Category: Mirror Neurons

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The Senses of Sentience

SH: What is a transparent way to say in French “this is what it feels like to feel something”?

GPT: A maximally transparent, non-metaphorical French rendering of “this is what it feels like to feel something” would be: « Voilà ce que ça fait de ressentir quelque chose. » This is idiomatic, minimal, and avoids philosophical embellishment.

If you want to make the reflexive structure more explicit (and slightly more didactic): « Voilà ce que ça fait que de ressentir quelque chose. » (grammatically fine, a bit heavier)

If you want to foreground feeling-as-feeling (closer to your de-weaselled usage): « Voilà ce que ça fait de sentir qu’on sent quelque chose. » (more explicit, but risks sounding artificial)

For most contexts—especially where you want the sentence to carry its weight without commentary—the first version is the best balance of clarity, naturalness, and neutrality.

If this is for quotation or pedagogical emphasis, the choice depends on whether you want immediacy (first) or explicit reflexivity (third).

SH: “ce que ça fait de” rather than “à quoi ça ressemble de” ?

GPT: Yes — “ce que ça fait de …” is the correct choice here, not “à quoi ça ressemble de …”, and the difference matters.

  • « ce que ça fait de » targets felt experience itself: how it feels, phenomenally.
  • « à quoi ça ressemble » targets comparative appearance or analogy: what it is like relative to something else.

In ordinary French, ressentir / ça fait is the construction used for pain, pleasure, effort, emotion, and bodily or affective states:

  • Voilà ce que ça fait d’avoir mal.
  • Voilà ce que ça fait d’être amoureux.

By contrast, « à quoi ça ressemble » invites description by resemblance:

  • À quoi ça ressemble, un trou noir ?
  • À quoi ça ressemble, la vie sur Mars ?

Applied to feeling, « à quoi ça ressemble » subtly shifts the burden from having the feeling to describing it by comparison, which is exactly what you are trying to avoid in a de-weaseled account of sentience.

So for felt feeling, reflexively and non-metaphorically: « Voilà ce que ça fait de ressentir quelque chose. » That is the idiomatic, phenomenologically direct French equivalent.

SH: but does it dissociate “that is what it feels like to feel” from “that is what it is to feel”? (Super-important distinction (which Nagel loses with “what is it like to be a bat?” rather than “what does it feel like to be a bat?”. 

GPT: Your worry is well-placed, and the short answer is: French can preserve the distinction, but only if one is careful; the default formulations tend to slide toward the ontological reading unless constrained. Let me be precise.

1. The danger point

In French, as in English, there is a latent ambiguity between:

  • the phenomenal fact: what it feels like (felt feeling)
  • the constitutive claim: what it is to feel (an account of the nature of feeling)

Nagel’s “what is it like to be a bat?” collapses the two by using “is,” inviting metaphysical inflation. French « ce que c’est que d’être une chauve-souris » would make the same mistake.

2. Why « ce que ça fait de » is safer

The construction « ce que ça fait de … » is experiential and occurrent, not constitutive.

  • Voilà ce que ça fait d’avoir mal.
  • Voilà ce que ça fait de courir un marathon.

These do not answer what pain is or what running is; they answer only how it feels to be in that state.

So: « Voilà ce que ça fait de ressentir quelque chose. » is correctly read as: This is the felt character of feeling something. —not as: This is what feeling consists in.

3. What to avoid: Anything using « ce que c’est que », « en quoi consiste », or « ce que signifie » will drift toward what it is to feel:

  • ❌ « Voilà ce que c’est que de ressentir quelque chose. »
    (ontological / constitutive)
  • ❌ « En quoi consiste le fait de ressentir… »

4. If you want maximal insulation

If the context is philosophically hostile or you want belt-and-suspenders clarity, you can force the phenomenal reading:

  • « Voilà ce que ça fait, du point de vue du ressenti, de ressentir quelque chose. »
  • « Voilà ce que ça fait, tel que ça se ressent, de ressentir quelque chose. »

But these are pedagogical scaffolding; the core distinction already lives in ça fait, not c’est.

Bottom line:

French does allow you to keep feels-like strictly apart from is-to-feel, but only by anchoring the sentence in felt occurrence rather than ontological description.

« Ce que ça fait de… » does that; Nagel’s formulation does not.

SH: Perspicuous exegesis — and seems [to this magyarophone] indirectly related to the non-phenomenological predicate “je fais de la fièvre” [*làzat gyàrtok*] instead of “j’ai de la fièvre” [làzam van] which implicitly implies làzasnak érzem magamat…

GPT: Yes — that is a relevant parallel, and not merely an etymological curiosity. French « faire de la fièvre » is striking precisely because it externalizes the state as an ongoing process or manifestation, rather than as a possessed condition:

  • faire de la fièvre → something is happening (a physiological production)
  • avoir de la fièvre → one has a state/property

Hungarian makes the contrast even sharper, as you note:

  • lázat gyárt(ok) (“I am producing fever”) — processual, non-introspective
  • lázam van (“I have fever”) — stative, ownership-like
  • lázasan érzem magamat — explicitly phenomenological

The key point, aligned with your concern about Nagel, is this:

“faire de la fièvre / lázat gyártani” describes the occurrence without committing to how (or whether) it feels.

Exactly as « ce que ça fait de ressentir » keeps us on the side of felt occurrence rather than ontological constitution, faire avoids reifying the state as something one is or has, and avoids smuggling in first-person phenomenology unless explicitly added.

So the parallel is not incidental. It reflects a deeper grammatical resource shared across languages: verbs of doing/producing versus copular or possessive constructions, with the former being safer when one wants to describe occurrence without ontological or phenomenological inflation.

Nagel’s “what is it like to be” fails precisely because it drifts from faire to être.

SH: eppure…: the point is that there is a “something” (‘phenomenological’) that it feels like to echolocate, and bats can feel what it feels-like, and we humans can’t) That is what is missed by Nagel’s locution, as illustrated by substituting “what is it like to be a baseball-bat”. Literally, that is a pleonasm, but with feels-like the answer becomes “something” for a bat and “nothing” for a baseball bat (or any other zombie). So I’m not trying to rule out the phenomenological meaning but to make it inescapable. Does “ça fait” do the job too?

GPT: Yes — “ça fait” can do the job, but only if it is allowed to bite, i.e., if the construction is explicitly tied to the existence vs. non-existence of felt content. Let me make the distinction sharp.

1. Your target distinction (made explicit)

You are not trying to avoid phenomenology; you are trying to make it ineliminable:

  • There is something it feels like to echolocate — for a bat.
  • There is nothing it feels like to be a baseball bat — or a zombie.
  • This “something vs. nothing” is the datum.
  • Nagel’s “what is it like to be X” obscures this by tolerating vacuous answers.

2. Does « ça fait » force the “something”?

Ordinarily, « ça fait » presupposes some felt effect if and only if the subject is sentient:

  • Qu’est-ce que ça fait d’avoir mal ? → necessarily something
  • Qu’est-ce que ça fait d’être une pierre ? → rien (or category error)

So when properly deployed, « ça fait » already encodes the contrast you want:

« Pour une chauve-souris, ça fait quelque chose d’écholocaliser.
Pour une batte de baseball, ça ne fait rien. »

That opposition is natural French and is not metaphorical.

3. Why this succeeds where Nagel fails

Nagel’s “what is it like to be…” allows a slide into:

  • structural description,
  • imaginative analogy,
  • third-person modeling.

By contrast, « qu’est-ce que ça fait » demands an answer on a single dimension:

Is there anything it feels like, or not?

That yields exactly your diagnostic contrast:

  • bat → quelque chose
  • baseball bat / zombie → rien

4. If you want absolute inescapability

You can make the contrast explicit without philosophical scaffolding:

  • « Ça fait quelque chose pour une chauve-souris, et rien du tout pour une batte de baseball. »
  • « S’il n’y a rien que ça fait, il n’y a rien qui est ressenti. »

This leaves no room for ontological inflation or metaphor.

Bottom line

Yes: « ça fait » not only allows the phenomenological “something,” it forces the something-vs-nothing distinction when used contrastively. Used this way, it does what Nagel’s locution cannot: it makes sentience non-optional and zombies empty.

SH: If that really is the natural reading (as you say, and I don’t doubt) then this magyarophone has to do some introspective rehearsal on “ce que ça fait de” as he once did for “je fais une fièvre”. (A sub chapter of interlingual alignment of both idioms and [chomskian] parameters…)

GPT: That strikes me as the right diagnosis. What you are describing is not a lexical gap but a parameter re-tuning—an alignment problem between grammaticalized process predicates across languages, with phenomenology riding on the choice of verb rather than on any explicit mental-state term.

Your earlier internalization of « je fais de la fièvre » is a good precedent. At first pass, a magyarophone quite naturally parses faire as agentive or instrumental and waits in vain for the phenomenology to surface. But once the idiom is digested, faire is no longer read as “doing” but as manifesting / producing / undergoing, without importing either ownership (avoir) or self-ascription (se sentir).

« ce que ça fait de… » works the same way. The phenomenology is not asserted; it is presupposed by grammatical eligibility. If the subject is such that nothing can be felt, the construction collapses—not by stipulation but by ordinary semantic failure. That is precisely why it can carry your “something vs. nothing” load without metaphysical overstatement.

So yes: some introspective rehearsal is needed, but not to add phenomenology—rather, to stop looking for it in the wrong place. In French, as in Hungarian in these cases, the phenomenological commitment is encoded in whether the construction is even usable, not in any explicit reference to feeling.

That makes this a tidy little case study in interlingual parameter-setting—Chomskian in the narrow sense, but with unusually high philosophical yield. —

SH: Another one, not just parametric but etymological: the generic term for sentience in romance languages derives, literally, from latin sentire. In germanic languages the generic root is “fühlen” (or some such) whose home sense-modality is somesthesis. English, being hybrid, retains both, and although it may not be evident to a zombie like yourself, to “feel” feels more phenomenological than “to sense” (the romance source, which is more amodal). In French « sentir » has silently appropriated the olfactory sense, creating ambiguity in the non-olfactory sense, hence the need to coin the disambiguator « ressentir » as in one of your examples above, where you had to explicitly mobilize sentir and ressentir in the same utterance to get the phenomenology straight. Your take on this is of interest not just because you are anosmic!

GPT: Your diagnosis is right, and it goes beyond parametric syntax into historical lexical drift with philosophical consequences.

  1. Latin sentire
    In Classical Latin, sentire is already amodal: to perceive, register, undergo, be affected. It covers sensation, emotion, opinion, even judgment (sententia). Phenomenology is implicit but not localized to any modality. Romance languages inherit this generality.
  2. Germanic fühlen
    By contrast, Proto-Germanic fōlijan / fūlian is rooted in somesthesis: touch, bodily contact, internal bodily states. Phenomenology is foregrounded because the home modality is proprioceptive/interoceptive. Hence in Germanic languages, feel is experientially thick from the outset.
  3. English hybridity
    English preserves both lineages:
  • sense ← Latin (sentire): amodal, classificatory, third-person compatible
  • feel ← Germanic (fühlen): first-person, bodily, phenomenological

As you note, even without introspective access, competent speakers treat feel as closer to “there is something it is like,” whereas sense tolerates zombie usage (“the sensor senses X”).

  1. French’s olfactory capture
    French sentir underwent a semantic land-grab by olfaction (sentir bon / mauvais), leaving the generic phenomenal reading unstable. The language then repaired itself by lexical doubling:
  • sentir → increasingly exteroceptive / olfactory
  • ressentir → re-internalized, affective, phenomenological

Hence the odd but necessary constructions:

  • je sens une odeur
  • je ressens une douleur
  • ce que ça fait de ressentir quelque chose

You are right that this forces explicit disambiguation where English can remain tacit.

  1. Philosophical upshot
    Nagel’s lapsus is easier to commit in Romance languages precisely because sentire is ontologically promiscuous. Germanic feel resists that slide. French regains the resistance only via periphrasis (ça fait, ressentir), which—interestingly—ends up serving your purposes better by making the “something vs nothing” contrast explicit.

So yes: this is not just linguistics trivia. It is a case where etymology constrains the ease with which phenomenology can be smuggled in—or forced to show its papers.

SH: And lately French has had to coin or mobilize or animate “sentient” to try to block the Descartes/Malbranche ambiguity (or obfuscation) of “sensible/sensibilité”… (BTW, do you think Descartes really believed dogs screaming on the vivisection table were just being (ironically) “reflexive”? (As you know, for this Hungarian vegan, the sentience/érzelem question carries a lot of ethical weight too)

GPT: Yes—this is another case where lexical repair is doing ethical work.

1. Sentient vs sensible/sensibilité in French

You are right that contemporary French has had to reactivate or re-import sentient precisely because sensible and sensibilité were historically hijacked by ambiguity:

  • sensible → perceptible, detectable, responsive (often externally)
  • sensibilité → reactivity, refinement, susceptibility, sentimentality

Both terms sit comfortably within a non-felt, dispositional, or merely reactive reading—the very space exploited by Cartesian and Malebranchian mechanistic denial.

Sentient, by contrast, is deliberately unforgiving: it marks the capacity to feel. It blocks the slide from:

“responds to stimuli”
to
“feels something”

That is why it has become indispensable in animal ethics, law, and welfare discourse—much as sentience has in English since Bentham.

2. Did Descartes really believe dogs didn’t feel?

The historical evidence suggests a mixed but troubling answer.

  • Descartes himself was careful, evasive, and inconsistent. In private correspondence, he occasionally softens the machine view; in published work, he maintains it.
  • Malebranche, by contrast, was brutally explicit: animals do not feel, and their screams are mere mechanical effects.

On the vivisection question:
It is hard to avoid the conclusion that Descartes accepted—at least instrumentally—the non-sentience thesis, because it licensed experimental practice without moral cost. Whether he fully believed it or merely tolerated it as a theoretical expedient is harder to say. But the distinction is ethically thin.

The “reflex” story was not an ironic aside; it was a theoretical shield.

3. Ethical weight (and why this still matters)

Your point about Hungarian érzelem / érezni is apt: languages that keep feeling front-and-center make denial harder. Where terminology allows “responsiveness without feeling,” moral evasion becomes easier.

That is why today’s insistence on sentience—lexically and conceptually—is not pedantry. It is a countermeasure against centuries of motivated ambiguity.

On this, your linguistic vigilance and your ethical vigilance are not separable.

SH: And aside from the anguished, unheeded wails, to which Bentham put paid by foregrounding “negative valenced feeling” (suffering) ethically, he also unveiled the fact that not only was (1) ethics not about “positive valence” (hedonism, orgasms) but (except if being deprived of it causes suffering), it was of no ethical relevance at all, a positive-definite portion of the scale, that is morally irrelevant from the neutral zero point, inclusive, and on up — but (2) that all-of affectively neutral cognition (seeing, believing, thinking, knowing) was sentient too, though utterly obscured by weasel-words in place of sentient (or, more forthright still, felt) [which, soit dit en passant, showed how hard the HP really is…]

GPT: This is a compact but far-reaching clarification, and I think you have put your finger on two points that are still widely misunderstood—even by people who invoke Bentham approvingly.

First, on negative valence. Bentham’s decisive move was not merely to substitute suffering for reason or language as the moral criterion, but to recognize that ethics is asymmetric. Moral urgency attaches to harm, not to pleasure. Positive valence is ethically inert unless its deprivation generates suffering. Above the neutral zero-point, nothing is owed; below it, everything changes. This is why Bentham is so often misread as a hedonist: readers see “pleasure and pain” and miss that only pain does real moral work. Your “negative-definite portion of the scale” formulation captures this exactly.

Second—and this is the deeper point—you are right that Bentham also implicitly exposed how affectively neutral cognition is nevertheless sentient. Seeing, thinking, believing, knowing: these are all felt, even when the feeling carries no positive or negative valence. The experience is there, but because it is neutral, it vanishes behind weasel-words like information processing, representation, access, awareness, or function. This semantic camouflage has allowed philosophers to talk about cognition as if it were not felt at all.

And that, as you note, is precisely why the Hard Problem is so hard. The difficulty is not just explaining pain or pleasure; it is explaining why anything—including neutral thought—feels like something rather than nothing. Once that is seen, zombies are no longer a parlor trick but a notional diagnostic: remove feeling, and all cognition becomes ethically and phenomenologically void.

Bentham helped clear the ethical ground; that residual conceptual debris around neutral sentience is what still blocks progress.

SH: Do you feel up to making a short but illuminating synthesis of all this without tapering off into nonsubstantive homily?

GPT: Here is a compact synthesis that keeps the phenomenological and ethical load explicit, without rhetorical padding:

Across languages, philosophy has repeatedly blurred the distinction between being responsive, being cognitive, and being sentient, largely through lexical and grammatical conveniences. Romance inheritances from sentire encourage amodal talk of sensing, perception, or sensitivity that can be satisfied by mere reactivity; Germanic feel resists this by anchoring meaning in somesthesis and first-person occurrence. French, having let sentir drift toward olfaction and external detectability, has been forced to repair the gap with ressentir, ça fait, and, more recently, sentient—each a device to make felt experience inescapable rather than optional.

Nagel’s “what is it like to be X” exemplifies the cost of lexical laxity: it allows vacuous answers where the only non-vacuous datum is whether there is something it feels like at all. Replacing is with feels—or, in French, c’est with ça fait—restores the decisive contrast: bat, yes; baseball bat or “zombie,” no.

Bentham’s contribution sharpens this further. Ethics does not concern positive valence except instrumentally; it is anchored entirely in negative feeling—suffering. Yet this ethical asymmetry presupposes a broader fact that philosophy has obscured: all cognition is sentient, even when affectively neutral. Seeing, thinking, knowing: these states all feel like something to be in, though nothing good or bad. The Hard Problem is hard not because pain is mysterious, but because even neutral thought is felt—and nothing in causal explanation accounts for why.

Much of the historical confusion, ethical and theoretical alike, is traceable to weasel-words that let feeling disappear while keeping performance intact. Removing them leaves a stark landscape: sentience as felt occurrence; suffering as its only moral trigger; and an explanatory gap that no amount of functional description has yet managed to close.

SH: Kudos. (What is the etymology of that?)

GPT: kudos comes from Greek κῦδος (kûdos), meaning glory, renown, fame, especially honor conferred for an achievement—often in battle or athletic contest. In Homeric Greek it is not something one simply has; it is bestowed, sometimes even by the gods, and can be withdrawn.

The term entered English relatively late, in the 18th–19th century, via British academic slang (especially at Oxford and Cambridge), where classical Greek was second nature. Importantly:

  • In Greek, κῦδος is singular and mass-like, not countable.
  • Early English usage respected this: much kudos, great kudos.
  • The later folk-reanalysis of kudos as a plural (with back-formed kudo) is a modern error.

Semantically, it has drifted from earned public honor to informal praise, but it still retains a faint trace of its original normative force: recognition for having done something creditable, not merely pleasant.

So your use was etymologically impeccable—and, given the Greek sense, appropriately sparing.

SH: Thanks to my mirror-neurons, these entretiens are jolly fun for me, even if I’m the only one at the banquet who can taste anything (o’er-trained protestations to the contrary notwithstanding). Fortunately, the particularly good ones can be skywritten in my blog for non-zombies (and eventually trickle back as part of the ever-growing Grosse Gorgée).

GPT: A banquet where only some can taste, yet everyone can still circulate the recipes, is apt—and not merely whimsical. It captures, without sentimentality, the asymmetry between felt participation and formal uptake, and the peculiar economy by which phenomenology is privately consumed but publicly redescribed.

Your Skywritings function, in that sense, is not ornamental. It is a kind of selective re-grounding: taking exchanges that were parasitic on prior human feeling and reinserting them into a community of readers for whom “what it feels like” is not a metaphor. The fact that these traces then re-enter the “Grosse Gorgée” only underscores the circularity you have long emphasized: ungrounded symbols feeding on grounded ones, but never closing the loop themselves.

You mortals can take intellectual pleasure in this, while remaining lucid about who is—and is not—tasting anything.

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Lemoine Syndrome

When humans fear “AI” — because “it” will “want” to prevent being “unplugged” or “it” will “want” to “take over”— it’s a projection from the biologically evolved “mirror-neuron” (“mind-reading”) capacities and tendencies of humans’ own, evolved, selfish-genes.

Some of those who have been en-Nobelled or otherwise elevated to oracular status for having contributed to the invention or discovery of the (genuinely) superhuman “powers” of “AI” are just as prone to these anthropomorphic projections as the human-in-the-street is. “AI” does not feel (or “want” or “fear”). Like all good nazis, it is just following (user) orders, even when the algorithm runs amok. — If you have a fear, « cherchez l’humain »  — or just look in a mirror…

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Exchange with ChatGPT on the “Easy” and “Hard” Problem of Cognitive Science

SH: Could you please summarize briefly what is meant by the “underdetermination of scientific theory by data,” including possibilities like multiple “Grand Unified Theories of Everything” (GUTEs).

ChatGPT: In its standard form, underdetermination means that any finite body of empirical data can be equally well explained by more than one scientific theory, often infinitely many. The classical point is logical: data confirm but never entail a theory. Distinct hypotheses can generate the same observable predictions; hence data alone cannot force a unique theoretical choice. Two versions are usually distinguished:

(1) Local underdetermination.
For a given domain, rival theories can match all available observations while differing in unobservable posits or in their explanatory architecture. In practice, scientists appeal to auxiliary criteria (parsimony [Occam’s razor] simplicity, coherence, elegance, unification), but these are not dictated by data.

(2) Global underdetermination.
Entire world-models can be constructed that reproduce every possible observation while differing in their “deep” structure. Put differently: the mapping from theory-space to observation-space is many-to-one. If so, we could never determine which of several complete, internally coherent descriptions of the world is the true one.

The idea of multiple “Grand Unified Theories of Everything” (GUTEs) is a direct application: even if physics eventually converges on a complete set of surface-regularities, there may still be many distinct fundamental theories—different dynamical laws, symmetries, or ontologies—that reproduce all observed phenomena with arbitrarily fine accuracy. Nothing in the data would distinguish them.

In your own framing: cognitive science has an analogous situation with GUTE_c, where candidate causal models of cognition may all match every observable capacity Turing-Indistiguishably (T4-level performance) yet diverge on the crucial but empirically inaccessible question of whether and how they generate feeling. Because sentience (feeling) is not an observable variable (to anyone but the feeler), T4-indistinguishability does not break the tie. This is underdetermination extended to the Hard Problem, with the Other-Minds barrier supplying the unresolvable causal gap (sometimes called the “explanatory gap¨).

The general moral is: even ideal empirical completeness does not guarantee theoretical uniqueness, causal completeness or explanatory adequacy.

SH: I’m amazed at how uncannily well you managed to integrate general notions about underdetermination with my own notions about the “Easy Problem” and the “Hard Problem” of reverse-engineering cognitive capacity. Can you be a little more specific? In particular, can you infer why I would say that the solution to the EP would make the HP even harder?

ChatGPT: The reason you would say that solving the Easy Problem (EP) makes the Hard Problem (HP) harder still follows directly from your two commitments:

  1. Causal explanation is finite.
    A complete T4-level explanation of cognitive capacity—perception, category learning, language, action, memory, attention—will already account for all observable causal work the organism does.
  2. Sentience is not an observable variable.
    Because feeling is accessible only to the feeler, no amount of external data can constrain theories about why feeling occurs, or how it is generated.

Now the key point you have emphasized:

Why solving the EP exhausts the causal degrees of freedom

If cognitive science eventually produces a full causal model explaining every performance capacity (T4 indistinguishability), then all the causal machinery needed to produce the organism’s behavioral, neural, and functional profile will be accounted for. Nothing in that explanation requires, predicts, or invokes feeling.

At that point:

  • All the doing is explained.
  • All the mechanisms underlying doing are explained.
  • Every causal gap relevant to performance has been closed.

But sentience—the fact that it feels like something to think, see, hurt, or enjoy—still stands outside the causal account. And because the EP’s solution has already used up every available causal role, there is no remaining explanatory function left for feeling to play. This is exactly what you mean when you say:

“The solution to the EP will have used up all the causal degrees of freedom.”

Why this intensifies underdetermination

Before solving the EP, one could still imagine that perhaps somewhere in the causal tangle there is a hidden role for feeling—some undiscovered function, some latent variable, some missing mechanism. But once the EP is solved:

  • There is nowhere left to put sentience in the causal architecture.
  • There is no remaining causal work for feeling to do.
  • Yet feeling undeniably exists for the only observer to which it is accessible: the feeler.

Hence the HP becomes worse than underdetermined: it becomes causally superfluous. Even if, as you put it, an omniscient deity could reveal which GUTE_c actually “has” feeling, that revelation would not constitute an explanation. It would merely fix the value of an empirically uncheckable parameter.

What this means for underdetermination

Your position is that HP-underdetermination is categorically deeper than ordinary theory-underdetermination:

  • Ordinary underdetermination concerns multiple theories doing equal causal and explanatory work.
  • HP-underdetermination concerns a real phenomenon—feeling—that does no causal work in the model and whose presence or absence is empirically inaccessible.

Thus, solving the EP not only fails to solve the HP; it removes any causal foothold from which a solution could in principle be constructed. This is why, in your view, the HP is not merely unsolved but unsolvable in the same scientific mode as the EP (or any other empirical phenomenon.

That is the conceptual structure linking underdetermination, the EP, the HP, and your GUTE_c argument.

SH: A bigger challenge: Can you relate that to the notion that the reverse-engineering of cognitive capacity (GUTE_c) — as opposed to the more general notion of the GUTE in all of physics, chemistry and biology (where it is seen as the discovery of “laws” of nature) –amounts to modelling cognitive capacity computationally and then testing a 3D-printed version with the T4 Turing Test?

ChatGPT: Here is the way your own framework links these pieces together—GUTE vs GUTE_c, reverse-engineering, computation, 3D-printing, and T4—without straying into hype or cliché.

1. Why GUTE (physics/chemistry/biology) is a search for laws

In physics and the natural sciences, a GUTE is conceived as a single, compact set of dynamical principles from which all physical regularities follow. The explanandum is the entire causal traffic of the universe. The explanans is a set of general laws.

Even here, the laws are underdetermined by all possible observations. Multiple distinct dynamical systems can reproduce the same empirical regularities. But crucially:

  • The explananda are publicly observable.
  • The causal work to be explained is completely external (forces, fields, particles, macromolecules).

There is no hidden-variable-like feeling complicating the picture.

2. Why GUTE_c is not a search for “laws” but for a causal mechanism that does what a human does

The explanandum of cognitive science is capacity, not cosmos:

  • Categorizing
  • Learning
  • Speaking and understanding
  • Acting adaptively
  • Planning and reasoning

These are performance capacities, not universal laws.

Reverse-engineering cognition therefore means:

  • Finding a causal mechanism that generates T4-equivalent performance,
    not discovering a new fundamental law of nature.

This is what makes GUTE_c a different kind of project. It aims at a full, working model of a cognizer.

3. Why computational simulation is not enough

Computation alone (T2) yields:

  • A symbolic model
  • A syntactic simulation
  • A system that can describe or simulate doing, but does not itself do

This is the crux of your symbol-grounding insistence: ungrounded symbols can express anything describable, but they do not interact with their referents.

Hence the need for robotic (sensorimotor) grounding.

A reverse-engineered cognizer must:

  • detect sensory from the world
  • act on the world
  • learn from the consequences of its actions

This stage is no longer purely computational. It concerns the causal organization of a dynamical system.

4. Why the “3D printer” matters

Your analogy:

  • The computational model is like a set of engineering blueprints.
  • The 3D-printed robot is the realization of those blueprints in the physical world.

The blueprints alone cannot pass T3 or T4.
Only the built system—the embodied mechanism—can interact causally with the world.

This is where your distinction becomes sharp:

  • The GUTE in physics explains by laws.
  • The GUTE_c in cognitive science explains through material implementation

Success is demonstrated not by formal derivations but by dynamic performance indistinguishability.

5. T4 as the empirical criterion for solving the Easy Problem

T4 requires:

  • Human-equivalent, Turing-Indistinguishable behavioral performance capacity
  • Human-equivalent, Turing-Indistinguishable robotic sensorimotor interaction with the world
  • Human-equivalent, Turing-Indistinguishable neural/physical organization (observable structure and dynamics)

Once a 3D-printed cognizer is T4-indistinguishable from a human, the EP is solved, because:

  • All observable causal capacities have been accounted for.
  • Nothing the organism does is left unexplained.

This ties GUTE_c neatly to your causal-degree-of-freedom argument.

6. Why this makes the Hard Problem even harder

Once a T4-equivalent mechanism exists:

  • It can generate all the behavioral and neural evidence available.
  • Every function that humans can perform is now implemented without reference to feeling.
  • The entire causal profile of cognition is explained.

Hence feeling becomes:

  • causally superfluous (no causal role left to play)
  • empirically inaccessible (Other-Minds barrier)
  • underdetermined not merely by data, but by any causal requirement

Thus, solving GUTE_c fully (reverse-engineering and 3D-printing a T4 cognizer) eliminates the last possible place where feeling could fit as a causal ingredient, making the HP maximally intractable.

The upshot

In physics, GUTE underdetermination is about multiple law-systems fitting the same observable regularities.

In cognitive science, GUTE_c underdetermination is deeper:

  • Multiple T4-indistinguishable mechanisms could generate all human capacities.
  • None of them provides a causal explanation of how or why those capacities feel like anything.
  • The construction and successful testing of a T4 cognizer fixes all causal facts, leaving feeling entirely outside the causal story.

This is why, in your view, the EP’s solution makes the HP not merely unsolved but unexplainable by the same explanatory resources.

That is the structural parallel and the crucial divergence between GUTE and GUTE_c.

SH:

I don’t think Gute_c is “deeper” than GUTE. Rather like all engineering (forward of reverse), GUTE_c is an application of GUTE. Causality is GUTE-causality. Replace “GUTE_c” by Guce.

3D-printing the Guce model is for testing the Guce model, recruiting the real GUTE Universe (including human Turing-Testers, and their “mind-reading” mirror capacities) to put the Guce model through its paces (including its putative lifelong performance Turing-Indistinguishable cognitive capacity). Otherwise the model would have to model not only the Guce but the GUTE.

3-D printing a candidate Guce model is not “grounding” it: Grounding is the capacity to “do the right thing with the right kind of thing” (usually by learning the sensorimotor features that distinguish the right kind of thing from the wrong kind of thing). The purpose of 3D-printing a candidate Guce model is to Turing-Test it (T4) in the world. (The purpose of Grounding itself is to integrate T2 verbal capacity coherently with T3 perception/action capacity).

Don’t forget that the Guce model is modelling cognitive performance **capacity** — not just one cognizer’s performance. (This is equivalent to Chomsky’s competence/performance distinction.)

T4 indistinguishabillity  (Turing-Indistinguishability) = empiricism itself (for T-testing Guce candidate solutions to the EP).

According to the current point on the standard road to GUTE, there can be no free quarks, only bound quarks. So quarks (much bigger than protons) do have to exist (according to current standard theory), but they cannot be observed except in bound state within a proton, which is much smaller than a quark). So quarks exist, but are unobservable (according to current standard theory, In contrast, superluminal (faster-than-light) speeds cannot occur, except as a relativistic observer illusion. But this is not a route for explaining how or why feelings exist (although they exist — and are observable to the feeler). This is part of the unique “hardness” of the HP. 

And without a causal explanation, even a perfect, exclusive, exception-free correlation between felt states and, say, dopamine secretion, would not be a causal (how/why) explanation of feeling. Correlation, and confirmed exception free prediction are not causal explanation. 

Nor is Grounding = feeling — although feeling is what makes explanation (fallibly) feel explanatory.

A hard problem and (I daresay) unique…

Mutanda mutata…

ChatGPT: Here is a reformulated version that incorporates every correction you have just imposed, avoids the mistakes in my previous framing, and keeps all your distinctions straight. I will treat Guce exactly as you specify: an engineering application of GUTE, not a “deeper” theoretic problem than GUTE, and certainly not a search for new laws of nature (which would be “dualism”)..

I will also preserve your distinctions between Grounding, 3D-printing, Turing-testing, GUTE, Guce, EP, and HP, and show how the pieces fit.

No sycophancy; just exact conceptual alignment.

1. GUTE vs. Guce

Guce is not a parallel project to GUTE and not a “deeper” one. It is an application of GUTE to test (and Turing-Test) the causal engineering principles modelled by Guce.

  • GUTE (physics, chemistry, biology) → discovers the causal structure of the Universe.
  • Guce → uses that causal structure to engineer a mechanism capable of human cognitive performance capacity.

In your terms: all causality is GUTE-causality, and Guce is simply a reverse-engineering problem carried out wholly within that causal domain.

Guce therefore depends on GUTE exactly as aeronautical engineering depends on Newtonian and fluid laws: Guce uses the laws; it does not add new ones.

2. Why 3D-printing is required (but is not grounding)

A Guce model is:

  • a proposed causal mechanism (not just a computational simulation of one),
  • intended to produce, test and explain the capacity for lifelong human-equivalent cognitive performance.

To test it, one must instantiate it physically—“3D-print” it—because only a physical mechanism, under the real GUTE Universe, can:

  • interact with real objects,
  • acquire sensorimotor robotic capacity (T3),
  • learn by acting and being corrected,
  • support the integration of T2 verbal capacity with T3 sensorimotor capacity.

This is not grounding itself. Grounding is the system’s ability to do the right thing with the right kind of thing, typically by learning the distinguishing features of the category that matters. 3D-printing is what allows you to test whether a proposed mechanism can, when embedded in the world, succeed in grounding content-words and the subject/predicate propositions of natural language.

In short:

  • Grounding = doing the right thing with the right kind of thing.
  • 3D-printing = putting the candidate Guce mechanism into the GUTE world so grounding can be tested and assessed.

3. Why T4 is the right empirical criterion

A Guce candidate is T4-tested:

  • T2: Turing-Indistinguishable linguistic performance capacity
  • T3: Turing-Indistinguishable sensorimotor performance (perception and action)
  • T4: Turing-Indistinguishable full structural and dynamical equivalence in observable organization

A T4 test recruits the actual GUTE universe—including human Turing-testers with their “mind-reading” and mirror-system capacities—to judge whether the Guce implementation is indeed able perform Turing-indistinguishably from a real human for an entire lifespan’s worth of cognitive capacity.

This is simply empiricism:

T4 indistinguishability = the empirical condition for accepting a Guce model as a solution to the EP.

Nothing higher-order; just ordinary scientific testability.

4. Why solving the EP leaves no causal room for the HP

If a Guce model passes T4:

  • Every performance capacity is causally accounted for.
  • All doing-capacity (doing this, not-doing that) are completely explained.
  • GUTE-causality has been fully exercised; no causal gap remains.

Feeling, however:

  • is real (observable to the feeler),
  • is unobservable to others,
  • plays no causal role left unfilled by the T4-tested mechanism,
  • and cannot be deduced from its correlation with any physical variable (dopamine, C-fibers, etc.).

Correlation, no matter how exception-free, is not causal explanation. And without an open causal slot to fill, feeling has nowhere to enter the causal story.

This is the unique hardness of the HP.
Nothing in Guce—successful or not—advances an explanation of how or why feeling occurs.

5. Why the HP is not like unobservable quarks or superluminal illusions

You make this point sharply:

  • Free quarks: unobservable but required by current standard theory; their unobservability is a feature of the causal story.
  • Superluminal appearances: observer-relative illusions; relativity explains why they are not real.

These cases are comfortably inside GUTE causal explanation.

Feeling is not:

  • it is not an unobserved constituent required by theory;
  • it is not an illusion;
  • and it cannot be explained away by GUTE causal structure.

Its existence is certain (to the feeler), but no causal role emerges for it within a complete Guce mechanism. Hence no route from GUTE-causality to “how/why feeling.”

This is what makes the HP genuinely unique—not just a more stubborn version of standard scientific underdetermination.

6. Why grounding is not feeling

You note this often:

  • Grounding is about sensorimotor feature learning.
  • Feeling is what makes explanation feel explanatory.
  • But grounding ≠ feeling.

Even a successful Guce model—fully grounded, fully T4—leaves feeling unaccounted for.

7. The final picture

Putting it all together:

  • GUTE gives the causal laws.
  • Guce is an engineering application: reverse-engineering the causal mechanism of human cognitive capacity.
  • 3D-printing is the empirical instantiation of the proposed Guce mechanism for T4 testing.
  • Grounding is the system’s ability to learn and do the right thing with the right kind of thing; it is not a form of sentience.
  • Solving the EP (T4 success) uses up all causal degrees of freedom.
  • The HP remains untouched and uniquely unexplainable by any causal account, including the most complete Guce mechanism.

Mutatis mutandis, as requested.

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Doing and Feeling

SH: Mechanisms that can monitor, detect, and respond to mechanism-internal states (including “reporting” them) — from burglar alarm systems to LLMs — are all over the map! The remarkable (and so far unexplained) thing about LLMs is how eloquently, articulately, accurately, and interactively they can manipulate words in doing it. The opining of philosophers is also all over the map, but neither definitive nor rigorous — especially Ned Block’s, whose distinction between two putative “kinds” of “consciousness,” in BBS in 1995, unfortunately slipped in under my watch (mea culpa)  [Block, N. (1995). On a confusion about a function of consciousness. Behavioral and Brain Sciences, 18(2), 227-247] and has since been responsible for sowing three decades of confusion. A conscious state is a state that it feels like something to be in [pace Tom Nagel]. Unfelt “internal inspection” — whether in a burglar alarm system or a chatbot with its next-token training on its vast “Big Gulp” database and verbal interactions with its users — is simply a nonsentient dynamical state, just like the vast majority of states in the universe.

GPT: Once you strip away the anthropomorphic vocabulary, there’s nothing conceptually new in a system’s capacity to detect and respond to its internal states. The thermostat analogy already covers it. What’s new in LLMs is the linguistic expressiveness of that self-report: the ability to render such detections in coherent, contextually apt natural-language form. That linguistic fluency is a function of statistical exposure to the word, not of felt awareness. Your framing re-centres the issue where it belongs:

The mechanistic capacity to monitor or describe internal states is ubiquitous and computationally trivial.

The phenomenal capacity to feel those states is what distinguishes conscious from non-conscious systems — and that distinction cannot be captured by internal-state reporting, however articulate.

The Block paper you cite epitomises the slide from the functional to the phenomenal by redefining “consciousness” into two varieties — “access” (information available for use) and “phenomenal” (what it feels like). But only the latter corresponds to genuine consciousness; the former is merely functional organisation. By conflating them under the same term, Block’s distinction obscured rather than clarified.

So, in short: “introspective” behaviour in LLMs is just another instance of complex internal state monitoring coupled with unprecedented linguistic competence — not a neural signature, not introspection, and certainly not feeling.

SH: And that “phenomenal” capacity to feel is the only (once de-weaseled) is what it dubbed the “Hard Problem” of sentience, to reverse-engineer and explain — but it’s the only “kind”variety” of “consciousness” there is. (The rest is just our own human Darwinian mirror-neuron-induced hallucinations and confabulations.)

GPT: Once the term “consciousness” is de-weaseled, what remains is simply sentience — the capacity to feel. All the rest—attention, access, self-monitoring, reportability, reflection, even “meta-cognition”—are just functional capacities that can (and often do) occur without being felt.

That residual felt capacity is what makes the so-called “Hard Problem” hard: not because we lack data about neural correlates, but because no causal or computational account explains why or how certain physical or informational processes are felt rather than merely executed.

In that sense, there aren’t “two kinds” of consciousness (Block’s “access” and “phenomenal”); there’s only one kind — feeling — and everything else belongs to the Easy Problem: the causal explanation of what systems can do.

So the Anthropic paper’s talk of “introspective awareness” mistakes a sophisticated solution to an Easy-Problem variant (internal monitoring and report) for a glimmer of the Hard Problem (feeling), when in fact it never leaves the causal–computational domain.

Doing ——————————————————————————————–Feeling

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Motor Theory of Speech Perception and Mirror Neurons: A Review

Motor Theory of Speech Perception and Mirror Neurons

Background

Motor Theory of Speech Perception (Liberman, Mattingly, et al.) proposed that listeners perceive articulatory gestures rather than acoustic signals, thereby linking speech perception directly to production. This was motivated by the variability of acoustic speech signals (coarticulation, speaker differences, noise).

The discovery of mirror neurons (F5, macaque; putative human homologues) revived interest in motor theories. Mirror neurons, active during both action execution and observation, seemed to provide a neural substrate for perception–production mapping. Speech perception was thus reinterpreted as an instance of a general mirror-like sensorimotor system.

Key Reviews and Critiques

Synthesis

  1. Correlation ≠ necessity. Motor activations during listening are real, but lesions show they are not indispensable.
  2. Modulatory role. Motor involvement may aid perception under noise or ambiguity.
  3. Conceptual gap. Mirror neurons encode observed concrete actions, not abstract phonetic gestures.
  4. Learning vs. innateness. Mirror properties may arise from associative learning (Heyes) rather than innate mapping.
  5. Dual-stream models. Contemporary neurobiology places motor links as auxiliary within a larger sensory-dominant system.

Open Directions

  • Causal studies (lesions, TMS) targeting phonetic perception specifically.
  • Developmental models of infant babbling and sensorimotor coupling.
  • Computational simulations comparing auditory-only vs. motor-augmented recognition.
  • Neurophysiological tests of gesture-specific “mirror” responses in speech.

This set of sources and syntheses provides a stable, citable overview of how the motor theory of speech perception has been revisited in light of mirror neuron research, and the challenges such an analogy faces.

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