Chatbots and Melbots

Something similar to LaMDA can be done with music: swallow all of online music space (both scores and digital recordings) and then spew out more of what sounds like Bernstein or (so far mediocre) Bach – but, eventually, who knows? These projections from combinatorics have more scope with music (which, unlike language, really just is acoustic patterns based on recombinations plus some correlations with human vocal expressive affect patterns, whereas words have not just forms but meanings).

Vocal mimicry includes also the mimicry of the acoustic patterns of the vocal expression of affect: anger, fear, sadness, hope. Dynamics, tempo, articulation, even its harmonic features. But these are affects (feelings), not thoughts. Feeling cold is not the same as thinking “I am cold,” which, miraculously, can be expressed by that verbal proposition that states what I am feeling. And language can state anything: “The cat is on the mat.” The words catmat, and on – all have referents, things and states in the worlds they refer to; and we all know, from our sensorimotor experience, what they are. “Meow” imitates the sound a cat makes, but it does not refer to it the way referring words do. And a sentence is not just a series of referring words. It is a proposition, describing something. As such it also has a truth-value: If the cat is really on the mat, then “the cat is on the mat” is TRUE; otherwise FALSE. None of that is true of music (except of course in song, when the musical and the propositional are combined). 

The notion of “transmitting thought” is a bit ambiguous. I transmit thought if I am thinking that the cat is on the mat, and then I say that the cat is on the mat. If instead of saying it, I mime it, like in charades, by imitating the appearance of the cat, maybe making meowing sounds, and gesturing the shape of a mat, and then its position, and then pantomiming a cat, lying on the space that I’ve mimed as a mat… That would indeed transmit to another person the thought that the cat is on the mat. And sufficiently iconic and programmatic music can transmit that thought too, especially if augmented by dance (which is also pantomime). 

[[I think language originated with communication by gestural pantomime; then the gestures became more and more conventional and arbitrary rather than iconic, and that’s also when the true/false proposition was born. But once propositional gesturing began, the vocal/auditory modality had huge practical advantages in propositional communication over the visual/gestural one [just think of what they all are] and language (and its representation in the brain) migrated to the speech/hearing areas where they are now.]]

Yes, music can express affect, and it can even express thought (iconically). But not only is vocal/acoustic imitation not the best of music, it need not be, for music can not only express affect (and mime some thought); it can also inspire and thereby accompany thought in the listener in the way a pianist or orchestra can accompany (and inspire) a violinist or vocalist.

But music is not propositional. It does not state something which is true or false. You cannot take a composer of (instrumental) music (Lieder ohne Worte) to court for having lied. (That’s why the Soviet Union could only oppress Shostakovich, but could not prove he had said anything false or treasonous.) Language (and thought) has semantics, not just form, nor just resemblance in shape to something else: it has propositional content, true or false.

It is true that it is much harder (perhaps impossible) to describe feelings in words, propositionally, than it is to express them, or imitate their expression iconically; but although it is true that it feels like something to think, and that every thought feels different, thinking is not just what it feels like to think something, but what that thought means, propositionally. One can induce the feeling of thinking that the cat is on the mat by miming it; but try doing that with the sentence that precedes this one. Or just about any other sentence. It is language that opened up the world of abstract thought (“truth,” “justice,” “beauty”) and its transmission. Try to transmit the meaning of the preceding sentence in C# minor… Music can transmit affect (feeling). But try transmitting the meaning of this very sentence in C# minor

Not all (felt) brain states are just feelings (even though all thoughts are felt too). Thoughts also have propositional content. Music cannot express that propositional content. (And much of this exchange has been propositional, and about propositional content, not affective, “about” feeling. And, again, what it feels like to think a proposition is not all (or most) of what thinking is, or what a thought means. 

[[Although I don’t find it particularly helpful, some philosophers have pointed out that just as content words are about their referents (cats, mats), thoughts are about propositions. “The cat is on the mat” is about the cat being on the mat – true, if the cat really is on the mat, false, if not. Just as a mat is what is in your mind when you refer to a mat, the cat being on a mat is what the proposition “the cat is on the mat” is “about.” This is the “aboutness” that philosophers mean by their term “intentionality”: what your intended meaning is, the one you “have in mind” when you say, and mean: “the cat is on the mat.” None of this has any counterpart in music. What Beethoven had in mind with Eroica – and what he meant you to have in mind — was originally an admiration for Napolean’s fight for freedom and democracy, and then he changed his mind, removed the dedication, and wanted you not to have that in mind, because he had realized it was untrue; but the symphony’s form remained the same (as far as I know, he did not revise it).

Shostakovich’s symphonies share with poetry the affective property of irony. He could say a symphony was about Lenin’s heroism, but could make it obvious to the sensitive listener that he meant the opposite (although in the 12th symphony he revised it because he feared the irony in the original was too obvious; the result was not too successful…). But poetry can be both literal – which means propositional – and figurative – which means metaphorical; more a representation or expression of a similarity (or a clash) in form than the verbal proposition in which it is expressed (“my love is a red, red rose”).

Music cannot express the literal proposition at all. And even the metaphor requires a vocal (hence verbal) text, which is then “accompanied” by the music, which may express or interpret the literal words affectively, as Bach does with his cantatas. Even Haydn’s creation depends on the implicit “sub-titling” provided by the biblical tale everyone knows. – But all of this is too abstract and strays from the original question of whether LaMDA feels, understands, intends or means anything at all…]]

I’d say what LaMDA showed was that it is surprisingly easy to simulate and automate meaningful human thinking and speaking convincingly (once we have a gargantuan verbal database plus Deep Learning algorithms). We seem to be less perceptive of anomalies (our mind-reading skills are more gullible) there than in computer-generated music (so far), as well as in scores completed by lesser composers. But experts don’t necessarily agree (as with authentic paintings vs. imitations, or even regarding the value of the original). Some things are obvious, but not all, or always. (Is the completion of the Mozart Requiem as unconvincing as the recent completion of Beethoven’s 10th?)

The “symbol grounding problem” — the problem that the symbols of computation as well as language are not connected to their referents — is not the same as the “hard” problem of how organisms can feel. Symbols are manipulated according to rules (algorithms) that apply to the symbols’ arbitrary shapes, not their reference or meaning (if any).  They are only interpretable by us as having referents and meaning because our heads – and bodies – connect our symbols (words and descriptions) to their referents in the world through our sensorimotor capacities and experience.

But the symbol grounding problem would be solved if we knew how to build a robot that could identify and manipulate the referents of its words out there in the real world, as we do, as well as describe and discuss and even alter the states of affairs in the world through propositions, as we do. According to the Turing Test, once a robot can do all that, indistinguishably from any of us, to any of us (lifelong, if need be, not just a 10-minute Loebner-Prize test for 10 minutes) then we have no better or worse grounds for denying or affirming that the TT robot feels than we have with our fellow human beings.

So the symbol-grounding would be solved if it were possible to build a TT-passing robot, but the “hard” problem would not. 

If it turned out that the TT simply cannot be successfully passed by a completely synthetic robot, then it may require a biorobot, with some, maybe most or all the biophysical and biochemical properties of biological organisms. Then it really would be racism to deny that it feel and to deny it human rights. 

The tragedy is that there are already countless nonhuman organisms that do feel, and yet we treat them as if they didn’t, or as if it didn’t matter. That is a problem incomparably greater than the symbol-grounding problem, the other-minds problem, or the problem of whether LaMDA feels (it doesn’t).

(“Conscious” is just a weasel-world for “sentient,” which means, able to feel. And, no, it is not only humans who are sentient.)

LaMDA & LeMoine

About LaMDA & LeMoine: The global “big-data” corpus of all words spoken by humans is — and would still be, if it were augmented by a transcript of every word uttered and every verbal thought ever thought by humans  — just like the shadows on the wall of Plato’s cave: It contains all the many actual permutations and combinations of words uttered and written. All of that contains and reflects a lot of structure that can be abstracted and generalized, both statistically and algorithmically, in order to generate (1) more of the same, or (2) more of the same, but narrowed to a subpopulation, or school of thought, or even a single individual; and (3) it can also be constrained or biased, by superimposing algorithms steering it toward particular directions or styles.

The richness of this intrinsic “latent” structure to speech (verbalized thought) is already illustrated by the power of simple Boolean operations like AND or NOT. The power of google search is a combination of (1) the power of local AND (say, restricted to sentences or paragraphs or documents) together with (2) the “Page-rank” algorithm, which can weight words and word combinations by their frequency, inter-linkedness or citedness (or LIKEdness — or their LIKEdness by individual or algorithm X), plus, most important ,(3) the underlying database of who-knows how-many terabytes of words so far. Algorithms as simple as AND can already do wonders in navigating that database; fancier algorithms can do even better.

LaMDA has not only data-mined that multi-terabyte word space with “unsupervised learning”, abstracting all the frequencies and correlations of words and combinations of words, from which it can then generate more of the same – or more of the same that sounds-like a Republican, or Dan Dennett or an Animé fan, or someone empathic or anxious to please (like LaMDA)… It can be tempered and tampered by “influencer” algorithms too.

Something similar can be done with music: swallow music space and then spew out more of what sounds like Bernstein or (so far mediocre) Bach – but, eventually, who knows? These projected combinatorics have more scope with music (which, unlike language, really just is acoustic patterns based on recombinations plus some correlations with human vocal expressive affect patterns, whereas words have not just forms but meanings).

LaMDA does not pass the Turing Test because the Turing Test (despite the loose – or perhaps erroneous, purely verbal way Turing described it) is not a game about fooling people: it’s a way of testing theories of how  brains (or anything) produce real thoughts. And verbal thoughts don’t just have word forms, and patterns of word-forms: They also have referents, which are real things and states in the world, hence meaning. The Platonic shadows of patterns of words do reflect – and are correlated with – what words, too, just reflect: but their connection with the real-world referents of those words are mediated by (indeed parasitic on) the brains of the real people who read and interpret them, and know their referents through their own real senses and their real actions in and on those real referents in the real world –the real brains and real thoughts of (sometimes) knowledgeable (and often credulous and gullible) real flesh-and-blood people in-the-world…

Just as re-combinatorics play a big part in the production (improvisation, composition) of music (perhaps all of it, once you add the sensorimotor affective patterns that are added by the sounds and rhythms of performance and reflected in the brains and senses of the hearer, which is not just an execution of the formal notes), word re-combinatorics no doubt play a role in verbal production too. But language is not “just” music (form + affect): words have meanings (semantics) too. And meaning is not just patterns of words (arbitrary formal symbols). That’s just (one, all powerful) way thoughts can be made communicable, from one thinking head to another. But neither heads, nor worlds, are just another bag-of-words – although the speaking head can be replaced, in the conversation, by LaMDA, who is just a bag of words, mined and mimed by a verbal database + algorithms.

And, before you ask, google images are not the world either.

The google people, some of them smart, and others, some of them not so smart (like Musk), are fantasists who think (incoherently) that they live in a Matrix. In reality, they are just lost in a hermeneutic hall of mirrors of their own creation. The Darwinian Blind Watchmaker, evolution, is an accomplice only to the extent that it has endowed real biological brains with a real and highly adaptive (but fallible, hence foolable) mind-reading “mirror” capacity for understanding the appearance and actions of their real fellow-organisms. That includes, in the case of our species, language, the most powerful mind-reading tool of all. This has equipped us to transmit and receive and decode one another’s thoughts, encoded in words. But it has made us credulous and gullible too.

It has also equipped us to destroy the world, and it looks like we’re well on the road to it…

P.S. LeMoine sounds like a chatbot too, or maybe a Gullibot…

12 Points on Confusing Virtual Reality with Reality

Comments on: Bibeau-Delisle, A., & Brassard FRS, G. (2021). Probability and consequences of living inside a computer simulationProceedings of the Royal Society A477(2247), 20200658.

  1. What is Computation? it is the manipulation of arbitrarily shaped formal symbols in accordance with symbol-manipulation rules, algorithms, that operate only on the (arbitrary) shape of the symbols, not their meaning.
  2. Interpretatabililty. The only computations of interest, though, are the ones that can be given a coherent interpretation.
  3. Hardware-Independence. The hardware that executes the computation is irrelevant. The symbol manipulations have to be executed physically, so there does have to be hardware that executes it, but the physics of the hardware is irrelevant to the interpretability of the software it is executing. It’s just symbol-manipulations. It could have been done with pencil and paper.
  4. What is the Weak Church/Turing Thesis? That what mathematicians are doing is computation: formal symbol manipulation, executable by a Turing machine – finite-state hardware that can read, write, advance tape, change state or halt.
  5. What is Simulation? It is computation that is interpretable as modelling properties of the real world: size, shape, movement, temperature, dynamics, etc. But it’s still only computation: coherently interpretable manipulation of symbols
  6. What is the Strong Church/Turing Thesis? That computation can simulate (i.e., model) just about anything in the world to as close an approximation as desired (if you can find the right algorithm). It is possible to simulate a real rocket as well as the physical environment of a real rocket. If the simulation is a close enough approximation to the properties of a real rocket and its environment, it can be manipulated computationally to design and test new, improved rocket designs. If the improved design works in the simulation, then it can be used as the blueprint for designing a real rocket that applies the new design in the real world, with real material, and it works.
  7. What is Reality? It is the real world of objects we can see and measure.
  8. What is Virtual Reality (VR)? Devices that can stimulate (fool) the human senses by transmitting the output of simulations of real objects to virtual-reality gloves and goggles. For example, VR can transmit the output of the simulation of an ice cube, melting, to gloves and goggles that make you feel you are seeing and feeling an ice cube. melting. But there is no ice-cube and no melting; just symbol manipulations interpretable as an ice-cube, melting.
  9. What is Certainly Truee (rather than just highly probably true on all available evidence)? only what is provably true in formal mathematics. Provable means necessarily true, on pain of contradiction with formal premises (axioms). Everything else that is true is not provably true (hence not necessarily true), just probably true.
  10.  What is illusion? Whatever fools the senses. There is no way to be certain that what our senses and measuring instruments tell us is true (because it cannot be proved formally to be necessarily true, on pain of contradiction). But almost-certain on all the evidence is good enough, for both ordinary life and science.
  11. Being a Figment? To understand the difference between a sensory illusion and reality is perhaps the most basic insight that anyone can have: the difference between what I see and what is really there. “What I am seeing could be a figment of my imagination.” But to imagine that what is really there could be a computer simulation of which I myself am a part  (i.e., symbols manipulated by computer hardware, symbols that are interpretable as the reality I am seeing, as if I were in a VR) is to imagine that the figment could be the reality – which is simply incoherent, circular, self-referential nonsense.
  12.  Hermeneutics. Those who think this way have become lost in the “hermeneutic hall of mirrors,” mistaking symbols that are interpretable (by their real minds and real senses) as reflections of themselves — as being their real selves; mistaking the simulated ice-cube, for a “real” ice-cube.

Symbols, Objects and Features

0. It might help if we stop “cognitizing” computation and symbols. 

1. Computation is not a subset of AI. 

2. AI (whether “symbolic” AI or “connectionist’ AI) is an application of computation to cogsci.

3. Computation is the manipulation of symbols based on formal rules (algorithms).

4. Symbols are objects or states whose physical “shape” is arbitrary in relation to what they can be used and interpreted as referring to.

5. An algorithm (executable physically as a Turing Machine) manipulates symbols based on their (arbitrary) shapes, not their interpretations (if any).

6. The algorithms of interest in computation are those that have at least one meaningful interpretation.

7. Examples of symbol shapes are numbers (1, 2, 3), words (one, two, three; onyx, tool, threnody), or any object or state that is used as a symbol by a Turing Machine that is executing an algorithm (symbol-manipulation rules).

8. Neither a sensorimotor feature of an object in the world, nor a sensorimotor feature-detector of a robot interacting with the world, is a symbol (except in the trivial sense that any arbitrary shape can be used as a symbol).

9. What sensorimotor features (which, unlike symbols, are not arbitrary in shape) and sensorimotor feature-detectors (whether “symbolic” or “connectionist”) might be good for is connecting symbols inside symbol systems (e.g., robots) to the outside objects that they can be interpreted as referring to.

10. If you are interpreting “symbol” in a wider sense than this formal, literal one, then you are closer to lit-crit than to cogsci.