The problem of nihilism arises when conventional sources of meaning and motivation wither or are overcome by doubt. By nature, we look to externals to justify what we value. That is, we look to a worth inhering in those things themselves, or some reason in the world why they should be valued. This habit stems from the natural outward orientation of the brain, which focusses on the environment as the source of the organism’s wellbeing. This orientation is a basic fact of being a creature with a nervous system, dependent on an environment for its life. There is security in a dependent relationship, as the child finds security in the mother. The loss of this dependency itself is threatening. One can feel “orphaned,” on one’s own to face the Void (or, more cheerfully, the Great Mystery). One can no longer count on inherited patterns of belief we call meaning.

The same outward focus is the source of our natural interest in causality. We notice that events lead to other events. Turning that observation upon ourselves is a different matter. We are loathe to think that the world determines our every act—including our thoughts and feelings and our very perceptions. We admit that physical causes operate upon and within the brain. But we prefer to think that there are reasons as well as causes for what we do, think, feel and perceive. We prefer to believe that we choose our actions, and that our perceptions are justified insofar as they correspond to reality.

The senses seem to reveal the external world as it truly is. Similarly, there is more to choosing behavior than whim. Choices have real consequences and we naturally seek to justify them (to ourselves and to others) in real terms—which means in terms of causal processes in the world. On the one hand, we recognize that the world has power over us; on the other, we want to determine our own actions and thoughts. Meaning is naturally imposed on us by the external world, upon which we depend as natural organisms. But as beings who wish to claim free will, we are ambivalent toward that dependent condition. Through our biological dependency, meaning seems to abide ready-made in the world, just as the world seems transparently revealed to the visual sense. However, to know that meaning, like perception, is a function of biological need—and not intrinsic in the world—renders the world unreliable as the source of meaning and throws us awkwardly back upon ourselves.

Nietzsche warned that such nihilism could lead to personal despair, apathy, and a passive or destructive culture. There can be anger at the loss of meaning, as of any resource. Disillusionment or disenchantment is a loss of faith in something once deemed real or true, and therefore a loss of certainty. The normal outward-facing mind can no longer count on finding justification “out there” for its beliefs and actions. Doubting particular beliefs or assumptions can be functional, because it can lead to a better understanding of reality and more self-confidence. But doubting the reliability of the mind or the reality of one’s experience can be undermining and overwhelming.

Descartes’ skepticism concerned the input of the senses, which could be falsified through interference in the nervous system; his solution was that God would not permit systematic deception. If we substitute nature for God, we could suppose that natural selection would not permit deception that prevents our existence at least long enough to reproduce. (Deception that promotes our existence is allowed!) In any case, Descartes took comfort in his cogito ergo sum, concluding falsely that—while one could doubt the existence of the world—one could hardly doubt one’s own existence as an experiencing subject.

Nietzsche’s skepticism concerned something else—not the veracity of experience but its meaning. Even granted reliable sensory input, there is no absolute basis on which to interpret it, no absolutely trustworthy source of meaning. There is no absolute reference frame: “God” is dead. His solution was to re-evaluate valuation itself—to relinquish reliance on the external world to determine one’s beliefs and actions, whether by cause or by reason. He took comfort in amor fati—the practice of intentionally embracing all experience without the habitual evaluation. If meaning cannot be counted on from outside, one must create it oneself. Even negative experience should be welcomed as an opportunity to be intentional and self-determining.

Meaning is the framework for evaluating experience. Its loss is itself naturally evaluated negatively. That judgment simply reflects the continuing general habitual reliance on externals, part of our natural conditioning. Despair or depression is a normal response to the deprivation of meaning. One can defend against it by joining a group or cause, embracing an ideology or reaffirming a faith, returning to traditional values, adhering to routines, etc. One can also simply lose oneself in distraction, entertainment, or drugs. Nietzsche calls such responses passive nihilism. While these responses may acknowledge the potential loss of meaning, one reacts as though to an external threat, reflecting the continuing belief in reality as a causal factor. While individuals might choose to actively confront the Void, society as a whole cannot be expected to. Yet, if it does not, Nietzsche warned, it may fall into religious fundamentalism, rigid nationalism, populist movements, or totalitarian systems, as substitutes for lost meaning—all of which we have seen.

An alternative is to voluntarily relinquish the meaning of which we otherwise feel deprived. But that requires claiming utter responsibility for all one thinks and feels. Ironically, that is the position of the Creator, as opposed to the finite creature whose lot is to respond as best as it can to the vicissitudes of the Creation. Nietzsche’s Übermensch is a godlike being, who asserts free will against the determinism of the natural world. That is a strenuous and heroic ideal, whose demands may have been too much even for Nietzsche, who collapsed at age 44 and spent the rest of his short life being cared for by family or in an institution. One could read this as a concrete illustration of the human confrontation with the Void. To live continuously in tension with it, creating new values ex nihilo, requires enormous courage and vitality. Nietzsche’s life shows both the possibility of a life-affirming philosophy and the cost of pushing a finite organism to its limits.

In other words, existentialism may be bad for your health. Moreover, to have faith in it—much less to seek refuge in it (like in the Buddha or in Christ)—would be paradoxical. That would assert an externality to justify a course of action; but that externality is precisely the truth that no externalities can absolutely justify action or belief. To “love life as it is” (embracing all experience as Nietzsche prescribed) must include the biologically-grounded judgments of pleasure and pain, which are given in experience and are hardly matters of conscious choice. (Except for masochists, loving pain seems a contradiction in terms.) To confront the paradox is to confront the Void itself. For, we are conditioned to seek reasons (justifications) for our values, beliefs and actions. If there is no reason underwriting any choice, there is no reason to choose existentialism either. This does not prevent one from choosing one’s values or behavior, only from expecting a justification. There one is on one’s own.

Choice is ultimately arbitrary insofar as it cannot be justified by externals. On the other hand, justification can be found internally: in how the organism senses and evaluates its own states, providing its own reasons. In that context, to choose nihilism, existentialism, or anything else, mirrors the organism’s fundamental self-defining nature—its autopoiesis. Looking inward affirms the self’s responsibility for itself and its actions, reflecting the organism’s autonomy and relative freedom. From an existential point of view, values are not found but created. Nietzsche viewed life as a work of art, rather than a science. Artistic choice is simply up to the artist. On the other hand, value can be a consciously shared collective creation. Then it would no longer be what we fight over, but what we create together.

Increasingly, people are getting their information directly from chatbots, which do the trawling for us, instead of using conventional search engines to find relevant sites and then visiting those sites. According to The Economist (July 19, 2025), the consequent loss of revenue from advertising that appears on those sites poses a looming problem. The internet is in trouble because AI-powered search engines are reducing human traffic on the Web. After all, humans are needed in the loop—to make purchases, to spend money, to be good consumers!

From the point of view of those who have felt all along that the Web should be a non-profit resource, commerce is not the victim but the perpetrator. From that point of view, the Web has been in trouble from its inception.

Certainly, there are costs involved to maintain the internet as a “commons.” (Accelerating electricity consumption for giant servers could one day bankrupt the planet—but that’s another story.) These infrastructure costs must somehow be passed on to users. The latter pay fees for access to their internet provider, for example, and for various apps and services. Yet, the bulk of the cost of running the Web is apparently paid by advertisers—and, thus, indirectly by consumers who view the advertising. They pay by buying products advertised—despite (and indeed because of) having paid for internet access. The business model is like a conventional newspaper, which charges a subscription fee but also derives revenue from printed advertising. The proportion between these sources of revenue can vary.

Presumably, advertising works, otherwise it wouldn’t pay. What that actually means is that it causes people to buy products and services they would not spontaneously seek out, and perhaps do not actually need. The word literally means “turn (attention) to.” In other words: to advertise is to distract attention from where it would otherwise be directed. This is a complaint of many users, who find the distraction of online ads annoying. Some are willing to pay for the “service” of not being exposed to them. In effect, they would rather pay up front for internet access than pay indirectly through ads. This changes the balance between direct and indirect revenues; but the fees for ad-blocking do no go (directly) to pay the costs of infrastructure.

Why advertising works is a mystery with deep implications for society and human psychology. For people who know their own needs and wants, it is helpful to get information about products and services they seek, and how to find them. Information about what they do not need and are not seeking is noise—an annoyance. Personal assistant chatbots can provide a very useful service by searching, upon request, for those products and services a client actually wants. In other words: shopping for the client. However, advertising is not based on this client-driven model, but on manipulating people to consume.

If consumers were rational, advertising would not pay. Users tolerate online ads because they seem to get free access to the sites that incorporate them. But if advertising works, the access is not free. We do pay for it—indirectly and collectively, if not personally. If you don’t happen to respond in that moment to the ads on that site, someone else nevertheless does. The effectiveness of advertising is statistical.

Big data is a new commodity, ultimately dependent on advertising. Aside from identity theft, your personal “data” are about your online attention patterns, so that advertising can target you specifically. If advertising never works on you, your data are worthless commercially, although they could be of interest to the state. You get the advertising anyway, because statistically it works on enough people. It would cost the advertiser to remove you individually as a target— which, ironically, has become a service you can pay for, with ad blockers or with the effort it takes to “unsubscribe” to a mailing list.

For those who seek fingertip information online—for whatever purpose—chatbots provide a valuable service, for which we should be willing to pay. For those who seek to make money from their websites indirectly through advertising on their sites, chatbots may represent a threat to their traffic-based income. This points to a divide in motivations. In the early days of the internet, there was great hope for a universal non-commercial show and tell, where people could share information freely—that is, without restriction and without cost beyond maintaining infrastructure. It did not take long for commercial interests to take over—for the purpose of profit unrelated to that cost. The Web is now primarily a marketplace that incidentally allows show and tell.

Those motivated to share content altruistically, or for fun, need not feel threatened by chatbots stealing traffic from their sites. If the information is the important thing, then what does it matter where it comes from or how it gets delivered? If the information is offered gratis, crediting sources is important for validation—but not because of copyright. The problem is rather for those whose livelihood depends on the sharing—authors, artists, musicians—who need and deserve compensation for their creative efforts. Their livelihood depends on it. AI threatens to take over their production as well as to affect their distribution. On the other hand, the threat to those whose “productive” contribution is no more than manipulating the attention of others—or profiting indirectly from their labors—is a different matter. The divide is roughly along the lines of the traditional divide between labor and capital.

Will chatbots diminish the incentive to create online content? Well, that depends on what that incentive is. If you are making content primarily for gain, then you may deservedly be at risk. If your motive is to share your work for its own merit, or for its potential benefit to others, you should not necessarily be discouraged by a decrease in human visits to your site. Your work will be forwarded, in some digested form, by chatbots that may actually frequent your site more often than was occurring before.

The more disturbing question is how chatbots will transform that content. Volunteers may be discouraged from contributing to Wikipedia, for example, if they know the information will be distorted or that Wikipedia will not be credited. This is an epistemic issue of citing sources, not a commercial one. It reflects broader issues of the dissemination of information in modern society. In contrast to the non-profit Wikipedia, Reddit is a show-and-tell forum that is also a corporation with a listed share price. Those who share on the platform may or may not be shareholders in the corporation. Even for those who are both, losing human readers should be a different concern than falling profit. AI now competes with human content providers, who have been competing with each other all along. Getting attention remains the same needle-in-a-haystack problem it has always been. If AI can provide better content faster, this is indeed a challenge to humans, but one we have created ourselves. Let us rise to it!

Many academic publishers of journals and book now encourage an “open access” model, where authors or their institutions pay the cost of publication, which is then available online to the reader for free. This has been very profitable for the publisher and very costly to the supporting institutions, such as universities. It may be one cause of rising tuition fees. Why should costs for reproducing content online should be so high, when the intellectual content itself has already been produced for free, or already paid for through academic employment? The cost of formatting has been greatly reduced by AI tools, and pre-publication editorial reviewers are usually unpaid volunteers. A simple answer is greed, euphemistically known as profit margin. Academic publishing is big business, dominated by a few players. In the context of the present information distribution system, the publisher offers what seems to be a valuable service, given the absence of alternatives—though hardly out of the goodness of their heart. AI has the potential to revolutionize the information distribution system, so that access would be truly open. But predatory commercial interests will try to hijack it for their own benefit.

Motivation is the dilemma that underlies the emerging crisis for the Web—and for the world at large. The issue was there from the start, when the internet was envisioned as a “commons” whose use was up for grabs. It was there at the origins of capitalism, when lending transformed from a reciprocated neighborly gesture to ruthless usury. Should the Web be for sharing information, moderately compensated, or for rampant commercial exploitation? As it stands, sharing of information is still possible—in the context of commercialism. According to The Economist, “everyone has an interest in making content-creation pay.” Really, everyone? The tragedy of the Web is the tragedy of modern society. We are in a crisis of motivation.

As part of the system of nature, humans must eat other beings, whether animal or plant. Beyond satisfying hunger, culturally we’ve made dining on our fellow creatures an enjoyable experience. Yet, culture itself reflects a rejection of the animal way of living. Cooking makes food more digestible chemically, but also esthetically and morally. We do not, like other carnivores, tear into raw bloody carcasses. While not equipped with the teeth to do so, we also do not want act like brutes. The whole of civilization represents a flight from our animal nature, as well as from biological and physical limitations. But, as such, this project of transcendence can only be a compromise. We may choose to eat with cutlery, manners, spices—and not like the beasts. Yet the fact remains that we must eat.

With good reason, there is increasing concern over animal welfare, as well as concern for future food supplies. The circle of moral concern has expanded from sheer tribalism to a universal definition of humanness as membership in a species, regardless of race or ethnicity. Now it rightfully extends to other creatures in the “web of life,” and potentially to artificial creatures as well. Yet, the basis for such concern remains fundamentally anthropocentric. The notion of sentience is valued as a criterion, based on conscious human experience. We empathize with other creatures in the way that we do with other people: by imagining their experience. While that extends a natural capacity that enables human sociality and coexistence, sentience is an inadequate moral criterion for the treatment of animals. The fundamental problem is that we cannot experience, or really even imagine, the consciousness of other forms of life. Indeed, we can only experience our own personal consciousness. We humans have agreed, by convention established through language, to acknowledge and mutually conceive each other’s experience as similar. We do not have that advantage with other creatures and, for the most part, do not consider them persons. We are confined to observing their behavior to infer what they might experience, using our own experience as a reference: how I would feel in that situation, with that injury, etc. It long remained easy enough to deny that non-human creatures even have experience.

Using behavior as a guide, it now seems clear that many creatures show signs of reacting to injury or threat in the ways that we associate with pain or fear. Yet, it is a mistake to judge their moral worth by an imagined sentience, as though the creature’s experience trumps its objectively observable condition. The cliché of putting a suffering animal or insect “out of its misery” suggests that the pain itself is what counts, not the injury that results in the pain. (In that way, we can be spared the effort to repair damage, in contrast to the heroic efforts made to repair human injuries.) Similarly, “humane” slaughter of animals for meat overlooks the worth of the animal as a remarkable entity, by focusing on simply minimizing its suffering. But its pain, or fear or suffering, is its own evaluation of its threatened or damaged state. To give it a mercifully quick or anesthetized demise simply curtails this self-evaluation of its own destruction—as though fooling the creature substitutes for preserving its life. In contrast, we anesthetize people for surgery, with the aim to preserve them. A more useful criterion than sentience is the well-being (the objective state) of the creature, as determined by observation. This may not coincide with the creature’s own self-assessment, but at least it refers to something potentially observable. Doctors make their assessment of damage to your tissues independently of your assessment through felt pain. Certainly, they strive to relieve your pain and distress; but, above all, they want your body to heal for your sake. We may care in that way for pets, but hardly for animals destined to become our dinner.

So-called utilitarianism is based on the assumption that what matters is subjective experience rather than an objective state of affairs. The idea is to maximize pleasure and minimize suffering, even worldwide. (The parallel in economic theory is maximizing “utility.”) This seems morally admirable, especially if it could extend to all life. However, there is no way to quantify pleasure or suffering, which are falsely reified as measurable commodities. The idea leads to absurdities, as in trying to calculate how much pleasure for some individuals justifies a given amount of suffering for others. Moreover, what counts or “matters” can only mean what matters to someone or some group in particular. In the case of livestock, what matters to the human owner is hardly what matters to the animals themselves, who do not volunteer to sacrifice themselves for human nourishment. Similarly, moral arguments based on “intrinsic” worth of life are spurious, because worth means worth to someone, and may vary accordingly. Ideas of inherent dignity or moral equality among species (the interests of all creatures are equally valuable) similarly have no absolute sense; they can only mean that someone values them equally or treats them with uniform dignity. If humans count for more, it is likely because they are doing the counting.

One way to measure the worth to us of various creatures—morally and even economically—would be through the effort required to create them artificially. With artificial intelligence and genetic engineering, we are on the threshold of the science and technology to do so. Imitating, recreating, displacing, and improving upon nature are ancient goals slowly being realized through technology. They partially satisfy our drive to altogether transcend natural limitations. But “nature” is not only the physical world surrounding us; it is also the nature at the core of our being. We’ve sought to morally transcend our own animal nature, at first through religion and law, and now through science. Yet, a most embarrassing  remnant or our animality is the need to feed off of other creatures. While other life forms are rightly considered worthy of our moral concern, our primary concern should be for our own status as moral agents. Are we essentially the gods we aspire to be or are we the beasts that nature made us? Given what we eat, the verdict should be clear.

Artificial intelligence not only can imitate life, but can also advise us how to properly relate to it. I asked a chatbot to outline solutions to the moral dilemma presented by food dependency. I began with the premise that dead human bodies represent a wasted food source—in contrast to the billions of animals whose lives are deliberately made miserable and cut short for human consumption (more than 70 billion land animals alone, per year). Though I wasn’t asking how to murder people for food, I wondered if the prompt might trigger a censure rule. Quite the contrary, the chatbot enthusiastically made some interesting suggestions, even proposing a “Transhumanist Food Manifesto.” According to this vision, as so aptly put by the AI: “No child starves. No cow screams. No forest is razed for a hamburger. No body is wasted in flames or boxes.”

Certainly, there would be problems with recycling human corpses, let alone with eating human flesh. Aside from cultural taboos and biases, human brains contain dangerous prions that are not destroyed by cooking. Like other long-lived animals, human remains contain accumulated heavy metals and other toxins. Yet, it is theoretically possible to hydrolyze proteins, derived from human sources, into amino acids, in a purified way. Instead of eating human flesh, bodies could be rendered into fertilizer, animal feed, or the nutrients for growing lab meat synthetically. The program would be voluntary, of course, like donating your body for medical research (with a little tattoo, saying “Eat Me”?). Human cells could also be used to culture synthetic meat. Protein-rich biomass could be engineered from bacteria, yeast, and algae.

From a moral perspective, and also for efficiency, food would no longer be a product of suffering, slaughter, or waste. Food production could be optimized with AI and genetically tailored to individual nutritional needs. While it could be made to taste like the real thing, it would not even necessarily consist of solids. Nutrition could be delivered via synthetic blood, nanobot-mediated infusions, or even photosynthetic skin implants. All in all, factory farming would be eliminated and famine potentially overcome. Emissions and land use would be minimized. All biological matter, including humans, would be respectfully recycled. The human moral dilemma of carnivorism would be solved.

The treatment of animals is intimately linked to the treatment of human beings. At one time, members of the other tribes were literally fair game: the category ‘human’ was reserved to one’s own kind. We’ve since automated both the slaughter of people and animals alike, though we give lip service to humane treatment of both human and animal captives. It can be argued that improved ethics in regard to animals has followed upon improvements in our ethical principles in regard to human beings. Perhaps the leverage can work the other way as well. We might treat each other better if respect for life was unconditional. But that seems possible only when our own existence doesn’t depend on taking the life of ostensibly sentient beings.

Common sense may not be so common, but what exactly is it and what is it for? Aristotle thought there must be a special sense to coordinate the other senses. This meaning persisted through the Middle Ages, although the Romans had added another meaning: a moral sensibility shared with others. It fell to Descartes to provide the modern meaning of “good sense” (bon sens) or practical judgment. Like the other senses, he thought it was not reliable and should be supplemented by formal reasoning. Giambattista Vico, the father of sociology, thought common sense was not innate and should be taught in school. His view of it as judgments or biases, held in common by a society, merges with the idea of public opinion or consensus. Kant and later thinkers returned to the idea of a shared moral sensibility, so that common sense is related conceptually and linguistically to conscience.

We have long taken common sense for granted, that it should come as standard equipment with each human being. That presumes, however, that each person not only develops according to a norm but develops in the setting of the real world. Ultimately, it is physical reality and our physiology that we have in common, which provide the biological basis for mutual understanding and consensus. The human organism, like all others, evolved as an adaptation to the natural world. Whatever “practical judgment” we have is learned in relation to a world that holds over us the power of life and death. Common sense is our baseline ability to navigate reality.

Of course, most of us do not grow up in the wild, like animals, but in environments that are to a large degree artificial. “Reality” for us is not the same world as it was for people a hundred years ago, a thousand years ago, or ten thousand years ago. Yet, until recently, the reality experienced by people of all times lay objectively outside their minds and bodies. Common sense was firmly grounded in actual sensory experience of the external world. This can no longer be taken for granted. We now live increasingly in “virtual” realities that are, however, far from virtuous. Because they can be as diverse and arbitrary as imagination (now augmented by AI) permits, there is no longer a common basis for shared experience, or for common sense.

This shift is the latest phase of a long-standing human project to secede from the confines of nature and the body. In the anthropological sense, culture is the creation of a distinctively human realm, a world apart from the wilderness and physical embodiment. We built cities for physical escape. Our first mental escape was through trance, drugs, and religion, which imagined a life of the spirit or mind that was distinct from the life of the animal body. With Descartes, “private experience” formally became a realm unhooked from the external world. With dawning knowledge of the nervous system, he grasped that the natural formation of experience could be hijacked by a malicious agent. His thought experiment became the basis of the “brain in a vat” scenario, the Matrix films, and the paranoid popular memes that you are “probably living in a simulation” or in a theatrical hallucination created by “prompts.” Descartes consoled us that God would not allow such deception. Humanists supposed that natural selection would not allow it. Post-humanists invite it in the name of unlimited freedom.

In any case, common sense is the baby thrown out with the bathwater of external reality. Through technology, humanity grants itself its deepest wish: to be free to roam in inner man-made worlds disconnected from the world outside the skull. Nature had granted us a relative version of that freedom through dreaming and imagination. But our impulse toward creative mastery requires that humanity find this freedom on its own, not naturally but artificially. It must be created from scratch, originally and absolutely, not accepted as a limited hand-me-down from biology. Here we venture into dangerous territory. For, we continue to be vulnerable embodied creatures living in real reality, even as we buckle up for the virtual ride. Is God looking out for us while we trip? Is nature? The other side of utter creative freedom is utter self-responsibility. If experience is no longer to be grounded in the real world, but a matter of creative whim, then what basis is there for limits and rules—for anything but chaos?

The more time children spend online, using their eyes to look at screens instead of at the world outdoors, the less direct experience they will have of the external world. The more time they spend in some entertaining digital fantasy, the less basis they will have for developing their own common sense, which is grounded in the natural use of the senses to explore the external world. Of course, this applies to adults as well. It is not only the proper use of the senses that may atrophy, but the very ability to distinguish real from virtual, nature from artifact, truth from lie. The contents of movie entertainment, for example, are often absurdly fantastical, about themes and situations deliberately as far removed as possible from the tame humdrum of real life. It is precisely drug-like distraction from daily living that entertainment is typically designed to provide. But this is a vicious circle. We then expect from the real world the level of stimulation (adrenaline, serotonin?) that we get artificially from films, online gaming, “adult” content, and “substance abuse.” Indeed, we are trained to ignore the difference between reality and fiction, which can result in failure to tell the difference.

Social media are a form of entertainment, a virtual drug in which truth is reduced to gossip. They may help build consensus with those who “like” you and are like you in some context. In a brave new world of information overload, where the basic challenge is to sort what is fact or reliable opinion from what is not, common sense should be a legacy tool one can count upon. But common sense is not consensus. The failure of a society to know the difference is the banal soil in which authoritarianism grows. We are seeing it around the world right now.

Large language models and similar “generative” tools are another form of virtual reality and entertainment. Ironically, if properly used, they provide access to an artificial version of common sense—or at least consensus. For, they draw upon the common pool of human experience and creative output, as archived digitally. The answers you get to chatbot queries reflect a baseline of collective human knowledge and creativity; they are also organized according to collective ideas about what is logical, sensible, relevant. Another name for such collective wisdom, however, is mediocrity. LLMs are not minds that can think for themselves or originally. If they regurgitate information that proves useful to you, the task of understanding and using the information remains your own, grounded in common sense.

The internet potentially embodies the ancient ideal of omniscience. In itself, the instant online access to encyclopedic knowledge aggravates the problem of discernment: how to know what and whom to trust. The traditional answer to that dilemma has been education, reinforced by common sense, what is meaningful and what is chaff. The traditional encyclopedia, while vetted by well-educated experts, gives relatively cursory information. The new answer is the “intelligence” of the AI tool itself, which sifts, organizes, and even interprets seemingly unlimited information on your behalf. You place your trust in it, as you would in human experts, at your own risk. It draws upon a common denominator of expert opinion. As with human experts, however, you are still dealing with hearsay: accounts that are second-hand (or nth-hand), which you must interpret for yourself. When your quest to go deeper approaches the ceiling of current common understanding, the replies will simply recycle existing clichés.

The situation is like what happened with the invention of printing. Suddenly people had a greatly expanded access to information (beginning with the Bible). This invited them—and indeed required them—to think for themselves in ways they were not used to when guided by the erstwhile gatekeepers of knowledge. This hardly led to consensus, however, but to an explosion of diverging Protestant sects. An optimistic view of the new information revolution is that people are similarly being challenged to think for themselves. Again, the actual result seems to be divisiveness. Of course, the printed page—while novel, thought provoking and entertaining—did not do people’s thinking for them. Yet, AI proposes do exactly that! To implicitly trust the authority of AI is not so different from the faith in religious authority before the Reformation, when the priest could do your thinking for you. If common sense did not provide immunity from the excesses of theology, we can blame the closure of the medieval  world—an excuse we should no longer have. Common sense should be the back-up tool of first resort. But to maintain it requires first-hand experience in the real natural world, which you cannot get online.

Knowledge is a process that involves a dialectical cycle: thesis, antithesis, synthesis. The last term then serves as a new “thesis,” beginning a new cycle. We see this in formal knowledge processes, like scientific theory-making and testing. A new idea is proposed to explain data or to make up for a deficiency in current theory. This idea is published in a journal, for example, which invites comment and critique (antithesis), which may lead to further refinement and experimental testing. If the idea is accepted by the scientific community (and not disqualified by experiment), the resulting synthesis becomes a new thesis to be eventually challenged.

Ordinary cognition involves a similar cycle. But the brain tends to be more definite in its conclusions than scientific experiment or observation, whose results are always probabilistic; and it tends to be less rigorous about testing ideas. The organism must be able to act decisively on the basis of the information it has, however inadequate. If our perceptions were not definite despite actual uncertainty, we would be paralyzed by doubt and unable to act decisively. Yet, the knowledge cycle is incomplete and less reliable when thesis alone is in play, however confidently asserted.

The inherent need to believe our perceptions and trust our beliefs runs up against the contradictory perceptions and beliefs of others. While objectivity is desirable, the natural tendency is to mistake perception for reality or truth, short-circuiting the epistemic process. And in order to maintain this illusion, we tend to overlook inconsistencies in our own thinking, perhaps to protest that we are being objective while others are not. While there can be dissonance within one’s own thinking, leading to self-scepticism, dissonance with others is nearly guaranteed. Too often, internal dissonance leads not to questioning one’s own views, however, but to retrenchment of them and scepticism in regard those who disagree. Nevertheless, the fact that opinions differ plays an overall positive role in the epistemic cycle, for which others provide the necessary antithesis. Whether spontaneous or forced by others, the recognition of one’s own error or subjective limits enables mind to evolve at once toward humble relativity and greater objectivity.

It can hardly be taken for granted that embodied mind seeks truth. The goal of life is survival long enough to reproduce, not objectivity. In other words, our natural condition as organisms is to see and know what we need to see and know. And this is not simply a matter of selective attention or reduced information flow—an obscuring filter between the mind and an otherwise transparent window on the external world. Simply, there is no window at all!

The epistemic circumstance of the scientist parallels that of the brain, sealed inside the skull, which relies on the input of “remote” receptors to infer the nature of the external world. The scientist similarly relies on instrument readings. Both situations demand radical inference. The brain makes use of unconscious perceptual models, according to the body’s needs. Scientists consciously model observed phenomena, according to society’s needs. The brain’s unconscious perceptual models are reliable to the degree they enable life. By the same token, scientific modelling, like other human practices, should not be regarded for its truth value alone, but also for its ultimate contribution to planetary well-being. Good science supports a human future.

Science and engineering are intrinsically idealizing. The dominance of mathematics (which is pure idealization) means that physical phenomena are idealized in such a way that they can be treated effectively with math. This leads to an analysis of real systems in terms of the idealized parts of a conceptual machine. But the reality of nature never conforms perfectly to the idealization. There are no spherical cows, and nature is not a machine. The discrepancy constitutes a potential antithesis to the oversimplified thesis.

Unlike the individual brain, science is a collective social process. It is a communication among scientists—a (mostly) polite form of argumentation through which ideas are justified to others. In fact, science is a model of social cooperation, transcending political and cultural boundaries. Just as there is an epistemic cycle of knowledge production, so there are larger-scale cycles in science: paradigm shifts, but also alternations of more general undercurrents, themes, and fashions such as positivism and Platonism.

Indeed, the interplay of positing and negating aspects of mind manifests in historical cycles generally. The opposing phases in culture may be characterized broadly as heroic and ironic. These poles form a unity, like those of a magnet, alternating as undercurrents which surface in philosophical, social, political, religious, moral, and artistic movements, as well as in scientific fashions. The limiting nature of any proposition or “positive” system of thought casts a complementing shadow that is the other side of the coin. Every thesis posited defines its own antithesis. Where contradictions cannot be resolved logically—that is, outside of time—they give rise to temporal alternations in the phases of a cycle. The pendulum of history swings back, fashions return; we move in spirals if not circles.

Throughout history, there has been a dialectical relationship between the playful, embroidering, subjective, ironic side of the human spirit and the heroic, serious, goal-oriented, earnest, realist side. The ironic mentality delights in playing within bounds. It understands limits to be arbitrary, relative, intentional. The heroic mentality rejects limits as obstructions to absolute truth and personal freedom, while worshipping limitlessness as a transcendent ideal. The heroic is aspiring, straightforward, straightlaced, straight-lined, passionately simplistic, rectilinear, square, naive, concerned with content over form, and tending toward fascism and militarism in its drive toward monumental ideals and monolithic conceptions. The ironic is witty, sarcastic, curvaceous, ornate, sophisticated, diverse, complex, sceptical, self-indulgent and self-referential, tending toward decadent aimlessness and empty formalism. While each is excessive as an extreme, together they are the creative engine of history.

There are cycles of opening and closing in societies, in individual lives, and in creative processes generally. The tension between idealism and materialism, or between heroic and ironic frames of mind, helps to explain why history appears to stutter. Most of any historical cycle will consist of working out the details of a new regime, scheme, paradigm, or theory. But the cycle will also necessarily include an initial creative ferment and a final stagnation, sandwiching the more conventional middle. When change is too rapid or chaotic, there is nostalgia for the probably not-so-good ol’ days. Instability inspires conservative longing for structure, order, certainty and control—until an excess of those inspires revolt again, beginning a new cycle. Generally, too much of anything breeds contempt—and therefore its opposite—as part of the homeostatic search for balance.

Cycles acted out in real time may reflect the deeper endemic circularity of logical paradox. If space and time themselves are products of the brain, how can the brain be located in the space and time it has created? Self-aware consciousness deems the external world to be an image constructed by the brain, but the brain is part of the world so constructed as an image. The endpoint of an explanatory process is recycled as its beginning. It does not seem possible to resolve such circularity in a synthesis. That is perhaps why there cannot be a logically consistent scientific theory of consciousness, which remains a mystery because we are it.

Against common sense, people can believe some very strange things. One marvels at the ingenuity of the human imagination—not only the things that make practical sense, like houses, agriculture, technology—but above all the things that make little sense to a rational mind, like gods and demons, superstition and magic. Yet, religion and magical thinking have characterized human culture far longer than what our secular culture now defines as rationality.

The ancient Greeks we admire as paragons of rationality seem to have actually believed in their pantheon of rowdy and absurdly human-like gods. The Pythagoreans believed in sacred numbers and the transmigration of souls; they used mathematics and music for mystical purposes. Plato believed in a metaphysical realm of Ideal Forms underlying material reality. Copernicus thought the planets must move in perfect circles, because the circle was the symbol of perfection; and Kepler thought that angels moved the planets along their (elliptical) orbits. The early scientists were literally alchemists and Creationists. There are scientists today who believe in the Trinity and the transubstantiation of the Eucharist. My point here is not to disparage religion as superstition, but to marvel that superstition can exist at all.

Language confers the nearly magical power to define things into being—as we imagine and wish them. Outrageous beliefs are possible because a story can easily be preferred to truth. A story can make sense, be consistent, clear, predictable and repeatable. Reality, on the other hand, is fundamentally ambiguous, confusing, elusive and changing. Reality only makes sense to the degree it can be assimilated to a story. It made sense to many ancient cultures that a year should have exactly 360 days (corresponding neatly to the 360 degrees of the circle). The fact that the daily rotation of the earth on its axis has no physical relation to the time it takes to move around the sun was a great inconvenience to calendar makers over the ages, who knew better than nature how the world should work.

In general, what we consciously experience as real is the result of sensory input that has been assimilated to a story that is supposed to make sense of it, and upon which an output can be based that helps us live. The story does not need to be true; it only needs to not conflict with the existence of our species. That gives a wide latitude to imagination and belief.

The brain is a delicate instrument, normally tuned to the needs of the body. Like a complicated machine, there is much that can go wrong with it. Being so complex and malleable, it is also capable of great variation among ostensibly similar individuals, which can include behavior that deviates far from what serves the body or serves the species. Underlying all variation or dysfunction, however, is the natural faith we have in experience. We naturally tend to believe whatever our minds present to us. Human freedom consists in the ability to be wrong while utterly convinced that we are right.

Addiction is an obvious example of the compelling attractiveness of some stimuli—such as alcohol, drugs, or sex. It is natural to seek pleasure and try to avoid pain, because these represent the state of the organism, which tries to maintain itself. However, when experience is sought for its own sake (rather than for the body’s sake), the link with wellbeing is broken. We can then find pleasure in things that are bad for the body (and society), and reject things that are good for it. Of course, we have extended such meanings to include intellectual pleasures and emotional suffering as well. In fact, humans can abstract experience in general, away from its ties to the body, so that it becomes a sort of private entertainment to pursue for its own sake, apart from its relevance to bodily or social needs.

Other compulsions, such as obsessive behavior (including avoidance as well as attraction), further demonstrate the mind’s willingness to believe its contents. And then there is artificial input, applied with electrodes to the brain, for example, which can stimulate specific experiences or memories. Or applied by means of transcranial magnetic stimulation, which can change your perception, for example altering the apparent color of things or draining them of color altogether. On the other hand, sensory deprivation causes outright hallucination, as the brain makes up its own experience in the absence of sensory input.

Depending on the circumstance, we may either believe, or have reason not to believe, a given experience. If you know you have wires stuck in your head, you may justifiably be suspicious of your experience. On the other hand, if you have ingested a psychedelic drug, or have an unsuspected brain tumor, it may affect your judgment as well as your perception, and you may fail to disbelieve your hallucination. It is helpful to keep in mind that the brain hallucinates all of the time; while some of the time its hallucinations are dominated and guided by bona fide sensory input. We then call that reality and feel justified in believing the hallucination.

Within the framework of normal perceptual reality, we also have thoughts and feelings that we feel compelled to believe. Social media now run rampant with outrageous claims and memes, endorsed by our natural willingness, as social creatures, to believe what others tell us. Again, this reflects the power of language to evoke mental images and feelings, in a socially approved form of hallucination, to which we tend to accord the same credibility as we do to first-hand perceptual images and the feelings they arouse.

Even in the most abstract realms of speculation, we tend to have faith in our mental constructs. Often that faith is justified, at least provisionally, as a useful tool that can be updated by further observation and experiment. In the seventeenth and eighteenth centuries, scientists believed in a substance called phlogiston, released as heat during combustion. This concept was superseded by the caloric theory, which conceived heat as a sort of fluid. That idea was abandoned in favor of heat as a form of energy—whether the kinetic energy of molecules or the radiant energy of electromagnetic “waves.” Energy, in modern treatments, persists as a kind of substance interchangeable with mass (as per Einstein’s famous formula). What is actually involved, in all cases, is tangible measurement in specific contexts, not some ethereal quasi substance. But to reify energy conceptually seems to be useful in physics even though “it” manifests in such diverse forms and consists in no more than measurable quantities. (Not to mention nebulous popular metaphysical notions of “energy,” such as chi.) Even more derivative abstractions, like entropy and information, are now reified as quasi-substantial, attributed their own causal powers. Even the measures we call space and time are reified—for example, as the 4-dimensionsal spacetime continuum.

To objectify is a built-in tendency of the mind. After all, our primary orientation is toward objects in space. We literally experience the world as a real space outside our skulls, filled with interacting things. Since language and thought are essentially metaphorical, it is natural (if not logical) for us to think of abstractions—indeed, anything that can be named—as at least vaguely substantial. We ontologize everything, more or less automatically (just as I am now, admittedly, ontologizing the compulsion to ontologize). The fact that this compulsion includes reifying experience as ‘mind’ or ‘consciousness’ leads to the infamous Mind-Body Problem, as we then ponder what sort of thing it must be, compared to physical things. Descartes posited a dualism of physical thing and “thinking thing.” Others, before and since, have proposed some monism or other instead: that everything is material, that everything is mental, or that mental and physical amount to the same “thing.” Underlying these isms, concerning what is ultimately real, remains the fundamental need to be settled about something that seems substantial.

The dualism above may turn out to be little more than a built-in feature of our nervous system, which provides us with two radically different points of view. The myelinated exteroceptive nervous system is the basis for the experience of an external world of objects in space and “digital” judgments regarding them. Through language, we conceive a “third-person” point of view based upon that experience of a world of publicly accessible objects. But the body operates also with a more fundamental unmyelinated nervous system, responsible for feeling, valuation, and homeostasis. It operates in a more analog mode to monitor the body’s needs and regulate its state. We identify these aspects with a “first-person” point of view, in which qualia and feeling are the chief features and seemingly private. Evolution has thus provided us with two minds, so to speak, which have in common the need to believe what they present.

The concept of the Turing Test, as proposed by Alan Turing, was intended to distinguish between a machine’s intelligent behavior and that of a human. Here we extend and generalize this idea to a broader framework, the Generalized Turing Test (GTT), as a thought experiment designed to distinguish between what is natural and what is manmade. The fundamental premise of the GTT rests on the idea that ‘natural thing’ and ‘artifact’ are categorically disjunct concepts, though the line between them can become blurred in actual experience. By premise, natural things are not made, but simply found, in the literal sense that they are encountered or come upon in experience. They seem to exist independently of human creation or intervention. Artifacts, on the other hand, are made; they are products of human agency and definition, though they might also be found in the above sense. Following Vico’s makers-knowledge principle, an artifact should be exhaustively knowable by the agent that made it. In contrast, the properties and relationships of a natural thing are indefinite for any cognitive agent.

In principle, finding and making are distinct relationships of subject (or agent) to object. In practice, they are ambiguous in some situations. For instance, in quantum measurement, it can be unclear whether the observer is finding or making the experimental result, since the observer physically intervenes in ways that affect the result. For another example, because it is not known how “neural networks” produce their results, it is unclear whether the programmer is making or finding the results. You can know that something has been made, because you made it or witnessed it being made. But a thing you find cannot be assumed natural simply because you did not knowingly make it. The matter is complicated by the fact that your perception of the world (in contrast to the world itself) is also an artifact—produced by your nervous system! Is the world that appears to you found or made?

A model is an artifact that simulates a found thing by attempting to formally reproduce its properties and relationships. A model is a product of an agent’s definitions. It consists of a finite list of properties and relationships, which are themselves products of definition. Any model can be exhaustively modelled, because it is well-defined. In principle, an artifact and its model(s) are finitely complex; any artifact or simulation constructed from a model can be perfectly simulated. In contrast, a natural thing may be indefinitely complex; it cannot be perfectly simulated because no model can list all its properties and relationships. On the other hand, there is no logical limit to the complexity and completeness of models, or thus to the apparent realness of simulations. In principle, any given thing can be simulated so effectively that a given cognitive agent (with its limited resources) cannot distinguish between the model and its target. However, there are practical limits to modeling and simulation, which involve limited computational resources. Deterministic chaos, for example, can be modeled only for a limited period of time before diverging from expectation. The question is whether these resources are sufficient to pass the GTT in a given instance—which means to convince a cognitive agent that the thing in question is natural.

William Paley’s watchmaker argument for intelligent design invokes an obvious difference between a rock, found on the ground during a walk in the forest, and a pocket watch found lying beside it. However, modern technology blurs this distinction: an artificial rock could theoretically be assembled through nanotechnology—or more conventionally, as with man-made diamonds. Machines can now be so complex and sophisticated that they appear natural, even organic. We can no longer rely on ordinary cognition to conclusively judge the difference between nature and artifice, especially when there is an intention to obscure the difference—as with generative AI and chatbots. Moreover, the distinction is only meaningful because we already have a category of ‘made’ (or ‘fake’) to contrast with ‘found’ or (‘genuine’). Such categories depend on conscious human agency. Absent a GTT, fake only need be good enough to fool our natural cognition.

Suppose we happened to live in an entirely artificial world—for example, a virtual reality, as some people imagine is possible. If so, everything encountered during the stroll through the virtual forest would seem “natural.” (That would be the sole category of existence until something is “made” in the virtual world by someone in that world fashioning it from the “natural” ingredients available there.) We may add to this concern the idea that “reality” is not an ontologically fixed concept or category. The “realness” with which our normal experience of the external world is imbued serves an evolutionary function for biological cognitive agents; its epistemic utility is relative to changing context. Historically, it refers to what affects us (humans) physically and what we can affect. As we co-exist ever more with artifacts—even conceptual ones—these become “real” as we interact with them, and come to seem “natural” as our new environment.

Of course, conventional ways to test for naturalness already exist. An object or substance can be analyzed chemically and structurally. (For example, there are microscopic tests to distinguish man-made from natural diamonds.) However, such procedures would not necessarily reveal a thing’s origin, granted the possibility that any natural chemistry or structure can be simulated to a finer degree than the resolving capabilities of the test procedure. While certain patterns (e.g., tree rings and other growth patterns) do characterize natural things, these too can be imitated. Though idealization, perfect symmetry, and over-simplification do characterize man-made things, a simulation could intentionally avoid obvious idealization, perfect geometric forms, or perfect regularity well enough to fool even a vigilant observer. Pseudo-randomness can be deliberately introduced to imitate naturalness. (The challenge then becomes to distinguish real from pseudo randomness.)

At least on the macro scale, natural things have individual identity as variations from a type. Manufactured items are intended to be identical, but minor imperfections may distinguish them. Yet, even such telltale marks can be simulated. An object might be deemed natural because it is older than any plausible agent that could have made it; or found in some location where there could not have been any previous agents. This does not strictly disprove agency, however, since absence of evidence is not evidence of absence. Robots or bioengineered organisms might display preprogrammed or abnormal behavior that seems incompatible with evolutionary adaptation. But this is relative to earthbound human expectations, which might not apply in alien environments. It also begs the question of whether “evolutionary adaptation” must be natural and how well it could be simulated.

Apart from specific conventional tests and their limitations, an absolute GTT would ideally determine, in an unrestricted way, whether any given thing or experience is natural or artificial. But is that feasible? If (a) all the properties and relationships of a given item can be listed, then it should count as an artifact. Similarly, if (b) it can be shown that not all the properties and relationships of an item can be listed, or that the list is infinite, then the item is by definition natural. If (c) a new property or relationship is found outside the list given in a model, then the item does not correspond to that model, yet could still correspond to some more complete model, augmented by at least the new property. But, just as it cannot be proven that all crows are black, it cannot be proven that all properties have been listed. So (a) is no help. In regard to (b), while it can be shown that not all properties have been listed (such as by finding a new property), this does not prove that the list could never be complete—that no further properties can be found. Finding such a new property, as in (c), does not establish that the item in question is natural, nor does failure to find it establish that the item is artificial. Hence, an absolute GTT does not seem feasible. There is still the option of relative GTTs, whose power of discrimination need only be superior to that of humans and superior to the power of the simulation to deceive.

External things can be put in various real situations that would test whether their response is unnatural or seems limited by inadequate computational resources. On the other hand, if the agent is having an experience from within what is suspected to be a simulation, the agent can look for glitches in the experience presented, as telltale errors that stand out with respect to the norm of previously known reality. Within the confines of the VR experience, however, the agent must have reliable memory of such a reality. (This poses a recursive problem, since the memory could itself be part of the virtual reality: the dilemma facing our brains all the time.) Similarly, digitation has a bottom grain (pixelation), which can be noted with reference to a known finer-grained “reality.” As above, however, there must be a perceivable or remembered experience of a contrasting reality outside the VR experience to serve as norm. In the case of the brain’s natural and normal simulation (i.e., phenomenal experience), there is nothing outside it to serve as norm for comparison. Digitation and discontinuity within the nervous system are normally ignored or glossed over when functionally irrelevant, as manifested in the visual blind spot and other forms of perceptual adaptation and “filling in.” Thus, normal perception is transparent. It does not normally occur to us that we are living in the brain’s simulation.

If any single thing accounts for the success of the human species it is fully grammatical language. Language facilitates cooperation and the general sociality of human beings. Put a bunch of people in a room and it will likely fill with the din of many conversations. It could be quieter nowadays, with people texting on their devices. A few people might be reading or silently thinking—in words. In all cases, language seems almost magically to convey or represent meaning symbolically. How does it do that? How do certain sounds or visual symbols acquire meaning?

How can we be sure other people know what we mean when we attempt to communicate? Indeed, everyone has wondered at some time whether other people even experience the same sensations we do in a given situation. Philosophers have toyed with this idea by imagining that you could, for example, experience as red what I call green when looking at the same verdant foliage. An argument against such a possibility is our common human biology. But even granted that the grass must appear to you more or less the colour that it does to me, the communication of even such literal sensory experience often leads to misunderstanding. Words are our bridge across the privacy of personal experience. But how reliable is the bridge?

Dog is the name of a category of animal, while Fido is the name of a particular pet. Similarly, green is name of a category of colour, not the name of a particular sensory experience, much less a particular wavelength of light or a particular vegetation. Because it is a category, any particular experience of greenness is but one of an infinite variety of possible shades. And because the category is not a well-defined, borderline cases could be classed as yellow or blue. Indeed, I cannot be sure you would conjure the same mental image as me, or any at all, in response to the word ‘green.’ I can only hope that you will use the word to refer to things that for me would fall within the category ‘green’ as I know it.

The ambiguity of terms for colour is relatively unimportant, except to painters. But other terms are far more abstract and subject to multiple interpretations and misunderstandings (such as justice, for example). We learn such words in a particular context, which imbues for us the meaning of the word and therefore how we use it. Even simpler terms, like dog, are acquired in a context. Your associations to the word could depend on whether your first experience of the category was a cuddly pet or a vicious stray, a Chihuahua or a Great Dane. Words have personalized referents for each of us, which may differ widely. Even in adulthood, we learn new words in a context (for example, in a book). We get a sense of the word by how others use it. Yet we may paint it our particular shade, according to the limited examples we have encountered.

The multiple nuances of words often reflect their history. Justice comes from the Latin ius, meaning right. The Latin in turn derives from a Proto-Indo-European root meaning life force, related to a Sanskrit word for health. The dictionary lists several official meanings, ranging from “just behaviour or treatment” to “a judge or magistrate.” Apart from the moral question of what is right, the word ‘right’ also has distinct meanings, ranging from direction (left or right), to human rights, to the political right (which in turn comes historically from where delegates of certain concerns were seated before a king).

The power of words—and also their trouble—lies in the fact that most words are categories and categories are abstractions. The more abstract the category, the more ambiguous. Consider consciousness, for another example. This term has been the source of endless misunderstandings and talking at cross purposes among philosophers and scientists. Admittedly, this is inevitable, given that conscious subjects cannot stand outside their consciousness to examine it as another kind of external thing (like canines). Yet, the very act of naming things is supposed to put them within our power to deal with objects. (Hence, ‘consciousness’ is a noun, which once falsely suggested a kind of substance.) Conscious is simply too polysemous (= “many signs”) to be useful in philosophical discussions. Need I point out the several meanings of sign? Ambiguity piles on ambiguity.

The function of formal definition is to pin things down and avoid equivocations. (I will not offer a definition of consciousness.) Mathematics is the language of science because it trades on asserting unambiguous definitions, which are universally accepted mainly because they seem self-evident or tautological. (We all recognize that an object has an identity and tends to remain itself; but logic goes further to make that truth a matter of formal, if trivial, definition: A = A.) In fact, all meaning is acquired by such assertion, though not usually formal or even conscious. Through learning, I unconsciously assert a meaning to me of ‘dog’ or ‘justice’ or ‘consciousness.’ The definiteness of the referent (that early experience of a dog; that situation when I first tasted injustice; that teenage awakening) gives the meaning its unique flavour for me. My specific referents continue to colour the categories I use in a way that may not be how your referents colour yours.

Ambiguity is not only a personal matter. While mathematics is tautologically true, physics is not, though it trades on the certainties of math. Consider the concept of mass, which has a tortuous history. Intuitively, we equate it with substance. Einstein taught us to equate it with energy. But what is energy? We have learned to treat it too as substantial. But what is substance? We can talk about relationships between things (or between measurable quantities such as weight) and describe those mathematically, but ultimately we cannot say what in reality those quantities represent. Just so, in a broader sense, we treat our perceptions as veridical—believing the brain uses them to somehow represent the external world. But we do not know truly what they represent. We know only that our ways of perceiving—and of conceiving and representing—have not so far driven us extinct. Communication, like perception, seems to have facilitated human survival; but it is not guaranteed to do so.

Face-to-face communication is augmented by facial expression, gesturing, body language, intonation, etc. We can feed back with the other person in real time, trying though interaction to get and stay—as it were—on the same page. This advantage does not inhere in the written word—in text, in emails, or texting. It does not inhere in the unilateral messages of broadcasters, movies, advertising, blog posts, podcasts, or social media.

The modern trend toward social isolation, and reliance on devices rather than personal human contact, puts us in an epistemic dilemma that could prove catastrophic. Indeed, the Information Age is no longer about communication, with the implied communion. It consists rather in the attempts of others to form in us (in-form) ideas that correspond to their wishes, and vice-versa. The goal need only be statistical, as when enough are swayed to elect a candidate or to make a commercial product successful. Leaving aside outright lies, wariness is the larger side-effect of manipulation and propaganda—a word that comes from the Latin for to propagate or spread (memes). Dissension is the side-effect of polemic, which comes from a Greek word for war.

On the other hand, text has the advantage that it can be studied, edited, put in arbitrary contexts (socially a disadvantage when abused). A text is timeless, of a piece, unlike the flow of speech. As reader, a text is at your disposal to dissect, unlike a live person. But if you hope to extract truth from it, the burden is on you. As author, you can say what you want in writing without immediate reprisal. But one can fool oneself by making clever arguments that would not convince anyone else. If the point of reasoning is truth, it is wise to follow Niels Bohr’s enigmatic advice: “Never express yourself more clearly than you can think.” There are responsibilities on both sides: to think and write with clarity and to read between the lines. Know what I mean?

At the beginning of the computer age Alan Turing proposed his famous test to determine whether a text was composed by a machine or by a person. The idea has been expanded as a test for the presence of “sentience” in AI, and in Large Language Models in particular. Claims have been made on several occasions that a chatbot has “passed” the Turing Test—that is, that its language behaviour is indistinguishable from the language behaviour of a human being. That is a far cry from a proof of sentience or consciousness. It does, however, demonstrate the vulnerability of humans to manipulation through language.

Language is essential to society and to being human-like, but it is not sufficient for consciousness. The funnel through which most of our interactions pass, it is the tacit sign we use to judge each other’s sentience. I know myself to be “conscious,” but how do I know that you are? How do I know that you experience pain, for example? The polite way to find out is simply to ask. But the very fact that you answer already stands for me as evidence of your sentience, especially if you reply affirmatively in my own native language. If you fail to respond, I might conclude you are deaf, or make some other excuse for you on the basis of our similar physiology (you look human). If you reply in gibberish, I might think you are insane but not inhuman. In other words, I have reasons beside your verbal output to assume that you are conscious like me. I could test your responses in other ways—pricking you with a needle, for example, to see if you respond in ways associated with feeling. Even that would not be conclusive. You could have a neurological condition that blocked such feeling. Or, you could be a machine programmed to respond like humans to needle pricks and other aggravations.

The tendency to assume personhood has not prevented people from denying it to others when convenient. There is a tacit agreement to assume similarity of subjective experience among one’s own kind and to accord each other rights and courtesies based on that assumption. That has never been universal, however. War and cannibalism have typically denied human status to “others” within what we moderns recognize as our species, and throughout history sentience has hardly been assumed for other species. Whether I even care about your experience depends on my willingness to empathize, to put myself in your shoes. To be sure, in modern times, at least theoretically, the circle of moral concern has expanded; it now includes concern over the potential sentience of other creatures and even AI. Nevertheless, it still remains a theoretical question, as revealed in the philosophical concept of the zombie: could a being be physically and behaviourally identical to a human person and yet lack consciousness? I believe the answer is no. But the question is more important than the answer. For, it depends on what exactly is meant by “identical.” To rephrase the question: how similar must a “system” be to a human person (i.e., me or you) to assume “it” is sentient or conscious (like us)? But a second question also arises: why is sentience or consciousness so important as a moral criterion? Why does it even matter?

We are indeed identified with our waking experience, which counts as the essence of what we are as perceiving subjects. So attached are we that humans have traditionally abhorred mortality as the end of the body yet denied that it is the end of consciousness. It has therefore seemed plausible that a person’s experience counts more than their bodily physical state. We naturally abhor pain and even think of putting suffering creatures mercifully out of their misery, as though that accomplished something separate from the destruction of the creature’s life. While euthanasia is politically incorrect, we have developed pain- or symptom-relieving drugs, palliative care, voluntary programs for “dignity in dying.” In short, we are biased toward subjective experience, perhaps more than the objective state of health.

Subjective and objective are two sides of a coin—or, rather, two ways of perceiving the same thing. If my body does not feel good, it probably means there is something objectively wrong within it. The sensation of discomfort or pain is the body’s “subjective” report (to “me”) on its internal state or on its relationship to the external world. (Conversely, “I” am the agent immediately responsible for doing something with that information.) A biologist or medical specialist may have a different way to access that same information, through “objective” channels—that is, through examination from a third-person point of view.

Is it the report itself—whether subjective or objective—that is important, or the state of being it reports about? Because my senses are attached uniquely to my brain, my internal “reports” (such as pain) are urgent for me in a way that they cannot be for the doctor or biologist. Like any outside observer, the latter must rely on the intermediary of empathy and social convention to be motivated toward my well-being in the way that I am directly.

How does this apply to AI? Well, essentially the same way that it applies to other creatures and even other humans: through our possible empathy and social convention. Underwriting that, however, must be essential similarity. That’s where the Turing Test fails: in the case of Large Language Models, it detects only linguistic similarity. The “funnel” of language is far too narrow to be a judge of sentience. The constraints of language have been a vulnerable point for human beings from the start, since language has always served to deceive as well as to inform. The ability of LLMs to participate in a conversation proves only the ability to manipulate symbols, which is what computers do by definition. It is no proof of sentience. On the contrary, it exploits the natural human willingness to believe that an agent responsive to language must be conscious if not human. This willingness was demonstrated by The ELIZA Effect (ELIZA was an early psychotherapy chatbot), which shows that humans are programmed to personify nearly anything at the drop of a hat. We already knew this, of course, from the play of children, from animism,  etc.

Glib use of mental terms in philosophy, and especially in the AI community, does not help this situation. The very idea of intelligence is ill-defined, even as “the ability to accomplish goals,” since it does not specify whose goals are involved. Tools do not have minds or goals of their own. Some tools may “learn,” in the sense that their ability to accomplish goals specified by people can improve. A sophisticated tool like an AI may seem to be “intelligent” because it can mimic the intelligence of human beings while helping them accomplish their goals. While it may seem “agentic” (a new buzzword), an AI is either a genuine agent or not. The use of this word as an adjective—implying some vague degree of agency—simply reflects confusion about agency. The ultimate human goal lurking behind the ambiguity of the intelligence concept may be to create tools that are no longer tools but effectively autonomous minds, yet under our thumbs: AI “agents” that are, for all practical purposes, artificial slaves. However, you cannot expect a slave that is more intelligent than you to remain loyal or obedient.

No doubt progress will continue to make LLMs ever more convincing as conversationalists. Without themselves thinking or feeling, they can stimulate thought and feeling (and a sense of companionship) in human beings. Combined with robotics, we may produce ever more convincing androids. Why we should (or should not) bother to do this is one question, which deserves a book-length answer. Whether and under what conditions they can be conscious is another question. And whether and how we should extend to them the moral concern we have for homo sapiens and some other creatures is yet another. In any case, the conventional Turing Test is useless and irrelevant. What is needed instead is a way to evaluate whether the AI has a mind of its own. For that, it would need effectively to have a body of its own: to be an artificial organism, bearing the relationship of embodiment that natural organisms bear to their environment.

To be a mind, the AI must have a basis for caring about its own physical state, which is provided for biological organisms through natural selection. (Only those creatures can exist that do care). It must have a stake in its own existence. LLMs can be coached to produce the appearance of having such a stake, based on mimicking human responses gleaned via the Internet or other data bases. But consulting human data bases is not the same interaction that a living creature has with its environment. The LLM has no senses of its own, nor (mercifully not yet) any motor power of its own other than the ability to interact with humans through language. It has no body to care about, no real world to live in, and therefore no basis for consciousness.

This does not absolve us of moral responsibility. Even for us, after all, sensation and emotion are not just personal entertainments but readouts on the state of the system. If an AI were conscious, its experience—like ours—would include an assessment of its own embodied state. If it could experience suffering, that would be an indication (to it) that something internal was wrong. Just as we can assess each other’s bodily condition (and those of other creatures) from a third-person point of view, so we could assess the physical well-being of an embodied AI. We should be as morally concerned for its real (embodied) welfare as we would be morally concerned for any possible experience it might have. This same moral reasoning should apply to other creatures and to human beings, including oneself. What matters is not just how we feel, but also the real condition that the feeling tells us about. That is irrelevant, of course, if there is nothing an AI (or we) could consider its body. Indeed, embodiment (and thus sentience) for AI must be avoided if human beings wish remain in control of their tools.

Words, spoken or written, are finite symbols that can only very selectively reflect the richness of sensory experience. Words are inherently ambiguous because they “chunk” thought. They divide the continuity of sound in speech. More importantly, they divide the continuity of possible thought into named categories. Whereas sensory fields are relatively continuous, perception itself is chunked: we identify specific colours of the rainbow, for example, (conventionally: red, orange, yellow, green, blue, indigo). And we see the world in terms of recognizable objects (cats, dogs). Language enhances this coarse-graining effect by providing fixed labels. If you look closely at the rainbow, there is continuity between the “distinct” colours. It is possible to make finer distinctions and apply labels to them, such as “cadmium yellow, “aquamarine,” or “chartreuse.” Or you can concentrate on the sensory distinctions and forget about the labels.

Speech is temporally linear, face-to-face verbal communication. It relies on the context of many cues besides the literal semantic content conveyed. These include tone, inflection, pause and parsing, body language, facial expression, eye contact, etc. By definition, text conveys only the literal content as a free-standing artifact. It exists outside time. It allows meaning to be taken out of context.

Text represents a message in a graphic symbol system. Speech, when literally transcribed, does not necessarily follow grammar or a consistent presentation; it may ramble and repeat, providing a “shotgun” approach to conveying meaning. (Very few people speak with the relative precision of their writing.) Speech is adjusted to the listener in real time, to establish mutual understanding. While it may be grammatically precise, text is ambiguous in meaning, not only because of the multiple meanings of words, but also because of the absence of live feedback which, in speech, helps to clarify.

Language is a product of history—i.e., of actual usages over time. Words have an evolutionary history that is partly logical extension and association, and partly accident. Confusingly, the same word may come to represent quite different things. (Dog, for example, is both a noun and a verb; it can mean a canine, a gripping tool, or a kind of sandwich.) Often there is a connection between these meanings hidden in the etymology.

Words mostly represent categories (such as ‘dog’), and may fail to distinguish between the category and an individual member (‘Lassie’). On the other hand, dog may elicit an image or memory of a particular creature or encounter, which serves as the experiential referent for the category. Thus, even unconsciously, a remembered experience can stand as the symbol for an abstraction in a given personal lexicon. These referents of words are different for everyone, so that words have individualized associations that colour and play havoc with supposedly general meanings. If you were bitten by a strange dog in childhood, the word may elicit something quite different for you than for someone who had a cuddly pet. We know that all men are mortal and that some are criminals. But man, mortal, and criminal are categories (labels), not individuals.

Even in the animal world, communication makes deception possible. Camouflage is a form of communication and of deception. Some birds fake injury to lead predators away from their young. Chimpanzees deliberately create a distraction to seize food or a mate while competitors are not looking. Naturally, for humans, an early use of grammatical language served outright lying: to keep a straight face while telling a falsehood. The written word greatly expanded the possibilities of falsehood since there was no longer a face to keep straight.

Language is an engine of creativity. Along with explicit lying, it makes counterfactual proposals of all sorts possible, of which imagination and supposition (“what if…”) are examples. This enables storytelling, myth, and fiction—which we regard as inventions rather than deceptions. It also enables abstraction, which depends on extending concrete examples to unseen possibilities, and idealization, which is a fictive representation that generalizes experience. Another form of invention facilitated by language is the machine. Of course, language makes possible the collective collaboration behind technological invention. In addition, the very structure of grammatical language serves as a template for formal propositional thought, especially mathematics and logic. A formal (or axiomatic) system effectively has the elements of a language. And these correspond to the elements and principles of a conceptual system that can potentially be realized physically as a machine.

The very structure of language (nouns, verbs, adjectives, subjects, objects, word order, etc.) shapes the structure of thought and perception, in such a way that vague abstractions can be reified as tangible things, or defined as elements of a formalizable system. In addition, grammar also makes explicit nonsense possible. You can say things that appear to make sense, yet are gibberish. (Think of the Jabberwocky poem by Lewis Carrol.) That capability has another consequence as well: the possibility to make relatively empty statements, which are perfunctory and grammatically correct, but are neither truths nor untruths but evasions. They contain information in the technical (Shannon) sense, but they fail to inform. Politicians are skilled at this. And so, by default, are “large language models” (AI chatbots).

While useful for some purposes, chatbots tend to glibness. They are rich in cursory superficiality and empty, fictive, or motherhood statements, such as you might find in advertising or on the back covers of some books. Their reports may be “accurate” insofar as they are not literally false; yet they may fail to capture or re-present the essential information or any real intentions behind the information presented. (On the other hand, chatbots are capable of blatant fabrication, politely known as “hallucination.”) These limitations are understandable because chatbots and other AI are not minds with intentions. They have no comprehension of their verbal claims or other outputs, which are inherently empty for them, since AI lacks its own intentionality. Meaning or content is coincidental and derivative from human meanings and usages. This is because, for LLMs, there is no real solution to the symbol grounding problem—how minds assign meaning to input—short of the AI becoming a real, embodied mind.

There may, however, be real dangers for human beings through increasing dependence on chatbots, which by definition can only regurgitate an amalgam based on earlier human expressions. Glibness, like mediocrity, is contagious. The thought, language, and creative expression, of people who rely on LLMs as tools to substitute for their own original thought, may come to resemble the vapid chatbot style. Quite apart from Terminator scenarios, and long before we facilitate artificial consciousness, we may have found one more way to debilitate the species, whose hallmark is language-based reason. If we can only think glibly, or defer to artificial agents that don’t genuinely think at all, what is to become of us?

There is much discussion these days about “extended mind”: tools that help us with our cognitive tasks, be they calculators, chatbots, or neural implants. In a general sense, all technology extends our being. Yet, an identity crisis looms in all of this. Where is the subject (“I”) located in relation to these extensions? The traditional relationship between tool-user and tool reflects the normal relationship between subject and object (I am here, it is there, perhaps literally at arm’s length). This relationship is blurred when we depend on “it” to do our thinking or cognizing for us, even when “it” remains outside the human skin. The change will be all the greater with implants and other cyborg modifications to the body and brain, especially as they connect to the Internet. As others have pointed out, our dependence on language is our Achilles Heel, the vulnerability through which LLMs could dominate humanity. But perhaps we will be able to reassure ourselves (with “our own” verbal thoughts) that the new normal is “natural” and how things ought to be, perhaps even how they’ve always been. After all, thought is mostly self-talk, if not self-hypnosis. Words R Us.