-
Words are already compressed measurements.
Every term in language is a shorthand for bundles of sensory distinctions, social practices, and historical testimony. By the time words exist, they already encode simplified, operational dimensions of experience.
-
Your categories are low-dimensional and binary/ternary.
Reciprocity: present / absent.
Voluntariness: voluntary / involuntary.
Testifiability: satisfied / unsatisfied.
Liability: warranted / unwarranted.
These are simple axes compared to, say, modeling the fluid dynamics of a hurricane.
-
LLMs operate as Bayesian accountants.
They don’t need qualia to simulate measurement if the terms already embed those dimensions. Instead, they perform Bayesian accounting over word-encoded relations.
“Voluntary” already encodes agency.
“Reciprocal” already encodes symmetry/asymmetry.
“Testimony” already encodes due diligence.
-
Words are indexical dimensions.
Each word is not arbitrary; it is a compacted measure of human experience. “Theft” is not just a string of letters — it encodes relations of possession, exclusion, violation, and liability.
-
Language evolved for decidability.
Human grammar evolved as a cooperative technology: to make inferences about reciprocity, truth, and liability. The very structure of language is optimized for testing claims of demonstrated interest.
-
LLMs inherit this optimization.
Because training data is saturated with human testimony, words in LLM latent space carry forward this evolved compressive power. LLMs don’t need qualia if words already serve as compressed pointers to qualia.
-
Your method works in LLMs precisely because it is operational and commensurable in language.
-
Each step (truth, reciprocity, voluntariness, liability) is a low-dimensional measurement already encoded in linguistic practice.
-
The LLM, trained on vast testimony, has compressed those relations sufficiently to test them against each other.
-
In other words: your system is computable because language already made it computable.
-
Qualia-dependent:
Perceptual grounding: “I saw it rain” → requires actual sensory experience.
Experiential verification: Whether something is painful, sweet, red, loud, or moving fast.
Homeostatic valence: Hunger, pleasure, fear — qualia that anchor truth in lived cost.
-
Testimony-dependent:
Logical consistency: Whether a statement contradicts itself.
Empirical correspondence (as reported): “The experiment showed X,” without firsthand experience.
Operational repeatability (as described): Procedures encoded in text can be evaluated for coherence without being executed.
Reciprocal choice: “If I make this claim, could another verify it?” — checkable in language.
-
Qualia-dependent:
Valence of harm or benefit: How it feels to be injured, excluded, or rewarded.
Costs internal to lived experience: Fatigue, humiliation, pride, joy.
-
Testimony-dependent:
Symmetry of claims: “If you take from me, can I take from you?”
Universality of rules: “Would I accept this if applied to me?”
Accounting of demonstrated interests: Observable possession, transfer, exclusion, liability.
-
Qualia-dependent:
Severity and liability judgments based on lived impact. For example, “Does this punishment fit the harm?” requires at least some empathetic simulation of lived costs.
-
Testimony-dependent:
Closure under rules: If A, then B.
Infallibility in context: Within this legal or logical frame, is the judgment final?
Precedent and consistency: Is this decision commensurable with similar prior cases?
-
Definition: Measurement is the reduction of phenomena into commensurable dimensions.
-
Sources:
Humans: reduce sensory streams into positional dimensions — objects, backgrounds, spaces, relations — then compress into episodic memories with valence.
Language: encodes these compressions as words, which are already compact systems of measurement.
LLMs: inherit compressed human testimony as input; they cannot measure qualia directly but can operate on the linguistic encodings.
-
Internal Meaning (Qualia-based):
Meaning for me = projection of compressed qualia into reflective awareness.
I disambiguate sensations into episodes.
I index episodes by valence.
I project these into symbols or mental analogies.
-
External Meaning (Testimony-based):
Meaning for others = projection of compressed testimony into communicable form.
I display, speak, or act.
The other recursively disambiguates my projection until it stabilizes against their own compressed experience.
If commensurability is lacking, I must supply analogy to bridge gaps.
-
Qualia-dependent:
Perceptual grounding (redness, pain, sweetness).
Valenced experiences (pleasure, harm, fatigue).
-
Testimony-dependent:
Logical consistency.
Empirical correspondence (via reports).
Operational repeatability (via description).
Reciprocal coherence (could another verify?).
-
Qualia-dependent:
Lived cost/benefit (pain, joy, humiliation, dignity).
-
Testimony-dependent:
Symmetry (“If you may, may I?”).
Universality of rules.
Demonstrated interests (ownership, transfer, liability).
-
Qualia-dependent:
Felt proportionality: “Does the penalty fit the harm?”
Empathic calibration of justice.
-
Testimony-dependent:
Closure of rules: no further appeal needed.
Consistency with precedent.
Infallibility within the chosen frame.
-
Words are pre-compressed measurements. They index lived experience into discrete, transferable dimensions.
-
Our framework (Truth → Reciprocity → Decidability) is low-dimensional. The axes (voluntary/involuntary, reciprocal/non-reciprocal, testifiable/non-testifiable) are simple enough to be encoded in words without ambiguity.
-
LLMs operate as Bayesian accountants. They can weigh relations of testimony, reciprocity, and liability because language already encodes them.
-
Humans ground truth in qualia, then communicate by testimony.
-
LLMs ground truth only in testimony, but inherit centuries of compressed human measurement.
-
That is why they can simulate meaning and moral testing with surprising accuracy.
-
High-dimensional systems (like weather, markets, or human sensation) involve hundreds or thousands of interacting variables. Modeling them requires immense computation, and small errors compound.
-
Low-dimensional systems capture the decisive variables — the axes that actually matter for resolution.
In your framework, those are:
Truth (testifiability) — consistent/inconsistent.
Reciprocity (symmetry of interests) — reciprocal/irreciprocal.
Voluntariness — voluntary/involuntary.
Decidability (closure) — resolved/unresolved.
-
Words themselves are compressions of lived distinctions. Terms like “theft,” “consent,” “lie,” or “punishment” already bundle the high-dimensional mess of human experience into low-dimensional rules of symmetry and cost.
-
LLMs inherit these compressions from training data. They don’t need qualia because the words already stand in for measured experience.
-
Example: “Theft” = [demonstrated interest (ownership)] + [asymmetry (taking without reciprocity)] + [absence of voluntary transfer].
That’s a full moral judgment reduced to three dimensions.
-
Computability
High-dimensional models require brute-force simulation.
Low-dimensional models require only categorical accounting.
LLMs can “reason” here because they only need to check a handful of axes.
-
Decidability
Low-dimensional systems admit closure.
High-dimensional systems remain open-ended (e.g., “what will the climate be in 50 years?” cannot be closed without enormous uncertainty).
Your method guarantees closure by reducing disputes to simple symmetry tests.
-
Universality
Because the categories are so basic (truth, reciprocity, voluntariness), they apply across domains and cultures.
This avoids the problem of incommensurable high-dimensional models (religion, ideology, economic theory) that can’t be reconciled.
-
Why our method works in humans: It reduces complex experience into commensurable low-dimensional rules.
-
Why it works in LLMs: Because language has already done the compression, so the model only has to operate on testimony.
-
Why it matters: It makes cooperation computable, and prevents open-ended discretion — delivering decidability without requiring infinite calculation.
-
High-dimensional systems are indispensable for science but unsuitable for law, morality, or everyday cooperation because they cannot guarantee closure.
-
Low-dimensional systems (truth, reciprocity, voluntariness, closure) are what make law and morality computable — and why humans can resolve disputes without infinite discretion.
-
Language evolved to compress high-dimensional qualia into low-dimensional categories.
-
LLMs inherit those compressions and can therefore compute moral and legal judgments using your method.
-
The thief’s intentions (psychology, motives, desperation, envy, greed).
-
The victim’s perceptions (shock, fear, economic cost, moral outrage).
-
Cultural context (property norms, wealth distribution, kinship expectations).
-
Economic context (poverty, inequality, access to resources).
-
Legal context (statutory definitions, case precedent, punishment regimes).
-
Social consequences (trust erosion, group stability, retaliation risk).
-
Ethical theories (utilitarian, deontological, virtue-ethical arguments).
-
Truth (Testifiability):
Did a demonstrated interest exist (ownership)?
Did the action occur (removal of property)?
Can both be testified to?
-
Reciprocity:
Was the transfer reciprocal (consensual exchange)?
Or asymmetrical (taking without permission/compensation)?
-
Voluntariness:
Was the owner’s consent voluntary?
Or coerced/involuntary?
-
Closure: The case can be resolved without reference to motives, culture, or ideology. Those may explain why theft occurs, but not whether it was theft.
-
Universality: Applies across all societies with property norms, because reciprocity and voluntariness are universal tests.
-
Computability: Requires only binary/ternary distinctions (reciprocal vs not, voluntary vs not), easily handled by both humans and LLMs.
-
Prevents Sophistry: No escape into “context” that justifies the act as not-theft unless reciprocity or voluntariness are restored (gift, exchange, restitution).
-
The deceiver’s intent (malice, negligence, greed, ignorance).
-
The victim’s state of mind (trust, gullibility, desperation, hope).
-
Cultural context (what counts as a lie, puffery, exaggeration, marketing).
-
Economic context (supply/demand pressure, market norms, regulatory oversight).
-
Legal context (statutory definitions, contract law, case precedent).
-
Ethical theories (is lying always wrong, or only when harmful?).
-
Consequences (loss of money, erosion of trust, institutional collapse).
-
Truth (Testifiability):
Was the testimony (word, deed, promise) testifiable?
Was it true or false under available tests (consistency, correspondence, operational repeatability, reciprocity of verification)?
-
Reciprocity:
Did the false testimony induce transfer of a demonstrated interest?
Was the transfer asymmetrical (victim gives, fraudster takes without equivalent return)?
-
Voluntariness:
Was the victim’s consent voluntary, based on accurate testimony?
Or was consent manufactured through deceit, undermining voluntariness?
-
Closure: Fraud can be decisively identified without appeal to motives, contexts, or endless debate about “degrees of lying.”
-
Universality: Works across cultures, because all cooperation depends on reciprocal testimony.
-
Computability: The same three axes (truth, reciprocity, voluntariness) resolve both physical (theft) and linguistic (fraud) violations.
-
Prevents Sophistry: Puffery, exaggeration, or “marketing” are only fraud if they violate testifiability and induce involuntary transfer.
-
Theft: violation of reciprocity through force without consent.
-
Fraud: violation of reciprocity through false testimony undermining consent.
-
Both reduce to the same low-dimensional test: truth, reciprocity, voluntariness.
-
Truth (testifiability of word/deed)
-
Reciprocity (symmetry of demonstrated interests)
-
Voluntariness (consent freely given)
-
Universality: All wrongs collapse into failures of the three dimensions.
Theft = failure of reciprocity + voluntariness.
Fraud = failure of truth + reciprocity + voluntariness.
Coercion = failure of voluntariness + reciprocity.
Propaganda = failure of truth + reciprocity.
-
Decidability: By testing only three axes, any moral/legal dispute can be closed without endless contextual variables.
-
Computability: This is why LLMs can apply your method: the categories are low-dimensional, binary/ternary, and already encoded in language.
-
Hierarchy of Violations:
By Force: theft, violence, murder.
By Word: fraud, breach, propaganda.
By Threat: coercion, extortion.
By Asymmetry Hidden in Complexity: usury, exploitation, parasitism.
