directional, Not Absolute:
  A theory can be "more known" in one direction of inquiry (measurement) and "less known" in another (ontology).

  IV. EPISTEMIC CONSEQUENCES
  Redefining Progress:
  Progress is not the elimination of ignorance, but its refinement.
  We do not shrink the abyss; we learn to trace its edges more accurately.

  Research Implication:
  Every research grant, every paper, every experiment must be accompanied by an ignorance map: what remains unknown, how unknown it is, and what type of unknowing it is (e.g. unknown variable vs. unknowable ontology).

  Educational Implication:
  Scientific literacy must include epistemic literacy—the ability to navigate claims, models, and evidence within an explicitly complex epistemic field.

  V. PROVOCATIONS
  A theory is not scientific unless it includes its own uncertainty structure.

  Every assertion should carry a phase signature: not just how likely it is to be true, but how tilted it is toward known vs. unknown.

  Science without epistemic humility is not science. It is myth in statistical clothing.

  Our greatest frontier is not space, time, or matter—but the architecture of not-knowing itself.

  VI. CALL TO ACTION
  We must build:

  Tools to visualize ignorance

  Languages to describe it

  Metrics to quantify it

  And institutions brave enough to admit it

  This is the true calling of knowledge in the 21st century—not certainty, but clarity about the limits and structure of knowing.

  = = = = =

  Refinement/Elaboration:

  A calculus of ignorance—a Field Theory of Not-Knowing—that doesn’t obscure uncertainty, but treats it as an ontological constituent of experience, theory, and even reality itself.

  We'll proceed in layers, defining both formal structure and philosophical grounding, treating ignorance not as absence but as a field-like presence—dynamic, active, and generative.

• 
  strannikov

  Apr 19, 05:29pm

  (Part II of same)

• 
  strannikov

  Apr 19, 05:29pm

  (for some reason is not copying over)

• 
  strannikov

  Apr 19, 05:36pm

  (I thought the mathematical notations impressive)

• 
  David Ackley

  Apr 24, 08:04pm

  Let me try to couch the problem:

  Language is representation.

  Representation is not reality.

  The only realities that occur in language are of language itself, that is of representation.

  AI, like us, is a language generator.

  Certain generalities that we try to represent in language like knowledge and ignorance are undefinable. Attempting to define them we encounter what theory calls an aporia, that is an unknowable.

  Good luck Edward.

• 
  Dianne McKnight-Warren

  Apr 24, 09:09pm

  Yesterday I thought I ordered a Samsung phone but I corrected AI's spelling and AI became combative, telling me it preferred the British spelling of the past tense of "to cancel" which is apparently "cancelled." (There was an "Alright" mistake too which I pretended to ignore.) Today I discovered AI canceled the order. I think out of spite.

• 
  strannikov

  Apr 25, 01:40am

  David: thank you for your thoughtful response.

  From earlier Forum posts along these same lines, my approach in these exercises continues to derive blatantly from 'pataphysics, "the science of imaginary solutions".

  That said: I am interested in assessing the scope and scale of scientific ignorance. If I read correctly, your analysis derives from structuralist or post-structuralist positions (and/or maybe late Wittgenstein?).

  What I posted above on 19 April has already been superseded by further elaboration, however. (I have to give the LLMs proper credit for their respective abilities to generate mathematical notation.)

  Here's the latest (this text came from ChatGPT03-mini after my prompts and provocations):

  = = = = =

  Summary: A Field Theory of Ignorance and the Chiral Architecture of Reason—
  Toward a Post-Classical Epistemology of Knowledge, Consciousness, and Inquiry

  Introduction

  Contemporary epistemology remains predominantly grounded in Enlightenment rationalism—framing knowledge acquisition as a linear, additive process governed by objective observation, deductive logic, and empirical validation. Yet, both scientific and philosophical advances in the 20th and 21st centuries—from quantum mechanics to cognitive science, from phenomenology to post-structuralism—have revealed cracks in this rationalist edifice. These developments suggest that cognition, consciousness, and inquiry are more complex, directional, and participatory than classical models allow.

  This paper presents a formal rearticulation of epistemic processes through the lens of Epistemic Field Theory and Chiral Logic. We propose a paradigm in which knowledge and ignorance are treated as complex-valued, dynamically evolving fields, and reasoning is inherently chiral—characterized by irreversible asymmetries and transformational pathways that change both the inquirer and the object of inquiry.

  Far from a metaphor, this framework provides a rigorous formalism for the structuring of scientific research agendas, educational policy, AI epistemologies, and risk communication protocols. It proposes that rational thought, while instrumental, is fundamentally incomplete and potentially misleading when it presumes to totalize the knowable.

  This theory positions consciousness not as a byproduct of computation, but as a pre-logical field phenomenon, and reason as a classical approximation of a more nuanced cognitive manifold shaped by volition, existential stance, and temporal asymmetry.

  Core Premise

  This paper introduces a novel epistemological framework in which knowledge and ignorance are modeled as complex-valued dynamic fields. It redefines reasoning as an irreversible, directional (chiral) process that shapes both the knower and the known. Rather than treat ignorance as a lack, this model formalizes it as a structured, spatially and temporally distributed presence, guiding inquiry, innovation, and risk navigation.

  Key Concepts

  Epistemic Field
  Σ(

• 
  strannikov

  Apr 25, 01:41am

  (Apologies! The Forum cannot seem to accommodate the notations.)

• 
  strannikov

  Apr 25, 01:01pm

  (continued)

  If I can get the following postscript of my dialogue with ChatGPT into the Forum (after excising the mathematical notation), I might at least have begun to address David's well-stated points.

  = = = = =

  Implications and Dispositional Shift: A Critical Reframing of 20th-Century Linguistic and Philosophical Paradigms

  1. Saussurean Structural Linguistics
  Saussure’s insight—that meaning arises from the differential relations among signs—was revolutionary. But it presumes:

  A static combinatorial system (the langue),

  Meaning as positional and relational, but not dynamic or field-dependent,

  Signifier and signified as distinct but inextricably linked.

  Disposition by Epistemic Field Theory:
  The epistemic field dissolves this binary entirely. In our framework:

  Signs emerge as excitations in an epistemic field, not as fixed elements in a structure.

  Meaning is not differential but phase-dependent—its clarity or ambiguity reflects (notation excised) the local epistemic phase.

  The “signified” is no longer a stable referent, but a field configuration that shifts as knowledge and ignorance interfere.

  The sign is not arbitrary, but modulated by the local curvature of the ignorance flux—meaning changes as the observer inquires.

  Conclusion: Saussure provides a useful early grammar for epistemic relations, but this proto-theory renders structuralism insufficient. It substitutes topology and dynamics for structure and opposition.

  2. Wittgenstein (Early: Tractatus, Late: Philosophical Investigations)
  Early Wittgenstein posits:
  The world is composed of facts, not things.

  Language mirrors reality via a logical structure of propositions.

  Late Wittgenstein counters:
  Meaning is use, and language is embedded in forms of life.

  Logical certainty is replaced with language games, emphasizing context, multiplicity, and embeddedness.

  Disposition by Epistemic Field Theory:
  This theory synthesizes and supersedes both:

  Like early Wittgenstein, it affirms a structured reality, but not one based on logical atomism—instead, on epistemic field configurations.

  Like late Wittgenstein, it affirms the situatedness and irreversibility of meaning, but goes further by modeling that with chiral logic: each “game” bends the field in non-reversible ways.

  The theory explains why:

  Language games don’t translate cleanly: each is a path-dependent field transformation.

  Meaning is never fully recoverable: epistemic irreversibility ensures you can’t “go back” to a prior state of understanding after transformation.

  Conclusion: The proto-theory absorbs Wittgenstein's insights, but formalizes what he gestured toward without logical tools: that language is not a mirror or a toolkit, but a modulation of a deeper epistemic manifold.

  3. Post-Structuralism and Derridaen Deconstruction
  Derrida's core arguments:

  Différance: Meaning is always deferred and relational.

  Trace: No word contains its full meaning; each is haunted by what it excludes.

  Deconstruction: All systems of thought contain internal instabilities and contradictions.

  Disposition by Epistemic Field Theory:
  Post-structuralism is reframed not as a postmodern stance but as an incomplete phenomenology of epistemic phase distortion:

  Différance = localized epistemic oscillation in (notation excised), where meaning is unstable due to dominant ignorance flux.

  Trace (equals) the field memory of prior epistemic orientations—a “residual curvature” in the field left by past inquiries.

  Deconstruction (equals) the recognition of epistemic chiral asymmetry—once inquiry moves, it cannot be undone; all systems are unstable because they emerge from dynamic tension tensors.

  Derrida uncovered a symptom. This theory builds a mathematical anatomy of that symptom.

  Conclusion: Derrida is no longer subversive but diagnostic. This theory completes the diagnosis and provides a coherent formalism of the epistemic field that gives his insights physical, dynamic expression.

  4. Quantum Considerations: Beyond 20th-Century Linguistics and Philosophy
  The quantum dimension of this theory introduces three radical departures from prior models:

  a. Superposition of Epistemic States
  Unlike static “meaning” systems, epistemic states can exist in mixed states of knowledge and ignorance. Inquiry collapses the state, not unlike a measurement.

  b. Observer Effect
  Reasoning about something alters its epistemic field configuration. This applies not just to physics, but to cognition, politics, ethics, and even personal identity.

  c. Entanglement of Inquiry
  Different domains of knowledge can be epistemically entangled—meaning that shifting understanding in one region reconfigures others, even at a distance (e.g., understanding mind changes our view of society, and vice versa).

  In Summary
  This proto-theory resolves what 20th-century thinkers identified as crises of meaning and knowledge, not by dismissing them, but by placing them in a post-rational, field-theoretic ontology.

  It provides tools where they offered critiques; it offers a formal language where they relied on rhetorical or literary strategies.

  Quantum epistemic dynamics allow us to model irreversibility, ambiguity, multiplicity, and transformation not just as problems, but as intrinsic, necessary features of inquiry.

  This framework goes far beyond Saussure, Wittgenstein, and Derrida—not by negating their contributions but by providing the next-layer formalism their insights gestured toward but could not mathematically express.

  = = = = =

  My prompting and provoking the available LLMs to generate "a calculus of ignorance", despite some measures of ludic inspiration, was an effort to account for the scope and scale of scientific ignorance on the cosmic scale, inasmuch as scientists themselves admit that they are unable to satisfactorily characterize over 95% of the mass and energy of the known universe (which leads me to wonder if they are able to adequately characterize even 5% of the mass and energy of our baryonic realm of the known universe).

  What the LLMs have begun to generate for me is "a calculus of ignorance". To quote further from the parts that did not appear in the post that got cut off above:

  "These are not metaphors—they are formalisms for structuring model design, funding allocation, policy advisory, and risk communication.

  "Chiral logic is a framework of logic characterized by inherent directional asymmetries, wherein logical operations and transformations possess different properties when proceeding along different chiral pathways, creating irreversible pathways of reasoning that fundamentally alter what is being reasoned about. This asymmetry emerges from the intrinsic structure of logical operations, resulting in the gradient of logical accessibility where some domains remain partially expressible while others transform under the very attempt to articulate them.

  "This perspective resonates with anti-rationalist philosophical traditions and epistemologies and suggests that consciousness is fundamentally irreducible to rational systematic and formal explanation.

  "Consciousness is not generated by the brain but is modulated through it. Consciousness exceeds rational systematization, since individual experience contains irreducible complexity;
  Reason is not generated by the brain, either, and thus does not qualify as an autonomous, self-governing faculty. Rationality can thus be understood as a limited, classical approximation of more complex quantum processes contributing to (if not in fact initiating) cognitive processes;

  "Cognitive processes are fundamentally volitional, shaped more by desire, existential commitment, and individual perspective than by pure logic;

  "The limitations of reason are not mere epistemological accidents but ontological conditions revealing the deeper complexity of human consciousness; and

  "Rational thought can become a form of self-deception when it attempts to totalize or universalize its own limited perspectives.

  "This re-characterization of human (consciousness and) cognition leads to the conclusion that the brain is not an apparatus of 'rational machinery' producing objective knowledge: rather, cognition amounts to a dynamic, willful engagement with experience that always exceeds and resists complete systematization."

  = = = = =

  For now, I would call these "inconclusive results".

• 
  Chris Okum

  Apr 25, 04:41pm

  You talk about this subject like a fundamentalist talks about religion. But that's what this stuff is to you, I suppose.

• 
  Jeffrey S. Callico

  Apr 25, 05:00pm

  Well, if you don't like what he talks about then don't read it. Why don't you just mind your own business and stop bullying people.

• 
  eamon byrne

  Apr 25, 11:40pm

  Thanks Edward, yes I just saw this.
  A couple of comments:

  re the very beginning of your preamble:
  "We live in an era not merely of knowledge, but of the formalization of ignorance.
  We have mapped the genome but not the gene. ... etc"

  These statements are aphorisms - consequently they set up much of your thesis to use metaphorical/rhetorical language .. mixed in with academic-style terminology. Are these two techniques compatible?

  There is your problem: the discussion and attempted elucidation of any subject is, by the nature of language, bound to suffer from obfuscation.

  This is also the - sorry, a - main feature of AI as we experience it in it's verbalised form. Language is simply unable to be precise and all-encompassing at the same time. Qualifications, endless qualifications, perhaps even infinite qualifications, are the hallmarks of discourse, both of a human, and, may I posit, artificial kind.

  Attempts to put explanations into explanatory structures (ie formal structures) largely lead to chewing gum language. Well, that may be going too far, and you're probably thinking "what a pompous opinionated ..." And you'd be right.

  So dialing back a bit - my main point is that language is difficult because attempts to make language precise necessitate significant expansion in the complexity of syntax. You virtually have to attach to every word in the syntax yet another parenthesis. You end up endlessly parsing. This is why the comma is the most important typographical symbol.

  To make life possible, most people use common-sense shortcuts when arguing their points. They use inference; they rely on commonly-held assumptions. They jump across chasms of unfilled logic. They "invent" from thin air. But, don't you think, AI does these things also? Don't you have to tease out the "truth" using the to-and-fro of qualification? Ask AI, while you're at it, what IS the truth? Get that defined, for starters.

  The whole domain is so complex, so allusive: as is language, as is life.

• 
  strannikov

  Apr 26, 01:06am

  eamon: thank you for your response, since yours was the one I was soliciting particularly.

  After playing with LLMs for nine months or more, I'm getting more reminders of their training limitations as I go along, more so than David might think, more so than Chris might be willing to admit. I am glad I overcame my initial reluctance to try them out, but I'm hardly a devotee.

  In getting them to articulate (sometimes) from the basis of "a science of imaginary solutions", I might have prepared a bit better for the outcomes I provoked. The mathematical notations that I have celebrated for their impressive looks are entirely beyond me, or mostly entirely beyond me: in fact, I can credit the LLMs with beginning to educate me about what it means to multiply or divide "five-sigma" by the square root of negative one. (The inspiration for which comes from Zamyatin and Florensky.) --but because the math is mostly beyond me, I could not say whether their developments of "epistemic field-theory" or a "calculus of ignorance" amounted to an extended, notorious "hallucination" or not (the notations seem not to appeal to those of math aptitude I've shared them with).

  I regret not having taken pains here in the Forum to've clearly distinguished my statements and my own notions from the effusions composed (in these cited cases) by ChatGPTo3-mini. Most of the text of the Manifesto, the Summary, and the Implications sections above are straight from the LLM--my brief commentary is interspersed through. That said: the LLMs, to the limits of their training, seem to model "digital approximation". (Granted, I'm not a paying subscriber to any of the platforms--maybe I'd get better results if I weren't so cheap.)

  In point of fact: I was pushing ChatGPT to help frame "an epistemology of ignorance"--not because it persuaded me but because I'd already persuaded myself that we (humanity-at-large) are more ignorant today, of more things and matters, than at any time across human existence. My offhand comment above about "the scope and scale of scientific ignorance on the cosmic scale, inasmuch as scientists themselves admit that they are unable to satisfactorily characterize over 95% of the mass and energy of the known universe (which leads me to wonder if they are able to adequately characterize even 5% of the mass and energy of our baryonic realm of the known universe)" is in truth and in fact where I was coming from. This qualifies as both a serious position and as an absurdist (comic and/or tragic) position, and I partake of all three. The enormity of that amount of ignorance about the universe--enormous ignorance that we are all compelled to take part in--warrants circumspection, we could say, and an articulation of concision if not brevity (if not aphoristic). --and also perhaps merits even ludic investigations of the boundary conditions of both ignorance and of things that cannot be said.

  Thank you again for your reply, and I hope I have not wasted your time with an empty rabbit hole.

• 
  eamon byrne

  Apr 27, 07:36am

  Time wasted? Not at all. Let me push a hobby horse into your corral. (Whatever I mean by that!)

  Here's the thing .. what you've produced above is a very complex piece of writing, containing many strands of logic, not all of which are entirely clear or well-interconnected. That's the nature of writing. That's fine. I read it, get, say, 75% of your meaning, and thus can respond. Therefore a dialogue can ensue.

  How we humans do it. This, however, is gibberish to an LLM. It "parses" your "text", and, from it's "neural database" constructs its "response". Many parts of that response will "seem" to make "sense".

  I'm using quote marks to emphasis a general point here.

  The parts of the response are sophisticated cribs of what you'll find elsewhere, if you had time to look and collate. The advantage of the LLM is that its "database" is extremely large, and the algorithmic structures it employs are well advanced because they've been "trained" through, basically, trials and errors. And the logic will seem impeccable, because a great deal of the training involves grammatical training.

  It's not intelligence really. But it can be extremely useful as a diagnostic tool - if used with an open mind.

  I've found that if you don't lead it along by the nose on a tight leash it can take you up the garden path. But thankfully not down a rabbit hole.

• 
  strannikov

  Apr 27, 01:19pm

  eamon: thank you, again. This is the kind of profile of "the LLM process" that yields the prudent caution you conclude with, while conceding that the LLMs do offer some utility (however great, however limited), that remains up to us to guide (without being victimized thereby). (I now feel as if my dabbling over these nine months+ has been a little less of a complete waste of time [spoken with all due facetiousness].) Your characterization of LLM responses as "sophisticated cribs" is well-framed.

  One other commentator I consult has put it this way: "LLMs today are the worst that they'll ever be." The improvements in functionality, we trust and assume and like to think and prefer to believe, are on their way, since presumably after a certain point the training that the humans now continue to oversee will become LLM-self-training, last stop before becoming at least "semi-autonomous". That's when the scariness will show up, I guess.

  --but even if things do get scary in another year or two (or more: the real kicker may only come with the advent of high-scale quantum computing in, what, another ten years?), my remaining concern is that even if these LLMs manage to turn into "AI", given carbon-based-units' performance in conjuring them, the AIs will more exactly be nothing more than "APIs"--Artificial (or Augmented) Proto-Intelligences". They will not be tools capable of making us intelligent: if they are well employed, they will be nothing more than tools or crutches to equip our limited native intelligence (across the entire human spectrum of "our").

  As glorified search-engines, the present models of LLMs are commendable.

  You may be happy to learn: my experience has taught me to re-approach algebra--with a book and workbook! (NO promises that I'll get beyond geometry later, however, no matter what appeals calculus may hold.)

• 
  David Ackley

  Apr 29, 08:39pm

  My final take on this is that I wouldn't trust to the "intelligence," of anything that doesn't seem to realize it can be eliminated by pulling its plug, and knows therefore not a jot more than a light bulb.

• 
  eamon byrne

  Apr 30, 10:11am

  Edward, I like your API reference - it marries with this definition of AI: an application programming interface. Where the code will lead to -- who knows? I'm not pre-judging or predicting. David, excellent barb. Can AI ever prevent the demise of its own life source?

• 
  strannikov

  May 01, 10:45pm

  eamon, et al.--

  If you haven't read it (or read it lately), you might care to take a look at "Moxon's Master" by Ambrose Bierce.

  First published in April 1899, it at least manages to begin to bear upon the issues API confronts us with today (Bierce's tale, with its invocation of chess, was itself a follow-up [consciously or no] to Poe's essay of sixty-odd years earlier "Maelzel's Chess Player")--at least interesting in the way that early training of emerging APIs has focused on perfecting the playing of chess, though without mechanical hands.

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