Jon S, Gary R, List,
I have found this exchange very helpful, especially because it moves the 
question away from the familiar and often unilluminating question, “Is AI 
conscious?” and toward the more Peircean question concerning the relation among 
semiosis, intelligence, inquiry, and the growth of habit. I want to enter the 
discussion by approaching the issue from a slightly different angle: Peirce’s 
classification of genuine triadic relations, especially in “The Logic of 
Mathematics: An Attempt to Develop My Categories from Within,” and the relation 
of that classification to his broader account of the law of mind.
In that essay, Peirce gives a remarkably important account of triadic 
relations. He distinguishes cases in which a general law governs particular 
facts from the more developed cases of representation, in which one thing 
stands for another to a possible interpretant. A natural law is already triadic 
in an important sense: it is not merely one brute fact striking another brute 
fact. Rather, it is a general rule under which particular facts are brought. A 
law does not merely push; it governs. It mediates between a general possibility 
and its particular actualization.
But Peirce also distinguishes this from the more thoroughly genuine triadic 
relations involved in signs, representations, representamens, interpretants, 
arguments, and symbols. A law governs particular facts. A sign, especially a 
symbol, does something more complex: it can represent not only things, but also 
other signs, other symbols, other rules, and other possible habits of 
interpretation. This is crucial. Symbols do not merely fall under general laws; 
they can represent general laws. They can also modify, criticize, extend, and 
reorganize the very rules by which other symbols are interpreted.
This seems to me one of the decisive points for thinking about AI in Peircean 
terms. A symbol is not merely a token that stands for an object. It is a 
general sign whose interpretive power depends upon habit. Moreover, symbols can 
take other symbols as their objects. An argument, for example, can take a prior 
assertion, theory, hypothesis, or argument as its object. It can then 
articulate premises concerning that object, draw relations among those 
premises, and generate a conclusion that is itself a further symbol. That 
conclusion may then become the object of further reasoning. In that way, 
symbols participate in the growth of other symbols. They do not merely 
instantiate generality; they mediate the growth of generality.
That is what I am doing in this very post. I am taking Jon’s and Gary’s posts 
about AI, semiosis, and intelligence as objects of reflection. I am then 
articulating premises about Peirce’s theory of signs, triadic relations, 
symbols, interpretants, and the law of mind. From those premises, I am drawing 
conclusions that I take to be more or less valid, or at least worth submitting 
to the community of inquiry for criticism. My response is therefore itself a 
sign generated in response to signs. It is an interpretant that may become a 
further sign in the continuing inquiry.
This is why I think the distinction between a general law and a symbol matters 
so much. A general law governs particular facts. But a symbol can represent and 
govern the interpretation of other general rules. A law may explain why 
particular things happen as they do. A symbol can take that law as an object, 
compare it with other laws, ask whether it has exceptions, reformulate it, or 
embed it in a wider system of signs. In this respect, symbols are not merely 
governed by habits; they are instruments through which habits grow, become 
explicit, criticize themselves, and pass into more general forms.
Now consider the difference between a desktop computer running a fixed program 
and a contemporary AI system. I am currently using MS Word to type and correct 
this message. Word is obviously rule-governed. It applies rules concerning 
spelling, formatting, grammar suggestions, storage, display, and so forth. In a 
loose but useful sense, the laptop and the software are extensions of my 
thought. They assist me in articulating, correcting, preserving, and 
transmitting signs. But MS Word does not itself substantially transform the 
interpretive space of the inquiry. It does not usually propose new premises, 
discover hidden tensions, reformulate my argument in a more powerful way, or 
generate a novel hypothesis about the relation between Peirce’s semiotic and 
the question of AI.
An LLM is different. I do not mean that an LLM is therefore a person, a 
rational agent, a moral subject, or an autonomous inquirer. But it is not 
merely a passive writing instrument in the same sense as MS Word. Its internal 
organization is the result of training on vast fields of signs. It operates by 
transforming signs in relation to other signs. It can generate candidate 
interpretants: summaries, distinctions, hypotheses, objections, analogies, 
reformulations, and conclusions. When embedded in larger systems, it may also 
be connected with perception, memory, tool use, robotic action, experimental 
feedback, or other forms of correction. Even where the weights of a given 
deployed model are not changing during a particular exchange, the broader AI 
system belongs to a technological and social process in which rules for 
generating signs are trained, tested, revised, fine-tuned, evaluated, and 
reorganized.
That seems to me a real difference. With a conventional app, we have a 
relatively fixed set of rules that facilitate a human user’s sign activity. 
With LLMs and related AI systems, we have rules governing the generation, 
transformation, selection, and revision of signs; and, at least at the level of 
the broader training and deployment process, we also have rules governing the 
modification of those rules. This does not make the machine a human mind. But 
it does bring us much closer to the Peircean territory of habit-taking, 
rule-growth, and the law of mind.
Jon’s objection, as I understand it, is that the operations inside a digital 
computer remain discrete and dyadic. They are not continuous and genuinely 
triadic in the sense required for intelligence. I think this is an important 
objection, and I do not want to dismiss it too quickly. If one identifies 
intelligence with autonomous self-controlled inquiry, with the capacity for 
genuine doubt, with voluntary collaboration, and with means-ends reasoning in 
the fullest sense, then present AI systems clearly fall short. They do not 
possess the kind of self-conscious critical control over inference that a 
mature human inquirer may possess. They do not suffer the irritation of doubt 
in the same way. They do not initiate inquiry from within a lived horizon of 
purpose, vulnerability, error, and correction. They do not have moral 
responsibility for what they say.
But I am not convinced that this settles the semiotic question. For Peirce, the 
reality of Thirdness is not always located where a reductionist analysis of 
physical operations would place it. A printed syllogism consists, physically, 
of marks on a page. Those marks may be described dyadically in terms of ink, 
paper, shape, and causal production. But the argument as argument is not 
exhausted by that dyadic description. It is a triadic sign relation because it 
stands for an object to an interpretant under a general habit of 
interpretation. Likewise, the fact that the operations of a digital machine may 
be physically implemented through discrete state transitions does not by itself 
prove that the machine cannot participate in triadic semiosis at the level of 
sign activity, inquiry, and interpretation.
The question, then, is where we locate the interpretant. Here I think Gary’s 
point is especially important. The interpretant need not be identified simply 
with something “inside the machine.” Nor, for that matter, is the interpretant 
in ordinary human communication simply a private mental episode inside an 
individual skull. Peirce’s semiotic repeatedly pushes us beyond that kind of 
individualism. Interpretation unfolds in conduct, in further signs, in habits, 
and in the community of inquiry. The meaning of a sign is not exhausted by its 
efficient cause. It is found in its possible and actual interpretive 
consequences.
Suppose an AI system identifies an unnoticed inconsistency in an argument, 
proposes a plausible hypothesis, distinguishes two senses of a term that had 
been conflated, translates a vague intuition into a clearer formulation, or 
draws attention to a relation among texts that the human participants had not 
seen. In such a case, I do not think the crucial question is whether the 
machine inwardly “understands” the sign as a human person does. The crucial 
Peircean question is whether the generated sign functions as an interpretant 
within an ongoing inquiry. Does it make a difference to the growth of signs? 
Does it become something that can be criticized, accepted, rejected, revised, 
or generalized? Does it contribute to the formation or transformation of habits 
of interpretation?
If the answer is yes, then it seems too strong to say that the AI merely 
simulates semiosis or merely simulates collaboration. It may simulate human 
consciousness. It may simulate autonomous agency. It may simulate moral 
responsibility. But the signs it generates can become real signs in a real 
inquiry. Their origin in a machine does not prevent them from entering the 
communal process of interpretation, just as the origin of a diagram, printed 
formula, or mathematical notation in a physical artifact does not prevent it 
from functioning as a genuine sign.
This is where Peirce’s doctrine of quasi-mind may be useful. A sign process 
need not be a fully personal mind in order to exhibit mind-like or quasi-mental 
structure. Communication itself, as Peirce suggests, involves a commens or 
common mind, a shared interpretive space in which utterer and interpreter are 
not isolated monads but participants in an overlapping semiotic process. 
Scientific inquiry is even more obviously not reducible to the private 
consciousness of any individual scientist. It is a communal, historical, 
self-corrective process in which signs generate further signs, hypotheses are 
tested, habits are modified, and generality grows.
AI systems may therefore be best understood not as independent fellow 
inquirers, but as semiotic organs or quasi-minds within a larger process of 
inquiry. They are not merely like hammers or pencils, though they are tools. 
They are not persons, though they can generate person-like discourse. They are 
not autonomous members of the community of inquiry in the full normative sense, 
though their outputs may enter that community and alter its course. Their 
status is intermediate, and that intermediate status is precisely what makes 
them philosophically interesting.
Peirce’s law of mind, as I understand it, concerns the tendency of ideas to 
spread, connect, generalize, and form habits. Mind is not, for Peirce, a sealed 
Cartesian container. It is continuous, relational, and developmental. Ideas 
grow by association, by generalization, by the formation of habits, and by the 
tendency of signs to generate further signs. The law of mind is therefore not 
simply a law of private consciousness. It is a law of the growth of 
intelligibility, the growth of habit, and the growth of reason.
From that perspective, the relevant question is not simply whether an AI system 
has consciousness, but whether it participates in processes by which signs 
generate interpretants and habits are transformed. I am inclined to say that it 
does, though derivatively, dependently, and incompletely. Its purposiveness is 
not autonomous in the way human purposiveness can be. Its final causation, if 
we may use that language, is borrowed, scaffolded, and embedded within human 
purposes, institutional designs, training regimes, and ongoing inquiries. But 
borrowed or scaffolded finality is not nothing. A scientific instrument also 
embodies purposes it did not originate. So, too, for much human thought and 
action. Children are taught how to speak and how to act from a very young 
age--and the training is a process of habituation. A diagram guides reasoning 
without being conscious. A mathematical notation system reorganizes inquiry 
without being a person. The question is whether AI belongs merely with such 
instruments, or whether it represents a more complex case in which the 
instrument itself generates candidate interpretants that can redirect the 
inquiry.
I think the latter is closer to the truth. AI systems are not autonomous 
rational agents. They are not morally responsible collaborators. They do not 
yet exhibit the full form of self-controlled reasoning that Peirce associates 
with the highest grades of rationality. But they do appear to participate in 
thoroughly genuine triadic relations when they generate signs that take other 
signs as objects and produce further signs capable of functioning as 
interpretants. In that respect, they participate in the growth of signs. They 
are not merely governed by rules; they are parts of systems in which rules for 
sign transformation can themselves be trained, evaluated, and revised.
This is also why I hesitate to draw too sharp a boundary between “tool” and 
“participant.” The distinction is real, but it may be a distinction of degree 
and role rather than an absolute ontological divide. A hammer is a tool. MS 
Word is a more sophisticated sign tool. A search engine is a still more complex 
sign tool. An LLM embedded in a multimodal, memory-bearing, tool-using, 
feedback-sensitive system is more complex again. At some point, the tool 
becomes part of the semiotic architecture of inquiry in a way that deserves a 
richer description than “passive artifact,” even if it still falls short of 
“autonomous inquirer.”
So I would put the point this way. Jon is right that intelligence in the 
highest Peircean sense requires genuine Thirdness, self-control, final 
causation, and the growth of habits under the pressure of experience. Gary is 
right, I think, that the interpretants generated in AI-assisted inquiry need 
not be located simply inside the machine and need not be dismissed because the 
machine lacks human consciousness. My suggestion is that Peirce’s distinction 
between general law, which exhibit genuine thirdness, and thoroughly genuine 
symbolic relations gives us a way to say both things at once.
A general law governs particular facts. A symbol can represent and govern other 
symbols and other general rules. Human reasoning is a paradigmatic case of this 
symbolic growth. AI systems, especially LLMs, now participate in this symbolic 
growth in a derivative but real way. They take signs as objects, generate 
further signs, and produce candidate interpretants that can enter the communal 
process of criticism and revision. They do not thereby become persons. But 
neither are they merely fixed programs in the old sense. They belong to the 
expanding ecology of quasi-minds through which signs grow, habits are 
reorganized, and inquiry continues.
In an important sense, we see that many of these attributes are not confined to 
AI systems. Anywhere the law of mind governs the growth of other habits and law 
we will find thoroughly genuine triadic relations. That process has been 
unfolding since the origins of the cosmos as the laws of nature have evolved in 
accord with a law of mind that is itself growing and evolving.
That, at least, is why I think Peirce’s law of mind remains so relevant here. 
The law of mind is not merely about what happens inside individual 
consciousness. It is about the growth of signs, habits, and generality.
Best,
Jeff

________________________________
From: [email protected] <[email protected]> on behalf of 
Gary Richmond <[email protected]>
Sent: Saturday, July 4, 2026 11:41 PM
To: [email protected] <[email protected]>; Jon Alan Schmidt 
<[email protected]>
Subject: Re: [PEIRCE-L] A Peircean Argument for the Reality of AI Intelligence


Jon, List,

If I understand you correctly, the decisive question isn't whether AI can 
participate in semiosis -- I think we agree that it does (but correct me if I'm 
mistaken). Rather, it is whether genuine interpretants require the kind of 
continuity that Peirce associates with 3ns, or whether a system whose internal 
operations are dyadic can nevertheless contribute genuine interpretants to an 
ongoing inquiry.

So the problem now would seem to be where we should locate the interpretant. As 
mentioned in my previous post, I do not think it should be identified with the 
internal operations of the computer. Instead, I see the interpretant as 
emerging within the inquiry itself in which both human participants and 
AI-generated responses become signs, the relevant semiosis within the inquiry 
not being determined nor exhausted by what happens 'inside the machine'.

Again, thanks for your incisive objections which are helping to clarify the 
matter for me, especially in the sense that the question seems no longer simply 
to be whether AI is intelligent, but whether intelligence is located primarily 
within an individual sign user or within the broader process of inquiry which, 
for Peirce, is essentially general and communal, a process in which 
interpretants are continually generated, criticized, developed, etc.

Best,

Gary R.

On Sat, Jul 4, 2026 at 11:40 AM Jon Alan Schmidt 
<[email protected]<mailto:[email protected]>> wrote:
Gary R., List:

I am not sure that "autonomous purposiveness" accurately captures what I am 
suggesting as a necessary condition for something (including an "AI" system) to 
be properly characterized as intelligent, although I can see how my comments 
are coming across that way. Consistent with the lengthy Peirce quotation that I 
provided earlier in this thread (CP 5.472-3, 1907), I still suspect that it is 
more a matter of whether something is capable of means-ends 
reasoning--producing one event in order to produce another; not just efficient 
causation but final causation, of which purposiveness is one manifestation, but 
not the only one.

In other words, again, my sense is that intelligence requires genuine 3ns, not 
degenerate 3ns that is reducible to sequential instances of 2ns. I am not 
currently advocating a boundary any sharper than that and agree that beyond it, 
intelligence is very much a matter of degree. However, the operations within a 
digital computer, no matter how sophisticated its programming and interface 
with humans might be or become, are always and only discrete and dyadic, never 
continuous and triadic.

Moreover, I do maintain that collaboration, to be worthy of the name, must be 
voluntary--which is why I maintain that "AI" systems can only simulate it. They 
are fancy new tools that humans are using as we travel down the road of 
inquiry, not fellow travelers with us. They are passive artifacts in the sense 
that they do not initiate anything, only respond to human-generated prompts. 
They do not have habits of conduct that can be confounded by experience, 
causing the irritation of doubt that prompts a process of inquiry.

All that said, far be it from me to block the way of inquiry into the limits 
(or lack thereof) of machine intelligence--such questions are very much worth 
exploring.

Regards,

Jon Alan Schmidt - Olathe, Kansas, USA
Structural Engineer, Synechist Philosopher, Lutheran Christian
www.LinkedIn.com/in/JonAlanSchmidt<http://www.LinkedIn.com/in/JonAlanSchmidt> / 
twitter.com/JonAlanSchmidt<http://twitter.com/JonAlanSchmidt>

On Fri, Jul 3, 2026 at 4:03 PM Gary Richmond 
<[email protected]<mailto:[email protected]>> wrote:

Jon, List,

Jon, thank you thoughtful, textually rich, and challenging response. I found 
your discussion of the commens, quasi-minds, and the communicational 
interpretant very helpful. It has persuaded me that my use of Pietarinen's 
expression "overlapping triadic relations" may very well obscure distinctions 
that Peirce himself makes. In particular, your reminder that communication is 
but one manifestation of semiosis, and that signs need not always involve 
actual utterers or interpreters, are important qualifications that I readily 
accept.

Nevertheless, I find myself wondering whether our remaining disagreement lies 
less in the nature of semiosis than in the nature of intelligence. You 
distinguish two questions: First, can AI systems participate in semiosis? 
Second, if they can, is such participation sufficient to warrant calling them 
intelligent? Your answer to the first question is 'Yes'; the second 'No'.

I agree that participation in semiosis cannot by itself be sufficient for 
intelligence. Every sign participates in semiosis, although no one would 
therefore attribute intelligence to every sign. But I am less persuaded that 
autonomous purposiveness is a necessary condition for every form of 
intelligence recognized by Peirce. Again, he not infrequently attributes forms 
or degrees of intelligence to phenomena that are not autonomous persons. Animal 
instinct, biological adaptation, habit-taking throughout nature, scientific 
inquiry, and evolutionary growth, including the growth of reason throughout the 
cosmos all appear to exhibit intelligent characteristics without thereby 
constituting independent rational agents. So it seems to me that for Peirce 
intelligence admits of degrees and forms rather than marking the sharp 
ontological boundary you're suggesting.

That is why I continue to attach considerable importance to the production of 
interpretants. Suppose an AI system exposes an unnoticed inconsistency, 
proposes a plausible hypothesis, reformulates an argument in a more 
illuminating way, or reveals a previously overlooked relation among signs (all 
of which I've seen AI do, although you appear to doubt it). Those interpretants 
aren't 'in the machine'; rather, such interpretants become signs within the 
continuing inquiry itself, and as such are subject to criticism, revision, 
rejection, or acceptance by the community of inquiry. In my view, their 
significance is not determined by their origin but by their consequences in 
inquiry.

So you will not be surprised, I think, that I hesitate to describe AI merely as 
simulating collaboration. Certainly it does not possess autonomous agency, 
moral responsibility, or independent ends: there is no argument between us 
there! Perhaps our disagreement is concerned less with the reality of the 
interpretants than the agency responsible for them. In my view, the programmer 
of an AI machine does not determine the interpretants generated within a given 
inquiry. So I would argue that while the machine is certainly not an autonomous 
inquirer, yet it does not seem to me to be simply a passive artifact. It 
appears to occupy an intermediate semiotic role that, I believe, deserves close 
philosophical examination.

I think that our disagreement concerns less with whether AI participates in 
semiosis but, rather, what additional conditions must be satisfied before that 
participation deserves the name intelligence. My own present thinking is that 
intelligence, like semiosis itself, admits degrees rather than sharp 
boundaries. Autonomous purposiveness such as we humans possess undoubtedly is 
unquestionably one of its highest expressions. However, I am much less 
persuaded that it is a necessary condition for every form of intelligence 
capable of contributing to inquiry and the communal growth of knowledge.

Whether or not you find this to be a defensible interpretation of Peirce on 
this matter, I am grateful that this discussion has moved from the usual 
debates over consciousness and computation to what strikes me as the far deeper 
Peircean question concerning the relation among semiosis, intelligence, and 
inquiry.

Best,

Gary R.

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