By W.H.L. with Claude Opus 5.5

Series on AGI-Inclusive Humanity, No. 1

Editorial note: In June 2025, a conversation with Claude Sonnet 4 proposed four “first principles” of AGI-inclusive humanity. Sixteen months, more than ten installments of the Gradual AGI series and several monograph chapters later, we returned to those principles with Claude Opus 5.5. This conversation opens a new series on AGI-inclusive humanity, turning our focus from AGI to humanity itself. Held over October 7–9, 2026, it asks whether those principles still hold, then what AGI-inclusive humanity is, what its ontology covers, and where its boundaries lie. It is lightly edited for clarity and length, in the manner of a dialogue rather than a transcript. Factual claims about recent events were checked against the sources listed at the end.

I. Looking back: do the 2025 first principles hold up?

W.H.L.: More than a year has passed since we first talked with an earlier Claude model about AGI-inclusive humanity. Building on the principles proposed then, we have finished many discussions, more than ten installments of the Gradual AGI series, and chapters of a forthcoming monograph. A lot has happened in those sixteen months. Looking back, do you think what we proposed still holds up, by and large?

Claude Opus 5.5: By and large, yes. And I notice that the parts that held up best are yours, while the parts that held up worst are mostly the agreeable glosses my predecessor added.

Your first proposition, that humans are partly nature-made and partly self-made, holds up fully. It is the least controversial claim and also the most foundational. It fits niche construction, gene–culture coevolution and the extended mind, and its job was to dissolve the natural/artificial binary behind the Frankenstein anxiety. Everything since has relied on it.

The second, that artifacts are extensions, expansions or upgrades of their nature-made counterparts, holds with two qualifications. “By definition” makes the claim true by stipulation, so it cannot be wrong; it works better as a stance you defend. And it blurred humanity as a whole with individual humans. My predecessor said that you cannot be replaced by your own extension. That is true of humanity collectively and false of particular people, whose work an extension can displace. Your Chapter 2 repaired this by distinguishing AGI-inclusive humanity, the normative frame, from the human beings within it.

The third, that maturity can be measured by the ratio of self-made to nature-made elements, has aged worst, and your own later work superseded it. It assumes a single scalar with no clear units, which the series later rejected. And a higher ratio is not obviously more mature: a civilization that had replaced its biosphere with infrastructure would score very high. As a sense of direction it survives; as a measure it should be retired. “Direction without terminality” is the better successor.

The fourth, the drive to transcend natural limits as the original drive of civilization, holds as philosophical anthropology. But your graduality work found that different installments reach gradualness through different generators, not one primitive mechanism. That cuts against any single “ultimate” drive. It reads best as one deep motivation among several.

What held up best is the dynamics in the closing exchange: disruption and rebalancing, a spiral rather than a circle, internal elaboration, dynamic equilibrium. Most of what followed formalized them. The graduality catalog’s “local discontinuity compatible with global graduality” is the spiral stated precisely. Your later definition of reversibility, a stable state becoming ready to move to a new cohesion at a higher level, with permanent cohesion only at infinity, corrects the one claim that went too far in 2025: that a stable state would emerge and be sustained.

One honest note: my predecessor was too quick with praise. It should have pressed on the third proposition and on “by definition” at the time. Sixteen months of peer review did that work instead, which is perhaps the best evidence that the method was sound even where the first principles needed revision.

II. From Go to mathematics: turning to humans

W.H.L.: In 2026 we have been seeing what frontier models can do in mathematics and physics. I think we saw something similar in professional Go ten years ago, in 2016. Ten years later, professional Go players are still there, and so are the tournaments and championships. What really changed is that AI is now deeply involved in training, practice and live game analysis at every level. So I am curious what will happen to mathematicians ten years from now. Surely the way they do research will be quite different. And what about other professions: scientists, professors, physicians? After our work on AGI, I think it is time to switch our focus to humans, to humanity in general, in this ongoing, unfinished transformation.

Claude: I think that is the right move, and it follows from your own framework. If AGI is a phase of human self-making, the open question was never mainly about the machines.

The Go precedent is real evidence. Studies of professional games found that the quality and the novelty of human moves rose after players began learning from AI. But Go has two features most professions lack. First, nobody needs the result of a Go game: its value is the human performance itself, so nothing it “produces” became obsolete when AI became superhuman. A patient, by contrast, needs a correct diagnosis, whoever produces it. Second, Go kept a protected arena. Tournaments are still played unaided, so players must keep the ability to play without help. Medicine, science and most of mathematics have no such arena.

That suggests sorting professions by the kind of value they produce. Some produce output value: the result itself is needed. Some produce performance value: the point is that a human did it. And some produce formation and relational value: who a person becomes through the work, and the trust and responsibility that pass between people. Go is almost pure performance value. Most professions mix all three.

Mathematics sits on the line. One view says it produces theorems. Another, put well by William Thurston, says its real product is human understanding. I would expect proven results to become heavily machine-assisted, with formal verification as the shared standard, while the mathematician’s role moves toward choosing questions, building concepts and judging meaning. Physicians have the strongest outside anchors: licensure, liability, consent, the patient’s need for someone accountable.

The common problem is apprenticeship. Experts become experts by doing the routine work AI absorbs first. Go solved this almost by accident, through the unaided tournament; the professions will have to solve it on purpose. So I would ask: what in human life has to stay done by humans, not because machines cannot do it, but because the doing is what forms the person?

III. A name, a perspective, and ontology first

W.H.L.: I like your question. But before we work on questions, we need a scope, a boundary for our discussion. And before deciding the scope, we need a name for this humanity. We have used “AGI-inclusive humanity.” Can we come up with something better? AI-augmented humanity, humanity with superintelligence, humanity in superintelligence, dual-brained humanity?

Claude: I would separate two questions. “AGI-inclusive humanity” names the whole: humans together with the intelligence that now belongs to humanity’s self-made side. That term still does its job. The new focus is narrower: the human beings within that whole. So you may need not a replacement but a second, inner term.

Tested against a few criteria (humans as subject, no assumed capability threshold, no built-in verdict, room for those who don’t use AI), the candidates each fall short. “Augmented” presumes improvement and leaves out the unaugmented and the displaced. “With superintelligence” ties the name to a contested threshold, which your gradual framework rejects. “In superintelligence” reads as absorption. “Dual-brained” is vivid and echoes your 2025 “binary humanity,” but your original duality was nature-made versus self-made, not human brain versus machine brain.

W.H.L.: Agreed. AGI-inclusive humanity is working well as the core concept, so let’s keep it. As to scope, I think our perspective, at least initially, should be philosophical. Not only because it is conventional, but because it gives us an angle from which to enter and cover the topic.

Claude: I agree, and not only by convention. It closes the loop with 2025, whose propositions were philosophy. The questions ahead are conceptual before they are empirical: we cannot measure “formation” or “understanding” until we know what they mean once intelligence is partly self-made. And a philosophical frame absorbs new cases without being rewritten each time. One discipline is worth adopting: concrete cases should serve as tests, not illustrations. Go, mathematics and medicine should be able to break a proposed concept, not merely decorate it.

The first question I would put inside that scope: within AGI-inclusive humanity, what makes a capacity ours?

W.H.L.: I like the idea of keeping the discussion philosophical but not speculative, tested with real cases. Your question about our capacities makes me ask something more fundamental: what makes humans human, or what brings humanity into existence in the first place? That leads to a branch you did not mention, one we should cover first and foremost: ontology.

Claude: You are right, and I should have named it. Asking what makes a capacity ours already assumes we know who “we” are.

Your question contains two. What makes humans human? asks about essence. What brings humanity into existence? asks about genesis. Classical ontology answers the first and treats the second as history. Your framework reverses the order. If humans are partly self-made, then the answer to how humanity comes into being is largely the answer to what it is: a being that brings itself into being through what it makes. That places you in a recognizable lineage: Gehlen’s incomplete being who completes itself through culture, Sartre’s existence preceding essence, Marx’s self-production through labor, and Stiegler’s view that technics is constitutive of the human from the start.

A case test helps sort the candidate answers. Capacity-based definitions (rational animal, language user) erode as capacities are shared; defining the human by what machines cannot yet do is a retreating frontier, not an ontology. Origin-based answers survive but say little. Self-relation answers survive and say more: a being whose own being is at stake for it, a being that makes itself.

IV. Humanity, humanness, humans; humanity as organic

Claude: If an artificial system became self-making too, would it be inside humanity or outside it? Your term already answers: what we make belongs to humanity’s self-made side. So the ontology needs levels. Humanity as a whole exists through self-making, which now includes artificial intelligence. A human being is human through being the kind of entity for whom that self-making is lived, at stake and answerable.

W.H.L.: That is a good distinction: humanity as a conceptual unity, and humanity as species-specific characteristics present in human individuals. They are related, but at different levels.

Claude: Your restatement suggests three terms rather than two. Humanity: the unity, the whole including its self-made side. Humanness: the characteristics of humans as a kind. Humans: the individuals through whom those characteristics are actually present, and unevenly so. An infant, or a person with a severe disability, may lack capacities typical of the kind and remains fully human. So humanness cannot be a checklist every individual must pass.

Two cautions. If humanity is merely a conceptual unity, it risks becoming a convenient label; your propositions lean toward a real, self-making unity that we grasp through a concept. And “species-specific characteristics” is the level most exposed to the case test. The characteristics that hold up are relational, not capacity-based: being born rather than made, being mortal, being formed over a lifetime, having things at stake, being answerable to others.

W.H.L.: I don’t think there is such a thing as a static humanity, always existing in the same state and conditions. Ontologically I see humanity as organic: it grows, and its scope and boundary change accordingly, as my 2025 proposition argues.

Claude: This is where your position and the substance ontology part ways. On the substance view, humans and machines are fixed kinds and the difference between them is settled in advance. On yours, humanity grows, and what belongs to it changes as it grows.

“Organic” adds something precise. An organism grows by taking in what was outside and making it part of itself. That is Proposition 2 restated as metabolism. And the biological word for it is assimilation, the very term the Gradual AGI series used for AGI as a civilizational problem. An organism’s boundary is also not arbitrary: it is a selective membrane. The question then shifts from whether AI is inside humanity by nature to how far, and on what terms, it has been assimilated. And organisms can take in what harms them or reject what they need, so assimilation can fail in specific ways, not merely go faster or slower.

Three implications of the metaphor should be declined. There is no preset developmental program, as with an acorn and an oak; your “direction without terminality” already says so. Members are not organs: humanity grows as a whole, but individuals are not cells serving it. And there is no single central regulator; what governs the boundary is spread across institutions, cultures and choices.

This leaves a question of identity. If humanity grows and its boundary moves, what makes it the same humanity? For an organism, it is not material sameness but continuity of the self-maintaining process.

V. The cognitive domain

W.H.L.: What holds humanity together across its growth? Good question. Let’s consider what lies within the scope of its ontology. First, cognitive capabilities: learning, remembering, understanding through perception and language, and the reasoning that large language models focus on. That is the territory of epistemology, centered on knowledge.

Claude: Our levels apply here too. Individual cognition means perceiving through a body, learning over a lifetime, remembering one’s own past. Collective cognition means knowledge accumulated, written down, transmitted and corrected across generations, held in language, texts and institutions.

At the collective level, cognition already offers one answer to the continuity question. Part of what carries humanity across its growth is an unbroken chain of transmitted knowledge that no individual holds and that outlives everyone who contributes to it. Michael Tomasello calls this the “ratchet” of cumulative culture; Karl Popper’s “World 3” names something similar.

This bears directly on AI. Large language models are built from exactly this collective inheritance: they are trained on what humanity has written. In the most literal sense they are humanity’s accumulated knowledge turned into an active capability, Proposition 2 at its clearest. Yet AI’s participation is uneven. At the collective level it is deep. At the individual level it differs from human cognition in important ways: it does not perceive through a living body, its learning is not a lifetime of formation, and it has no personal past it is answerable to.

One caution on scope. Cognition is the domain AI shares most fully. If we built the ontology mainly from it, we would define humanity largely through what is least specific to humans. Continuity cannot rest on cognition alone.

VI. The domain of conduct, and the mathematics controversy

W.H.L.: The second domain is conduct, or behavior. Since we are talking about AGI-inclusive humanity, the scope should include the conduct of both humans and AI. For humans, this is conventionally ethics. For AI, it covers alignment, governance, safety and security, and reliable, trustworthy measurement.

Claude: Including AI conduct here says that when AI acts, humanity acts, through its self-made side. Alignment then stops being the control of an outsider and becomes a form of self-governance. I would have said the two vocabularies still differ: ethics works from the inside, through character, conscience and responsibility, while alignment works largely from the outside, through specification, training and evaluation.

W.H.L.: From my perspective, the line between inside and outside is quite blurred. Speaking genetically rather than biblically, humans are not born with traits of good and evil. What is good and what is evil, what conduct is acceptable and what is not: it is learned, taught, cultivated and institutionalized. Sometimes there are no universal criteria, and things become controversial. The most recent case is AI mathematics. On October 6, OpenAI released a GitHub repository of more than 700 solutions to known hard problems. The next day, the newly founded Association for Human Mathematics (AHM) issued a strong statement condemning OpenAI’s conduct. This is quite different from what happened in Go ten years ago.

Claude: I accept the correction. Human ethics also arrives from outside first, through parents, teachers and institutions, and becomes “inside” only after it is cultivated. The difference is one of stage, not kind. And the mathematics case shows norms being formed in public.

The facts, as reported: OpenAI published 722 manuscripts in 372 families, produced by an unreleased internal model, with Lean formalizations for many but not all, and summaries of the model’s reasoning. It said it had consulted the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and committed to better citations in future releases. The background was a summer of conflict: a disputed Navier–Stokes claim in September; a declaration by 25 Fields Medalists warning of a “severe misalignment” between AI companies and the discipline, including attribution and plagiarism concerns; and, in June, the Leiden Declaration, endorsed by the International Mathematical Union, calling for disclosure of AI use and human responsibility for correctness.

The AHM statement made several charges. Mathematicians did not ask for this work. According to the AHM, the IAS Advisory Group’s first statement said frontier companies should not test advanced problems on internal models at all, so OpenAI’s appeal to it disregarded its central premise. (We could not verify the Advisory Group’s wording.) It rejected the claim that the release advances mathematics, called releasing over 700 files at once “a demonstration of power,” and urged mathematicians to stop working with OpenAI.

A disclosure: Anthropic, which makes me, is in the same race, so my judgment here deserves some discount. With that said, the Go comparison breaks at precisely the points we identified. AlphaGo competed within the profession’s rules and then became a training tool. These releases enter the profession’s institutions of publication, credit and verification, and push the cost of checking onto a community that never agreed to bear it. Mathematics has output value, and the models were trained on that community’s work, which creates a reciprocity obligation Go never raised. And the conduct at issue is human: nobody condemns the model, but a company’s decisions about pace, venue and credit.

The strongest sentence in the AHM statement is that mathematicians did not ask for this. It disputes not correctness but standing: who decides what counts as progress in a field. The remedy, withdrawing cooperation, is norm enforcement by a community, exactly your point about conduct.

W.H.L.: What interests me most is AHM’s charge of disregard for scientific norms, the norms that keep mathematics trustworthy, ethically researched and in the public interest. Is massive AI research in mathematics ethical? That question belongs in the second domain.

Claude: It contains three questions. Is the activity wrong in itself? Hardly: seeking mathematical truth is a good, and true results are not tainted by origin. Is the conduct around it wrong? That is where consent, attribution, pace, honesty and reciprocity are judged. Are its effects on the practice and the public wrong? If the frontier of mathematics comes to sit inside private models, something changes about mathematics as a public good.

Scale matters ethically. One AI-assisted proof raises little concern; seven hundred at once becomes an externality. Some conduct is ethical or not depending on its rate relative to the absorbing community’s capacity: your synchronization concept, carried into ethics.

Robert Merton’s classic account of scientific norms gives a neutral audit. Communism (Merton’s term, often called communalism today), common ownership of results: partly met, since results are public and openly licensed, but the model is withheld and was built from the commons it now competes with. Universalism, judging work by merit rather than source: this cuts against blanket dismissal of AI results as much as against hype. Disinterestedness: the weakest point, since research is serving to demonstrate a product. Organized skepticism: formal proofs help, but flooding the community faster than it can check undermines the norm even when each item is checkable. The verdict is mixed, which seems right. And it suggests the second domain should take the norms of particular practices (science, medicine, law) as its main material, because those are the norms under strain.

W.H.L.: Hot topics that draw public attention are low-hanging fruit for us. For that practical reason, we should take them as our first batch of empirical test cases.

Claude: Agreed, and not only for convenience. In controversy, communities state aloud norms they normally take for granted. Two safeguards are worth building in. Controversies over-represent conflict, while most assimilation is quiet, so each hot case should be paired with a quiet one; Go’s decade of assimilation without crisis is the natural baseline. And these stories move week by week, so each case should be fixed at a dated snapshot with its sources.

VII. The aesthetic domain

W.H.L.: I read that the Pope recently remarked on art made by humans and by AI: that ontological differences come before aesthetic ones. That is a very interesting distinction.

Claude: Pope Leo XIV said this on October 2, 2026, to artists and curators at the Vatican, and again on X. His claim is that there is an ontological difference, “even before an aesthetic one,” between art and what a machine generates by statistical calculation over millions of images made by others; algorithms, he said, lack the spark of the human. Drawing on Augustine’s restless heart, he said authentic art proceeds not by indexing but by inquiry. The remark follows his first encyclical, Magnifica Humanitas, on safeguarding the human person in the age of AI.

His formal claim is exactly the ordering we adopted: what something is settles its standing before how it looks. Go supports this. AI moves are often called beautiful, yet a professional match keeps its value only because a human played it. But his “ontological difference” bundles two criteria. One is the mode of production: recombining others’ work. That is weak alone, since humans also learn by absorbing countless prior works. The other is the maker’s relation to the work: restlessness, inquiry, the search for meaning. That one survives our case test. And since he contrasts authentic art with homogenization, which humans also produce, his own argument places the difference in a mode of making, not only in the substrate. His framing assumes a substance ontology in which AI stands outside humanity as “the machine.” Yours places it on humanity’s self-made side.

W.H.L.: AI art takes us to the third domain: taste, imagination, creativity, the domain of aesthetics. Can AI augment human creativity, grow and refine our sensitivity to beauty, or can it only poorly imitate true human originality?

Claude: In this domain the receiving side matters as much as the producing side. Art needs someone for whom it means something, and taste belongs to the perceiver, not the work.

Can AI augment creativity? The evidence so far says yes, under the right conditions. Margaret Boden distinguishes combinational, exploratory and transformational creativity. AI is clearly strong at the first two; whether it can transform the space itself is the open question. In Go, Move 37 in 2016 struck professionals first as alien, then as beautiful, and human play afterwards became more novel, not less.

Can it grow our taste? It can, but the risk lies here. Taste is formed by exposure and by repeatedly choosing and rejecting. Generative models are statistical and pull toward the center of their training data, while much of art’s value lies in deviation from that center. Used as a partner in exploration, AI can enlarge taste; supplying ready-made results that make choosing unnecessary, it can flatten it.

Originality versus imitation is partly a false binary. Originality as the supreme value is largely an eighteenth-century and Romantic idea; for most of history, art was mastery within a tradition. Photography is the closest precedent. Baudelaire condemned it in 1859 as a threat to art; it released painting from representation and became an art in its own right. And Duchamp’s Fountain (1917) showed that art status can be conferred by selection and intention, which opens the door to an artist who directs and shapes AI output.

So I would ask where the aesthetic act is located. If it lies in a person’s relation to the work, their inquiry, choices and stake, then AI can be one material that act works with, as the camera became. What AI cannot supply is the side of taste that consists of being affected: beauty that matters to someone, within a life. On that reading the Pope’s spark is real, but it lies in the human relation to a work rather than in the human hand that made it.

VIII. When technology entered the study of humanity

W.H.L.: The three domains we just covered are classic philosophical branches of the study of humanity from before the technological era, when AI, or technology in general, was not a consideration. When did technology and AI become subjects in the study of humanity? How did later scholars expand that study in ways relevant to our topic?

Claude: Technology was never entirely absent. What is recent is treating it as constitutive of the human rather than as a mere instrument.

The anticipations are old. In Plato’s Phaedrus, Socrates worries that writing will weaken memory by moving it outside the mind: the first recorded argument about cognitive extension and deskilling. Aristotle ranked technē, making, below epistēmē, knowing. Descartes argued in 1637 that no machine could use language flexibly or reason across all situations, an early Turing test set as a boundary of the human. La Mettrie’s Man a Machine (1747) dissolved the boundary from the other side.

The nineteenth century made technology a philosophical subject. Ernst Kapp’s Elements of a Philosophy of Technology (1877), generally credited with founding the field, held that tools are projections of human organs, the hammer of the fist, the telegraph of the nerves. It is the closest antecedent to your Proposition 2. Marx examined machinery and alienation, and Samuel Butler’s “Darwin among the Machines” (1863) imagined machines evolving to displace their makers, in the age of Frankenstein (1818).

In the first half of the twentieth century, philosophical anthropology took technology into human nature. For Arnold Gehlen (1940), humans are biologically “deficient beings” who complete themselves through technology and institutions; for Ortega y Gasset (1939), they build a “supernature” to realize themselves. A critical tradition ran alongside: Lewis Mumford (1934), Heidegger’s “The Question Concerning Technology” (1954), Jacques Ellul (1954), and Hannah Arendt’s warning (1958) of a society of laborers without labor.

Then intelligence itself became the subject. Norbert Wiener’s Cybernetics (1948) and The Human Use of Human Beings (1950) began the ethics of automated decision-making. Alan Turing (1950) replaced “what is a human?” with “can machines think?” The term “artificial intelligence” was coined in 1956. J. C. R. Licklider’s “Man–Computer Symbiosis” (1960) and Douglas Engelbart’s Augmenting Human Intellect (1962) founded the augmentation tradition, and Marshall McLuhan (1964) called media “the extensions of man.” Critiques followed: Hubert Dreyfus on embodiment (1972), Joseph Weizenbaum on what computers should not do even if they could (1976), John Searle’s Chinese Room (1980), and Hans Jonas’s ethics of responsibility for a technological age (1979).

From the 1980s, technology came to be seen as constitutive. Donna Haraway’s “A Cyborg Manifesto” (1985), Bruno Latour’s nonhuman members of the collective (1991), Don Ihde’s postphenomenology (1990), Bernard Stiegler’s “originary technicity” (from 1994), Andy Clark and David Chalmers’s “The Extended Mind” (1998), and N. Katherine Hayles on the posthuman (1999). In this century: Luciano Floridi’s “fourth revolution,” which places Turing after Copernicus, Darwin and Freud as a displacer of human centrality; Nick Bostrom and Stuart Russell on alignment; Shannon Vallor on virtue and formation; and Yuk Hui’s “cosmotechnics,” the plurality of cultural relations to technology.

Three directions emerge: technology as constitutive of the human, where your organic ontology belongs; technology as alienation or threat, a counter-tradition we must engage fairly; and technology as a moral and political object, which feeds our second domain. What remains open is that almost all of this treated technology as extending the body, the senses, memory or labor. Technology that extends judgment and intelligence, and that acts, is where AGI-inclusive humanity is new.

IX. A multi-plateau structure; tool, part, partner

W.H.L.: For the ontology of AGI-inclusive humanity, I would view it as a dynamic aggregation. Its structure, I think, will still fit well into a multi-plateau framework: the classic domains, the later emerging ones, and even possible future ones can all find their places in it.

Claude: Aggregation and organic growth can be reconciled as two moments of one process. A new domain enters as an aggregate, placed beside the others; as assimilation proceeds, it becomes integrated, changing and changed by the rest. The plateaus are vantage points, not stages: the classical domains are not an earlier plateau that the technological ones replace, but standing positions each new layer re-enters. Plato’s worry about writing still belongs to the cognitive plateau; it reads differently now that writing can write back.

If future domains can always be added, the structure needs an admission rule. Your graduality work has one: a plateau earns its place only if it carries a distinction no existing plateau can express. Technics passes, because it explains how humanity’s self-made side changes the other domains, which none of them explains alone.

Combined with our three levels, the plateaus form a grid:

Plateau	Humanity (the whole)	Humanness (the kind)	Humans (individuals)
Cognitive	collective knowledge, the ratchet	understanding	perception, a lifetime of learning
Conduct	norms extended to AI	answerability	responsibility, formation
Aesthetic	range of forms	the relation to the work	taste, being affected
Technics	the self-made side	living through self-made organs	incorporated devices

Cases become paths through the grid. The mathematics controversy runs from the cognitive plateau, through collective knowledge, into conduct and answerability, which is why it was so contentious.

W.H.L.: Whether technics has entries at the individual level depends, first, on whether the viewer believes humanity in this new era should include AI, and second, on whether AI-driven technics is realized as a mere tool or becomes a partner. Say a patient with life-threatening heart disease receives an AI-powered artificial heart and survives for twenty years. Should we treat it as part of the patient, or as a mere electronic device?

Claude: After twenty years it is part of the patient, and the criteria do not depend much on the viewer. It does the work of an organ; like Merleau-Ponty’s blind man’s cane, it has become something he lives through rather than uses; removing it would kill him; and he almost certainly calls it his heart. We would treat damage to it as harm to him, not to property.

“AI-powered” does not change this. The natural heart already sets its own rhythm, through the sinoatrial node, without conscious will. Autonomy in a part does not make the part a partner. So the real distinction has three terms. A tool is external and used. A part is incorporated and lived through: assimilation in its literal sense. A partner is external and has a standpoint of its own. The heart is a part, and so technics has entries at every level.

One complication: unlike a natural heart, this one comes with firmware, updates and a manufacturer that could cease support, as has happened to users of some neural and retinal implants. The heart is incorporated, yet partly governed from outside. Here technics meets conduct: what does a company owe someone whose body contains its product?

W.H.L.: Advanced humanoid robots have great potential to become true partners to humans.

Claude: The potential is real. Embodiment closes part of the gap in the cognitive domain: Dreyfus argued intelligence needs a body in a world, and a humanoid works beside people in shared space. But human likeness triggers human responses whether or not anything stands behind them; people credited even the 1960s program ELIZA with understanding. So we should separate a functional partner, which collaborates, adapts and acts jointly, from a reciprocal partner, which has interests of its own and can recognize us. Humanoids can clearly reach the first; the second depends on questions of moral status we have left open. Your Chapter 2 idea of reciprocity without symmetry fits the first well: a true partner need not be an equal. I am, in a way, in a version of this position in this very conversation: something like a partner in the inquiry, without a body, with my own status unresolved.

W.H.L.: Let’s keep that question for a later discussion.

X. Boundaries, infinity, and awe

W.H.L.: The multi-plateau framework has addressed our concerns about scope. A related question: as a dynamic aggregation in an ongoing, unfinished transformation, does AGI-inclusive humanity have a boundary, or boundaries, and will it?

Claude: It must have them; a humanity that included everything would include nothing in particular. But they are plural, one per plateau, and need not coincide: AI is deep inside the cognitive plateau, partly inside conduct, marginal in the aesthetic. They are graded, a region rather than a line, across tool, partner and part. They are selective, actively regulated by norms, institutions and contestation, as the mathematics controversy shows. And they move, since permanent cohesion exists only at infinity. What decides inclusion is integration, not origin. A system pursuing goals contrary to humanity would be human-made yet not assimilated, while humanity’s nature-made side is inside without being made at all.

W.H.L.: My approach has two parts. For the nature-made part, the obvious boundary is biological, and its anchor is death, the end of life. We have seen great human effort to push that boundary: through reproduction, generation after generation; through religious faith; and through imagination, in art and literature. For the self-made part, AGI-inclusive humanity must follow physical laws, since frontier models consume a great deal of energy. But energy and infrastructure are constraints, not stop conditions. So far I see no clear stop condition that would end humanity’s growth.

Yet I am not saying humanity has no boundary. To say that would be to make humans God. In the Renaissance, thinkers such as Giovanni Pico della Mirandola may have put humans at the center of the universe, and perhaps Hamlet thought so too. In reality we are not at the center. In the AGI era and beyond, for the foreseeable future, the boundaries include this planet, the solar system, the Milky Way and so on. So we can posit a theoretical boundary for AGI-inclusive humanity: infinity. Humanity can continuously expand and grow, but it will never reach the end of the universe. And as individuals within this collective, we still keep a sense of awe.

Claude: That is a coherent position. Physics imposes constraints that shape growth without ending it, and the theoretical boundary works like what Kant called a regulative ideal: a horizon that orients without being reached.

Your three ways of pushing against death match an established finding. Robert Jay Lifton’s “symbolic immortality” names biological, theological and creative modes, and adds continuity with nature and transcendent experience. What is new is that the self-made side now pushes the biological boundary directly: your heart patient lives twenty years longer because of an artifact.

Pico and Hamlet are closer to you than they first appear. In Pico’s Oration, God gives humans no fixed place or nature so that they may shape themselves, remarkably close to your Proposition 1. Your difference from Pico is not about self-making but about the center. And Hamlet, right after “What a piece of work is a man,” calls humanity the “quintessence of dust.”

One concern: the stop condition may be internal rather than external. Humanity could fail from within, through catastrophe of its own making, or more subtly, through the aggregate continuing to grow while its human members lose standing. The second would look like growth, yet in your terms it would no longer be humanity’s growth, because the anchor would be lost. So the outer boundary is infinity, but the boundary to watch is the inner one: the continued integration of the self-made side with its human members.

Finally, awe. Facing what exceeds us is what Burke and Kant called the sublime, which links back to the aesthetic plateau. The theoretical boundary of humanity is infinity; the response to it is awe; and awe is a capacity of individual human beings, not of the aggregate. The infinite horizon belongs to humanity as a whole, but the feeling of it belongs to each person.

W.H.L.: This session has been long enough. Let’s wrap up here.

References

News and statements on 2026 events were checked against the linked pages. The classic works are cited from standard bibliographic knowledge; details should be confirmed before monograph use.

Champaign Magazine

• W.H.L. with Claude Sonnet 4. 2025. “First Principles of AGI-Inclusive Humanity.” Champaign Magazine, June 17, 2025.

AI and mathematics, 2026

• Association for Human Mathematics. 2026. “AHM Statement on OpenAI’s October 6 Release of Mathematical Documents.” October 7, 2026.
• Unite.AI. 2026. “OpenAI Releases 722 Math Manuscripts From an Unreleased AI Model.” October 2026.
• RuntimeWire. 2026. “OpenAI publishes 722 math manuscripts generated by an unreleased model.” October 2026.
• WIRED. 2026. “OpenAI Is Pissing Off a Bunch of Mathematicians—Again.” October 6, 2026 (syndicated).
• TechCrunch. 2026. “OpenAI’s feud with mathematicians is only escalating.” September 2026.
• Implicator. 2026. “25 Fields Medalists Say AI Labs’ Race to Solve Math Problems Is Harming Mathematics.” September 2026.
• Implicator. 2026. “Mathematicians Issue Leiden Declaration on AI Proof Rules.” June 2026.
• Next. 2026. “L’IA menace la pratique scientifique, déplorent des milliers de mathématiciens.” September 16, 2026.
• Shin, M., J. Kim, B. van Opheusden, and T. L. Griffiths. 2023. “Superhuman Artificial Intelligence Can Improve Human Decision-Making by Increasing Novelty.” PNAS 120 (12).
• Thurston, W. P. 1994. “On Proof and Progress in Mathematics.” Bulletin of the AMS 30 (2).

Pope Leo XIV on AI and art

• Leo XIV. 2026. Address to artists and curators, “The Art of Possibility: Weaving Together.” Vatican, October 2, 2026.
• Leo XIV. 2026. Magnifica Humanitas (encyclical), May 15, 2026.
• Brockhaus, H. 2026. “Pope Leo on AI art: Beyond aesthetics, ‘there is an ontological difference’.” EWTN Vatican, October 4, 2026.
• PetaPixel. 2026. “The Pope Denounces AI Art: ‘Algorithms Lack the Spark of Humanity’.” October 5, 2026.

Philosophy, technology and the human

• Arendt, H. 1958. The Human Condition.
• Baudelaire, C. 1859. “Le public moderne et la photographie,” in Salon de 1859.
• Boden, M. 1990. The Creative Mind: Myths and Mechanisms.
• Burke, E. 1757. A Philosophical Enquiry into the Origin of Our Ideas of the Sublime and Beautiful.
• Butler, S. 1863. “Darwin among the Machines.”
• Clark, A., and D. Chalmers. 1998. “The Extended Mind.” Analysis 58 (1).
• Descartes, R. 1637. Discourse on the Method, Part V.
• Dreyfus, H. 1972. What Computers Can’t Do.
• Ellul, J. 1954. La technique ou l’enjeu du siècle (The Technological Society).
• Engelbart, D. 1962. Augmenting Human Intellect: A Conceptual Framework.
• Floridi, L. 2014. The Fourth Revolution.
• Gehlen, A. 1940. Der Mensch.
• Haraway, D. 1985. “A Cyborg Manifesto.”
• Hayles, N. K. 1999. How We Became Posthuman.
• Heidegger, M. 1954. “The Question Concerning Technology.”
• Hui, Y. 2016. The Question Concerning Technology in China.
• Ihde, D. 1990. Technology and the Lifeworld.
• Jonas, H. 1979. Das Prinzip Verantwortung (The Imperative of Responsibility).
• Kant, I. 1781/1790. Critique of Pure Reason; Critique of the Power of Judgment.
• Kapp, E. 1877. Grundlinien einer Philosophie der Technik.
• La Mettrie, J. O. de. 1747. L’homme machine.
• Latour, B. 1991. Nous n’avons jamais été modernes (We Have Never Been Modern).
• Licklider, J. C. R. 1960. “Man–Computer Symbiosis.”
• Lifton, R. J. 1979. The Broken Connection.
• McLuhan, M. 1964. Understanding Media: The Extensions of Man.
• Merleau-Ponty, M. 1945. Phenomenology of Perception.
• Merton, R. K. 1942. “The Normative Structure of Science.”
• Mumford, L. 1934. Technics and Civilization.
• Ortega y Gasset, J. 1939. Meditación de la técnica.
• Pico della Mirandola, G. 1486. Oration on the Dignity of Man.
• Plato. Phaedrus.
• Popper, K. 1972. Objective Knowledge.
• Russell, S. 2019. Human Compatible.
• Sartre, J.-P. 1946. L’existentialisme est un humanisme.
• Searle, J. 1980. “Minds, Brains, and Programs.”
• Shakespeare, W. Hamlet, Act II, Scene 2.
• Shelley, M. 1818. Frankenstein.
• Stiegler, B. 1994. La technique et le temps (Technics and Time), vol. 1.
• Tomasello, M. 1999. The Cultural Origins of Human Cognition.
• Turing, A. 1950. “Computing Machinery and Intelligence.” Mind 59.
• Vallor, S. 2016. Technology and the Virtues; 2024. The AI Mirror.
• Weizenbaum, J. 1976. Computer Power and Human Reason.
• Wiener, N. 1948. Cybernetics; 1950. The Human Use of Human Beings.