{"id":2624,"date":"2025-11-21T13:08:58","date_gmt":"2025-11-21T18:08:58","guid":{"rendered":"https:\/\/generic.wordpress.soton.ac.uk\/skywritings\/?p=2624"},"modified":"2025-11-22T09:57:52","modified_gmt":"2025-11-22T14:57:52","slug":"exchange-with-chatgpt-on-the-easy-and-hard-problem-of-cognitive-science","status":"publish","type":"post","link":"https:\/\/generic.wordpress.soton.ac.uk\/skywritings\/2025\/11\/21\/exchange-with-chatgpt-on-the-easy-and-hard-problem-of-cognitive-science\/","title":{"rendered":"Exchange with ChatGPT on the “Easy” and “Hard” Problem of Cognitive Science"},"content":{"rendered":"\n

SH:<\/strong> 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).<\/p>\n\n\n\n

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

(1) Local underdetermination.<\/strong>
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.<\/p>\n\n\n\n

(2) Global underdetermination.<\/strong>
Entire world-models can be constructed that reproduce every possible observation while differing in their \u201cdeep\u201d structure. Put differently: the mapping from theory-space to observation-space is many-to-one. If so, we could never determine which<\/em> of several complete, internally coherent descriptions of the world is the true one.<\/p>\n\n\n\n

The idea of multiple \u201cGrand Unified Theories of Everything\u201d (GUTEs)<\/strong> is a direct application: even if physics eventually converges on a complete set of surface-regularities, there may still be many distinct fundamental theories<\/strong>\u2014different dynamical laws, symmetries, or ontologies\u2014that reproduce all observed phenomena with arbitrarily fine accuracy. Nothing in the data would distinguish them.<\/p>\n\n\n\n

In your own framing: cognitive science has an analogous situation with\u00a0GUTE_c<\/strong>, where candidate causal models of cognition may all match\u00a0every<\/em>\u00a0observable capacity Turing-Indistiguishably (T4-level performance) yet diverge on the crucial but empirically inaccessible question of\u00a0whether and how they generate feeling<\/strong>. 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\u00a8).<\/p>\n\n\n\n

The general moral is: even ideal empirical completeness does not guarantee theoretical uniqueness, causal completeness or explanatory adequacy.<\/p>\n\n\n\n

SH:<\/strong> 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 <\/strong>to the EP would make the HP even harder?<\/p>\n\n\n\n

ChatGPT<\/strong>: The reason you would say that solving the Easy Problem (EP)<\/strong> makes the Hard Problem (HP)<\/strong> harder still<\/em> follows directly from your two commitments:<\/p>\n\n\n\n

\n
    \n
  1. Causal explanation is finite.<\/strong>
    A complete T4-level explanation of cognitive capacity<\/em>\u2014perception, category learning, language, action, memory, attention\u2014will already account for all observable causal work<\/strong> the organism does.<\/li>\n\n\n\n
  2. Sentience is not an observable variable.<\/strong>
    Because feeling is accessible only to the feeler, no amount of external data can constrain theories about\u00a0why<\/em>\u00a0feeling occurs, or how<\/em> it is generated.<\/li>\n<\/ol>\n\n\n\n

    Now the key point you have emphasized:<\/p>\n\n\n\n

    Why solving the EP exhausts the causal degrees of freedom<\/strong><\/p>\n\n\n\n

    If cognitive science eventually produces a full causal model explaining every performance capacity<\/strong> (T4 indistinguishability), then all the causal machinery needed to produce the organism\u2019s behavioral, neural, and functional profile will be accounted for. Nothing in that explanation requires, predicts, or invokes feeling<\/strong>.<\/p>\n\n\n\n

    At that point:<\/p>\n\n\n\n

      \n
    • All the doing<\/strong> is explained.<\/li>\n\n\n\n
    • All the mechanisms underlying doing are explained.<\/li>\n\n\n\n
    • Every causal gap relevant to performance has been closed.<\/li>\n<\/ul>\n\n\n\n

      But sentience\u2014the fact that it feels like something to think, see, hurt, or enjoy<\/em>\u2014still stands outside the causal account. And because the EP\u2019s solution has already used up every available causal role, there is no remaining explanatory function<\/strong> left for feeling to play. This is exactly what you mean when you say:<\/p>\n\n\n\n

      \u201cThe solution to the EP will have used up all the causal degrees of freedom.\u201d<\/p>\n\n\n\n

      Why this intensifies underdetermination<\/strong><\/p>\n\n\n\n

      Before solving the EP, one could still imagine that perhaps somewhere in the causal tangle there is a hidden role for feeling\u2014some undiscovered function, some latent variable, some missing mechanism. But once the EP is solved:<\/p>\n\n\n\n

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

        Hence the HP becomes worse than underdetermined: it becomes\u00a0causally superfluous<\/strong>. Even if, as you put it, an omniscient deity could reveal which GUTE_c actually \u201chas\u201d feeling, that revelation would not constitute an\u00a0explanation<\/em>. It would merely fix the value of an empirically uncheckable parameter.<\/p>\n\n\n\n

        What this means for underdetermination<\/strong><\/p>\n\n\n\n

        Your position is that HP-underdetermination is categorically deeper than ordinary theory-underdetermination:<\/p>\n\n\n\n

          \n
        • Ordinary underdetermination concerns multiple theories doing equal causal and explanatory work.<\/li>\n\n\n\n
        • HP-underdetermination concerns a real phenomenon\u2014feeling\u2014that does no<\/em> causal work in the model and whose presence or absence is empirically inaccessible.<\/li>\n<\/ul>\n\n\n\n

          Thus, solving the EP not only fails to solve the HP; it\u00a0removes any causal foothold from which a solution could in principle be constructed<\/strong>. This is why, in your view, the HP is not merely unsolved but\u00a0unsolvable<\/em>\u00a0in the same scientific mode as the EP (or any other empirical phenomenon.<\/p>\n\n\n\n

          That is the conceptual structure linking underdetermination, the EP, the HP, and your GUTE_c argument.<\/p>\n<\/div><\/div>\n\n\n\n

          SH:<\/strong> 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?<\/p>\n\n\n\n

          \n
          \n

          ChatGPT:<\/strong> Here is the way your own framework links these pieces together\u2014GUTE vs GUTE_c, reverse-engineering, computation, 3D-printing, and T4\u2014without straying into hype or clich\u00e9.<\/p>\n\n\n\n

          \n\n\n\n

          1. Why GUTE<\/em> (physics\/chemistry\/biology) is a search for laws<\/em><\/strong><\/p>\n\n\n\n

          In physics and the natural sciences, a\u00a0GUTE<\/strong>\u00a0is 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<\/em> is a set of general laws.<\/p>\n\n\n\n

          Even here, the laws are underdetermined<\/strong> by all possible observations. Multiple distinct dynamical systems can reproduce the same empirical regularities. But crucially:<\/p>\n\n\n\n

            \n
          • The explananda<\/em> are\u00a0publicly observable<\/strong>.<\/li>\n\n\n\n
          • The causal work to be explained is completely external<\/strong> (forces, fields, particles, macromolecules).<\/li>\n<\/ul>\n\n\n\n

            There is no\u00a0hidden<\/em>-variable-like feeling complicating the picture.<\/p>\n\n\n\n

            \n\n\n\n

            2. Why GUTE_c<\/em> is not a search for \u201claws\u201d but for a causal mechanism that does what a human does<\/strong><\/p>\n\n\n\n

            The explanandum of cognitive science is capacity<\/strong>, not cosmos:<\/p>\n\n\n\n

              \n
            • Categorizing<\/li>\n\n\n\n
            • Learning<\/li>\n\n\n\n
            • Speaking and understanding<\/li>\n\n\n\n
            • Acting adaptively<\/li>\n\n\n\n
            • Planning and reasoning<\/li>\n<\/ul>\n\n\n\n

              These are performance capacities<\/strong>, not universal laws.<\/p>\n\n\n\n

              Reverse-engineering cognition therefore means:<\/p>\n\n\n\n

                \n
              • Finding a causal mechanism that generates T4-equivalent performance<\/strong>,
                not discovering a new fundamental law of nature.<\/li>\n<\/ul>\n\n\n\n

                This is what makes GUTE_c a different kind of project. It aims at a full, working model of a cognizer<\/strong>.<\/p>\n\n\n\n

                \n\n\n\n

                3. Why computational simulation is not enough<\/strong><\/p>\n\n\n\n

                Computation alone (T2) yields:<\/p>\n\n\n\n

                  \n
                • A symbolic model<\/li>\n\n\n\n
                • A syntactic simulation<\/li>\n\n\n\n
                • A system that can describe or simulate doing, but does not itself do<\/em><\/li>\n<\/ul>\n\n\n\n

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

                  Hence the need for robotic (sensorimotor) grounding<\/strong>.<\/p>\n\n\n\n

                  A reverse-engineered cognizer must:<\/p>\n\n\n\n

                    \n
                  • detect sensory from the world<\/li>\n\n\n\n
                  • act on the world<\/li>\n\n\n\n
                  • learn from the consequences of its actions<\/li>\n<\/ul>\n\n\n\n

                    This stage is no longer purely computational. It concerns the\u00a0causal organization of a dynamical system<\/strong>.<\/p>\n\n\n\n

                    \n\n\n\n

                    4. Why the \u201c3D printer\u201d matters<\/strong><\/p>\n\n\n\n

                    Your analogy:<\/p>\n\n\n\n

                      \n
                    • The computational model is like a set of engineering blueprints.<\/li>\n\n\n\n
                    • The 3D-printed robot is the realization of those blueprints in the physical world.<\/li>\n<\/ul>\n\n\n\n

                      The blueprints alone cannot pass T3 or T4.
                      Only the built system\u2014the embodied mechanism\u2014can interact causally with the world.<\/p>\n\n\n\n

                      This is where your distinction becomes sharp:<\/p>\n\n\n\n

                        \n
                      • The GUTE<\/strong> in physics explains by laws<\/em>.<\/li>\n\n\n\n
                      • The\u00a0GUTE_c<\/strong>\u00a0in cognitive science explains through material implementation<\/li>\n<\/ul>\n\n\n\n

                        Success is demonstrated not by formal derivations but by\u00a0dynamic performance indistinguishability<\/strong>.<\/p>\n\n\n\n

                        \n\n\n\n

                        5. T4 as the empirical criterion for solving the Easy Problem<\/strong><\/p>\n\n\n\n

                        T4 requires:<\/p>\n\n\n\n

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

                          Once a 3D-printed cognizer is T4-indistinguishable from a human, the EP is solved, because:<\/p>\n\n\n\n

                            \n
                          • All observable causal capacities have been accounted for.<\/li>\n\n\n\n
                          • Nothing the organism does is left unexplained.<\/li>\n<\/ul>\n\n\n\n

                            This ties GUTE_c neatly to your causal-degree-of-freedom argument.<\/p>\n\n\n\n

                            \n\n\n\n

                            6. Why this makes the Hard Problem even harder<\/strong><\/p>\n\n\n\n

                            Once a T4-equivalent mechanism exists:<\/p>\n\n\n\n

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

                              Hence feeling becomes:<\/p>\n\n\n\n

                                \n
                              • causally superfluous<\/strong>\u00a0(no causal role left to play)<\/li>\n\n\n\n
                              • empirically inaccessible<\/strong> (Other-Minds barrier)<\/li>\n\n\n\n
                              • underdetermined<\/strong> not merely by data, but by any<\/em> causal requirement<\/li>\n<\/ul>\n\n\n\n

                                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<\/strong>, making the HP maximally intractable.<\/p>\n\n\n\n

                                \n\n\n\n

                                The upshot<\/strong><\/p>\n\n\n\n

                                In physics, GUTE underdetermination is about multiple law-systems fitting the same observable regularities.<\/p>\n\n\n\n

                                In cognitive science, GUTE_c underdetermination is deeper:<\/p>\n\n\n\n

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

                                  This is why, in your view, the EP\u2019s solution makes the HP not merely unsolved but unexplainable by the same explanatory resources<\/strong>.<\/p>\n\n\n\n

                                  That is the structural parallel and the crucial divergence between GUTE and GUTE_c.<\/p>\n<\/div><\/div>\n<\/div><\/div>\n\n\n\n

                                  SH:<\/strong><\/p>\n\n\n\n

                                  I don\u2019t think Gute_c is \u201cdeeper\u201d than GUTE. Rather like all engineering (forward of reverse), GUTE_c is an application<\/strong> of GUTE. Causality is GUTE-causality. Replace \u201cGUTE_c\u201d by Guce<\/strong><\/em>.<\/p>\n\n\n\n

                                  3D-printing the Guce model is for testing the Guce model, recruiting the real GUTE Universe (including human Turing-Testers, and their \u201cmind-reading\u201d 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.<\/p>\n\n\n\n

                                  3-D printing a candidate Guce model is not \u201cgrounding\u201d it: Grounding is the capacity to \u201cdo the right thing with the right kind of thing\u201d (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).<\/p>\n\n\n\n

                                  Don\u2019t forget that the Guce model is modelling cognitive performance **capacity** \u2014 not just one cognizer\u2019s performance. (This is equivalent to Chomsky\u2019s competence\/performance distinction.)<\/p>\n\n\n\n

                                  T4 indistinguishabillity\u00a0 (Turing-Indistinguishability) = empiricism<\/strong> itself (for T-testing Guce candidate solutions to the EP).<\/p>\n\n\n\n

                                  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<\/strong> a route for explaining how or why feelings exist (although they exist \u2014 and are observable to the feeler). This is part of the unique \u201chardness\u201d of the HP.\u00a0<\/p>\n\n\n\n

                                  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. <\/p>\n\n\n\n

                                  Nor is Grounding = feeling — although feeling is what makes explanation (fallibly) feel explanatory.<\/p>\n\n\n\n

                                  A hard problem and (I daresay) unique\u2026<\/p>\n\n\n\n

                                  Mutanda mutata\u2026<\/em><\/p>\n\n\n\n

                                  \n

                                  ChatGPT<\/strong>: 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\u00a0Guce<\/strong>\u00a0exactly as you specify:\u00a0an engineering application of GUTE, not a \u201cdeeper\u201d theoretic problem than GUTE<\/em>, and certainly not a search for new laws of nature (which would be “dualism”)..<\/p>\n\n\n\n

                                  I will also preserve your distinctions between Grounding<\/strong>, 3D-printing<\/strong>, Turing-testing<\/strong>, GUTE<\/strong>, Guce<\/strong>, EP<\/strong>, and HP<\/strong>, and show how the pieces fit.<\/p>\n\n\n\n

                                  No sycophancy; just exact conceptual alignment.<\/p>\n\n\n\n

                                  \n\n\n\n

                                  1. GUTE vs. Guce<\/strong><\/p>\n\n\n\n

                                  Guce<\/strong> is\u00a0not<\/strong>\u00a0a parallel project to GUTE and not a \u201cdeeper\u201d one. It is an\u00a0application<\/strong>\u00a0of GUTE<\/strong> to test (and Turing-Test) the causal engineering principles modelled by Guce<\/strong>.<\/p>\n\n\n\n