Jon, Gary F, List, For me, this has been a most valuable discussion. While I had earlier come to the conclusion that Artificial Intelligence is *not* intelligent, the comments and quotes included in this exchange strongly suggest to me that it will never be, *can* never be because it misses the necessary features that characterize intelligence.
As Jon concisely put it, "If genuine semiosis is truly continuous. . . then a digital computer, no matter how sophisticated, can only ever *simulate *it--just as the real numbers do not constitute a true continuum, but usefully *approximate *one for most practical purposes. After all, whenever we humans break up our own reasoning (arguments) into discrete steps--namely, "definitely formulated premisses" and conclusions (argumentations. . .) --we are always doing so artificially and retrospectively, *after *the real and continuous inferential process has already run its course." Yet, to the extent that AI may prove dangerous, I continue to think that it behooves us -- to the extent to which it is possible -- to move AI systems toward Peircean theoretical rhetoric within the communities of inquiry in which each of us may be engaged. Nevertheless, Gary F's warning shouldn't be ignored: "If present experience is any guide. . . , clearly AI systems are going to align with the values of the billionaire owners of those systems (and to a lesser extent the programmers who work for them), which is certainly no cause for optimism. Best, Gary R On Fri, Jan 9, 2026 at 12:30 PM Jon Alan Schmidt <[email protected]> wrote: > Gary R., Gary F., List: > > GF: Having read the fine print at the end of the paper, it’s clear that > Manheim’s article was co-written with several LLM chatbots, and I wonder if > some of the optimism comes from them (or some of them) rather than from the > human side. > > > I noticed that, too, with the result that it is more difficult for me to > take the article seriously. In a 1999 paper > <https://www.jstor.org/stable/40320779>, "Peirce's Inkstand as an > External Embodiment of Mind," Peter Skagestad quotes CP 7.366 (1902) and > points out that Peirce "is not *only *making the point that without ink > he would not be able to express his thoughts, but rather the point that > thoughts come to him in and through the act of writing, so that having > writing implements is a condition for having certain thoughts" (p. 551). I > know firsthand that the act of writing facilitates my own thinking, and I > cannot help wondering if Manheim's choice to delegate so much of the effort > for drafting his article to LLMs precluded him from carefully thinking > through everything that it ended up saying. > > GF: Successful "alignment" is supposed to be between a super "intelligent" > system and *human values*. One problem with this is that human values > vary widely between different groups of humans, so which values is future > AI supposed to align with? > > > If an artificial system were really intelligent, then it seems to me that > it would be capable of *choosing *its own values instead of having a > particular set of human values imposed on it. In a 2013 paper > <https://www.academia.edu/9898586/C_S_Peirce_and_Artificial_Intelligence_Historical_Heritage_and_New_Theoretical_Stakes>, > "C. S. Peirce and Artificial Intelligence: Historical Heritage and (New) > Theoretical Stakes," Pierre Steiner observes that according to Peirce ... > > PS: [H]uman reasoning is notably special (and, in that sense only, > *genuine*) in virtue of the *high *degrees of self-control and > self-correctiveness it can exercise on conduct: control on control, > self-criticism on control, and control on control on the basis of > (revisable and self-endorsed) norms and principles and, ultimately, > aesthetic and moral ideals. ... The fact that reasoning human agents have > *purposes > *is crucial here: it is on the basis of purposes that they are ready to > endorse, change or criticize specific methods of reasoning (inductive, > formal, empirical, ...), but also to revise and reject previous purposes. > Contrary to machines, humans do not only have *specified *purposes. Their > purposes are often vague and general. In other passages, Peirce suggests > that this ability for (higher-order and purposive) self-control is closely > related to the fact that human agents are living, and especially *growing*, > systems. (p. 272) > > > I suspect that much of the worry about "AI safety/alignment," as reflected > by common fictional storylines in popular culture, is a tacit admission of > this. What would prevent a sufficiently intelligent artificial system, > provided that such a thing is even possible, from *rejecting *human > values and instead adopting norms, principles, ideals, and purposes that we > would find objectionable, perhaps even abhorrent? More on the > living/growing aspect of intelligent systems below. > > GF: LLMs have to be artificially supplied with a giant database of > thousands or millions of symbolic texts, and it takes them months or years > to build up the level of language competence that a human toddler has; and > even then is is doubtful whether they *understand *any of it. > > > As with intelligence, I am unconvinced that it is accurate to ascribe > "language competence" to LLMs, especially given the well-founded doubt > about "whether they *understand *any of it." John Searle's famous > "Chinese room" thought experiment seems relevant here, e.g., as discussed > by John Fetzer in his online *Commens Encyclopedia* article > <http://www.commens.org/encyclopedia/article/fetzer-james-peirce-and-philosophy-artificial-intelligence>, > "Peirce and the Philosophy of Artificial Intelligence." Again, in my view, > LLMs do not actually *use *natural languages, they only *simulate *using > natural languages. > > GF: I can’t help thinking that all this has a bearing on the perennial > question of whether semiosis requires *life *or not. > > > In light of the following passage, Peirce's answer is evidently that *genuine > *semiosis requires life, given that it requires *genuine *triadic > relations; but he also seems to define "life" in this context much more > broadly than what we associate with the special science of biology. > > CSP: For forty years, that is, since the beginning of the year 1867, I > have been constantly on the alert to find a *genuine *triadic > relation--that is, one that does not consist in a mere collocation of > dyadic relations, or the negative of such, etc. (I prefer not to attempt a > perfectly definite definition)--which is not either an intellectual > relation or a relation concerned with the less comprehensible phenomena of > life. I have not met with one which could not reasonably be supposed to > belong to one or other of these two classes. ... In short, the problem of > how genuine triadic relationships first arose in the world is a better, > because more definite, formulation of the problem of how life first came > about; and no explanation has ever been offered except that of pure chance, > which we must suspect to be no explanation, owing to the suspicion that > pure chance may itself be a vital phenomenon. In that case, life in the > physiological sense would be due to life in the metaphysical sense. (CP > 6.322, 1907) > > > Elsewhere, Peirce maintains > <https://list.iu.edu/sympa/arc/peirce-l/2025-11/msg00044.html> that a > continuum is *defined* by a genuine triadic relation, so his remarks here > are consistent with my sense that what fundamentally precludes digital > computers from ever being truly intelligent is the *discreteness* of > their operations. As I said before, LLMs are surely quasi-minds whose > individual determinations are *dynamical *interpretants of sign *tokens*; > but those correlates are involved in *degenerate *triadic relations, > which are reducible to their constituent dyadic relations. In my view > <https://list.iu.edu/sympa/arc/peirce-l/2025-11/msg00056.html>, the *genuine > *triadic relation involves the *final *interpretant and the sign *itself*, > which is general > <https://list.iu.edu/sympa/arc/peirce-l/2025-11/msg00019.html> and > therefore a continuum of potential tokens that is *not *reducible to the > actual tokens that individually embody it. > > Regards, > > Jon Alan Schmidt - Olathe, Kansas, USA > Structural Engineer, Synechist Philosopher, Lutheran Christian > www.LinkedIn.com/in/JonAlanSchmidt / twitter.com/JonAlanSchmidt > > On Thu, Jan 8, 2026 at 11:17 AM <[email protected]> wrote: > >> List, I’d like to add a few comments to those already posted by Jon and >> Gary R about the Manheim paper — difficult as it is to focus on these >> issues given the awareness of what’s happening in Minnesota, Venezuela, >> Washington etc. (I may come back to that later.) >> >> Except for the odd usage of the term “interpretant” which Jon has already >> mentioned, I think Manheim’s simplified account of Peircean semiotics is >> cogent enough. But his paper seems to get increasingly muddled in the >> latter half of it. For instance, the “optimism” about future AI that Jon >> sees in it seems quite equivocal to me. Having read the fine print at the >> end of the paper, it’s clear that Manheim’s article was co-written with >> several LLM chatbots, and I wonder if some of the optimism comes from them >> (or some of them) rather than from the human side. >> >> Also, the paper makes a distinction between AI *safety* and the >> *alignment* problem, but then seems to gloss over the differences. >> Succesful “alignment” is supposed to be between a super”intelligent” system >> and *human values*. One problem with this is that human values vary >> widely between different groups of humans, so which values is future AI >> supposed to align with? If present experience is any guide (and it better >> be!), clearly AI systems are going to align with the values of the >> billionaire owners of those systems (and to a lesser extent the programmers >> who work for them), which is certainly no cause for optimism. >> >> I think Stanislas Dehaene’s 2020 book *How We Learn* deals with the >> deeper context of these issues better than Manheim and his chatbot >> co-authors. Its subtitle is *Why Brains Learn Better Than Any Machine … >> for Now.* Reducing this to simplest terms, it’s because brains learn >> from *experience* — “the total cognitive result of living,” as Peirce >> said* — and they do so by a scientific method (an algorithm, as Dehaene >> calls it) which is part of the *genetic* inheritance supplied by >> *biological* evolution. An absolute requirement of this method is what >> Peirce called *abduction* (or retroduction). >> >> For instance, human babies begin learning the language they are exposed >> to from birth, or even before — syntax, semantics, pragmatics and all — >> almost entirely without instruction, by a trial-and-error method. It >> enables them to pick up and remember the meaning and use of a new word *from >> one or two encounters with it*. LLMs have to be artificially supplied >> with a giant database of thousands or millions of symbolic texts, and it >> takes them months or years to build up the level of language competence >> that a human toddler has; and even then is is doubtful whether they >> *understand* any of it. LLM learning is entirely bottom-up and therefore >> works much slower than the holistic learning-from-experience of a living >> bodymind, even though the processing speed of a computer is much faster >> than a brain’s. (That’s why it is so much more energy-hungry than brains >> are.) >> >> I can’t help thinking that all this has a bearing on the perennial >> question of whether semiosis requires *life* or not. I can’t help >> thinking that *experience* requires life, and that is what a “scientific >> intelligence” has to learn from — including whatever *values* it learns. >> It has to be embodied, and providing it with sensors to gather data from >> the external world is not enough if that embodiment does not have a *whole >> world within* it in continuous dialogue with the world without — an >> internal *model*, as I (and Dehaene and others) call it. But I’d better >> stop there, as this is getting too long already. >> >> *The context of the Peirce quote above is here: Turning Signs 7: >> Experience and Experiment <https://gnusystems.ca/TS/xpt.htm#lgcsmtc> >> >> Love, gary f >> >> Coming from the ancestral lands of the Anishinaabeg >> >> >> >> *From:* Gary Richmond <[email protected]> >> *Sent:* 8-Jan-26 04:03 >> *To:* Peirce List <[email protected]>; Gary Fuhrman < >> [email protected]>; Jon Alan Schmidt <[email protected]> >> *Subject:* AI safety and semeiotic, was, Surdity, Feeling, and >> Consciousness, was, Truth and dyadic consciousnessg >> >> >> >> Gary F, Jon, List, >> >> In the discussion of Manheim's paper I think it's important to remember >> that his concern is primarily with* AI safety. Anything* that would >> contribute to that safely I would wholeheartedly support. In my view, >> Peircean semeiotic might prove to be of some value in the matter, but >> perhaps not exactly in the way that Manheim is thinking of it. >> >> Manheim remarks that his paper does not try to settle philosophical >> questions about whether LLMs genuinely reason or only simulate thought, and >> that resolving those debates isn’t necessary for building safer general AI. >> I won't take up that claim now, but suffice it to say that I don't >> *fully* agree with it, especially as I continue to agree with your >> argument, Jon, that AI is* not* 'intelligent'. Can it every be? >> >> What Mannheim claims is necessary re: AI safety is to move AI systems >> toward Peircean semiosis in the sense of their becoming 'participants' in >> interpretive processes. He holds that this is achievable through >> engineering and 'capability' advances rather than "philosophical >> breakthroughs;" though he also says that those advances remain insufficient >> on their own for safety. Remaining "insufficient on its own for full >> safety" sounds to me somewhat self-contradictory. But I think that more >> importantly, he is saying that* if* there are things -- including >> Peircean 'things' -- that we can begin to do now in consideration of AI >> safety, then we ought to consider them, do them! >> >> Manheim claims that AI safety depends on deliberately designing systems >> for what he calls 'grounded meaning', 'persistence across interactions' and >> 'shared semiotic communities' rather than 'isolated agents'. I would tend >> to strongly agree. In addition, AI safety requires goals that are *explicitly >> defined* but also open to ongoing discussion rather than quasi*-emerging >> implicitly* from methods like *Reinforcement Learning from Human >> Feedback *(RLHF) . Manheim seems to be saying that companies developing >> advanced AI should take steps in system design and goal setting -- >> including those mentioned above -- if safety is taken seriously. The >> choice, he says, is between ignoring the implications of Peircean semeiotic >> and continuing merely to refine current systems despite their deficiency >> vis-a-vis safety; OR to embrace Peircean semiosis (whatever that means) and >> intentionally build AI as genuine 'semiotic partners'. But,I haven't a >> clear notion of what he means by 'semeiotic partners', nor a method for >> implementing whatever he does have in mind. >> >> I think Manheim off-handedly and rather summarily unfortunately dismisses >> RLHF -- which is, falsely he argues, claimed as a way of 'aligning' models >> with human values. From what I've read it has not yet really been developed >> much in that direction. As far as I can tell, and this may relate to the >> reason why Manheim seems to reject RLHF in toto, it appears to be more a >> 'reward proxy' trained on human rankings of outputs which are then fed >> back through some kind of loop to strongly influence future responses. >> Human judgment enters only in the 'training'', not as something that a >> complex system can engage with and debate with or, possibly, revise >> understandings over time. In Manheim's view, RLHF is not 'bridging' human >> goals and machine behavior (as it claims) but merely facilitating machine >> outputs to fit *learned preferences*. >> >> Still, whatever else RLHF is doing that is geared specifically* toward >> AI safety*, it would likely be augmented by an understanding of Peircean >> cenoscopic science including semeiotic. I would suggest that the semeiotic >> ideas that it might most benefit from occur in the third branch of *Logic >> as Semeiotic*, namely methodology (methodeutic) , perhaps in the present >> context representing, almost to a T, Peirce's alternative title, *speculative >> rhetoric*. It's in this branch of semeiotic that pragmatism >> (pragmaticism) is analyzed. There is of course much more to be said on >> methodology and theoretical rhetoric. >> >> For now, I would tweak Manheim's idea a bit and would suggest that we >> might try to move AI systems toward Peircean semeiotic rhetoric within >> communities of inquiry. >> >> Best, >> >> Gary R >> > _ _ _ _ _ _ _ _ _ _ > ► PEIRCE-L subscribers: Click on "Reply List" or "Reply All" to REPLY ON > PEIRCE-L to this message. PEIRCE-L posts should go to [email protected] > . > ► <a href="mailto:[email protected]";>UNSUBSCRIBE FROM > PEIRCE-L</a> . 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