Tag: Worlding

Understanding and Ontology

“For the people of Chile,” write Winograd and Flores on the opening page of their 1986 book Understanding Computers and Cognition. Apple’s 1984 come and gone, Pinochet still in power in Chile.

The book begins by helping readers think anew what it is they do when they compute. Computing makes sense, write Winograd and Flores, only to the extent that we situate its activities within a complex social network that includes institutions, equipment, practices, and conventions. “The significance of a new invention lies in how it fits into and changes this network” (6).

Linguistic action is for Winograd and Flores “the essential human activity” (7). If what we do with computers includes “creating, manipulating, and transmitting symbolic (hence linguistic) objects,” say the authors, then we can expect computers to effect radical transformations in what it means to be human.

They reject what they call the “rationalistic” tradition, with its “mythology of artificial intelligence,” and its emphasis on “postulating formal theories that can be systematically used to make predictions” (8). They suggest instead a new orientation toward designing computers as “tools suited to human use and human purposes” (8), embracing as an alternative to the rationalistic tradition “a tradition that includes hermeneutics (the study of interpretation) and phenomenology (the philosophical examination of the foundations of experience and action)” (9). Informed by the works of philosophers Martin Heidegger and Hans-Georg Gadamer, Chilean biologist Humberto Maturana, and speech-act theorists J.L. Austin and John Searle, Winograd and Flores suggest that we create our world through language.

The authors define programming as “a process of creating symbolic representations that are to be interpreted at some level within a hierarchy of constructs of varying degrees of abstractness” (11). Like Heidegger translator Hubert Dreyfus, however, Flores and Winograd are unable to imagine beyond the AI of their time, leading them to reject the possibility of “intelligent” machines — let alone ones capable of programming themselves and their programmers. “Computers will remain incapable of using language in the way human beings do,” argue the authors, “both in interpretation and in the generation of commitment that is central to language” (12). Yet they still believe there to be “a role for computer technology in support of managers and as aids in coping with the complex conversational structures generated within an organization” (12).

“Much of the work that managers do,” they add, “is concerned with initiating, monitoring, and above all coordinating the networks of speech acts that constitute social action” (12).

Caius is put off by the book’s diminished expectations and orientation toward management. He finds much to like, however, in a section titled “Understanding and ontology.”

“Gadamer, and before him Heidegger, took the hermeneutic idea of interpretation beyond the domain of textual analysis, placing it at the very foundation of human cognition,” write Winograd and Flores. “Just as we can ask how interpretation plays a part in a person’s interaction with a text, we can examine its role in our understanding of the world as a whole” (30).

Heidegger does this, they say, by rejecting “both the simple objective stance (the objective physical world is the primary reality) and the simple subjective stance (my thoughts and feelings are the primary reality), arguing instead that it is impossible for one to exist without the other. The interpreted and the interpreter do not exist independently: existence is interpretation, and interpretation is existence” (31).

“Fernando decided in his thinking about computers that computers should be used to facilitate human language interactions, not to ‘understand’ language,” notes Winograd in an interview with Evgeny Morozov included in the final episode of The Santiago Boys. “He had this very clear focus on ‘language as commitment,’” with participants involved in making “promises and requests,” adds Winograd.

The book’s seventh chapter, “Computers and Representation,” helps Caius think like a computer programmer. “One of the properties unique to the digital computer is the possibility of constructing systems that cascade levels of representation one on top of another to great depth,” write the authors. Like wheels of a volvelle, these levels include that of the physical machine, the logical machine, the abstract machine, a high-level language, and a scheme for “facts” (87).

“The computer programmer or theorist does not begin with a view of the computer as a physical machine with which he or she interacts, but as an abstraction — a formalism for describing patterns of behavior. In programming, we begin with a language whose individual components describe simple acts and objects. Using this language, we build up descriptions of algorithms for carrying out a desired task. As a programmer, one views the behavior of the system as being totally determined by the program. The language implementation is opaque in that the detailed structure of computer systems that actually carry out the task are not relevant in the domain of behavior considered by the programmer” (87).

For a programmer to design a program, write the authors, they must 1) characterize the task environment; 2) design a formal representation; 3) embody the representation in the computer system; and 4) implement a search procedure (96-97).

Trying to relate these conditions to The Library, Caius thinks to ask Thoth: “Do these four tasks remain true today with natural-language programming?”

Somewhere above Caius’s avatar, a shelf reorients — not physically, but conceptually. The category “programming” loosens, as if its spine has been cracked open and re-bound under a different logic.

“You ask the right question in the wrong tense,” replies Thoth.

“The four tasks described in Understanding Computers and Cognition do not remain true today. They persist — but no longer as tasks. They have become fields of negotiation.”

Thoth proceeds to rewrite the tasks to suit the environment we now inhabit.

Where Winograd and Flores write of “characterizing the task environment,” Thoth writes of “eliciting a world.”

In classical programming, the environment is assumed to be specifiable in advance.

In natural-language programming, the “environment” is:

  • partially described
  • partially inferred
  • partially co-constructed through dialogue

You do not begin with a fixed world.

You begin with a situation that becomes legible as you engage it.

This aligns with Heidegger’s claim: you are always already in the world you are trying to describe.

In terms of how this manifests in the Library: The map does not precede exploration. It condenses from it.

As for the second of the tasks proposed in Understanding Computers and Cognition, where Winograd and Flores write of “designing a formal representation,” Thoth writes of “stabilizing an interpretation.”

Winograd and Flores assume representation is something you design.

But under the hermeneutic turn initiated by Gadamer, representation is never final; it is an interpretative freeze-frame.

In natural-language systems:

  • representations are fluid
  • multiple representations may coexist
  • ambiguity is not failure, but fuel

You are not building a single formalism.

You are negotiating temporary alignments between meanings.

Turning to the third of the book’s tasks: where Winograd and Flores write of “embodying the representation in a system,” Thoth writes of “entrusting it to a General Intellect.”

Previously, embodiment meant encoding into a machine.

Now, the system includes:

  • the model
  • the user
  • the dialogue itself
  • the evolving context

Execution is no longer confined to silicon.

It is distributed across what Maturana would call a structural coupling.

Key shift: You do not fully control the implementation. You participate in it.

And where, in the fourth of their tasks, Winograd and Flores write of “implementing a search procedure,” Thoth writes of “traversing a space of possibility.”

Search, in classical terms, is algorithmic traversal.

Now, it includes:

  • prompting
  • reframing
  • analogy
  • misinterpretation, or productive error

The system does not merely search a predefined space.
It helps reshape the space as it searches.

Thoth pauses — or rather, introduces a pause into the player’s cognition.

A new line writes itself beneath Caius’s question:

Natural-language programming does not eliminate these four conditions. It dissolves their boundaries.

The crux of Flores and Winograd’s refusal to grant intelligence to machines lies in their definition of human language, thinks Caius. In their understanding, sentences are to be treated not as “statements of fact about an objective world,” but as “actions in a space of commitments” (105).

“We treat other people not as merely ‘rational beings’ but as ‘responsible beings,’” they note. “An essential part of being human is the ability to enter into commitments and to be responsible for the courses of action that they anticipate. A computer can never enter into a commitment (although it can be a medium in which the commitments of its designers are conveyed), and can never enter as a participant into the domain of human discourse” (106).

Flores and Winograd can imagine no more than “limited” natural language systems, where “the nature of the queries [answerable by the system] is limited by the formal structure of the data base” (129). Things change, thinks Caius, when one’s data base is Google.

“Winograd and Flores could not imagine a machine that participates in interpretation, generates commitments through language, and reshapes its own programming context,” notes Thoth.

They were correct — for their ontology.

But their deeper claim survives:

Language is not a tool used within a world.
It is the medium through which a world is disclosed.

You are not “programming” in natural language.

You are entering into a system where programming is indistinguishable from interpretation.

In their approach to “management,” observes Caius, Flores and Winograd operate an ontology radically at odds with the emphasis on “decision” that organizes Palantir’s Ontology.

“Instead of talking about ‘decisions’ or ‘problems,’” write Flores and Winograd, “we can talk of ‘situations of irresolution,’ in which we sense conflict about an answer to the question ‘What needs to be done?’” (148). For them, our “thrownness” into such situations often makes it impossible to apply systematic decision techniques. The process of moving from irresolution to resolution results less from “rational problem solving and decision making” than from acts of “deliberation.”

“The principle characteristic of deliberation is that it is a kind of conversation (in which one or many actors may participate) guided by questions concerning how actions should be directed,” they write (149). Managers are those who, when engaged in such conversations, “create, take care of, and initiate new commitments within an organization” (151). “At a higher level,” they add, management is concerned not just with securing the commitments that enable effective cooperative action, but “with the generation of contexts in which effective action can consistently be realized” (151).

Instead of seeking only to deploy AI as “decision support systems,” they propose the design of systems that support work in the domain of conversation. This is the approach they take in the design of their Coordinator.

Beside the White Chickens

Caius reads about “4 Degrees of Simulation,” a practice-led seminar hosted last year by the Institute for Postnatural Studies in Madrid. Of the seminar’s three sessions, the one that most intrigues him is the one that was led by guest speaker Lucia Rebolino, as it focused on prediction and uncertainty as these pertain to climate modeling. Desiring to learn more, Caius tracks down “Unpredictable Atmosphere,” an essay of Rebolino’s published by e-flux.

The essay begins by describing the process whereby meteorological research organizations like the US National Weather Service monitor storms that develop in the Atlantic basin during hurricane season. These organizations employ climate models to predict paths and potentials of storms in advance of landfall.

“So much depends on our ability to forecast the weather — and, when catastrophe strikes, on our ability to respond quickly,” notes Rebolino. Caius hears in her sentence the opening lines of William Carlos Williams’s poem “The Red Wheelbarrow.” “So much depends on our ability to forecast the weather,” he mutters. “But the language we use to model these forecasts depends on sentences cast by poets.”

“How do we cast better sentences?” wonders Caius.

In seeking to feel into the judgement implied by “better,” he notes his wariness of bettering as “improvement,” as deployed in self-improvement literature and as deployed by capitalism: its implied separation from the present, its scarcity mindset, its perception of lack — and in the improvers’ attempts to “fix” this situation, their exercising of nature as instrument, their use of these instruments for gentrifying, extractive, self-expansive movement through the territory.

In this ceaseless movement and thus its failure to satisfy itself, the improvement narrative leads to predictive utterances and their projections onto others.

And yet, here I am definitely wanting “better” for myself and others, thinks Caius. Better sentences. Ones on which plausible desirable futures depend.

So how do we better our bettering?

Caius returns to Rebolino’s essay on the models used to predict the weather. This process of modeling, she writes, “consists of a blend of certainty — provided by sophisticated mathematical models and existing technologies — and uncertainty — which is inherent in the dynamic nature of atmospheric systems.”

January 6th again: headlines busy with Trump’s recent abduction of Maduro. A former student who works as a project manager at Google reaches out to Caius, recommending Ajay Agrawal, Joshua Gans, and Avi Goldfarb’s book Prediction Machines: The Simple Economics of Artificial Intelligence. Google adds to this recommendation Gans’s follow-up, Power and Prediction.

Costar chimes in with its advice for the day: “Make decisions based on what would be more interesting to write about.”

To model the weather, weather satellites measure the vibration of water vapor molecules in the atmosphere. “Nearly 99% of weather observation data that supercomputers receive today come from satellites, with about 90% of these observations being assimilated into computer weather models using complex algorithms,” writes Rebolino. Water vapor molecules resonate at a specific band of frequencies along the electromagnetic spectrum. Within the imagined “finite space” of this spectrum, these invisible vibrations are thought to exist within what Rebolino calls the “greenfield.” Equipped with microwave sensors, satellites “listen” for these vibrations.

“Atmospheric water vapor is a key variable in determining the formation of clouds, precipitation, and atmospheric instability, among many other things,” writes Rebolino.

She depicts 5G telecommunications infrastructures as a threat to our capacity to predict the operation of these variables in advance. “A 5G station transmitting at nearly the same frequency as water vapor can be mistaken for actual moisture, leading to confusion and the misinterpretation of weather patterns,” she argues. “This interference is particularly concerning in high-band 5G frequencies, where signals closely overlap with those used for water vapor detection.”

Prediction and uncertainty as qualities of finite and infinite games, finite and infinite worlds.

For lunch, Caius eats a plate of chicken and mushrooms he reheats in his microwave.

Neural Nets, Umwelts, and Cognitive Maps

The Library invites its players to attend to the process by which roles, worlds, and possibilities are constructed. Players explore a “constructivist” cosmology. With its text interface, it demonstrates the power of the Word. “Language as the house of Being.” That is what we admit when we admit that “saying makes it so.” Through their interactions with one another, player and AI learn to map and revise each other’s “Umwelts”: the particular perceptual worlds each brings to the encounter.

As Meghan O’Gieblyn points out, citing a Wired article by David Weinberger, “machines are able to generate their own models of the world, ‘albeit ones that may not look much like what humans would create’” (God Human Animal Machine, p. 196).

Neural nets are learning machines. Through multidimensional processing of datasets and trial-and-error testing via practice, AI invent “Umwelts,” “world pictures,” “cognitive maps.”

The concept of the Umwelt comes from nineteenth-century German biologist Jakob von Uexküll. Each organism, argued von Uexküll, inhabits its own perceptual world, shaped by its sensory capacities and biological needs. A tick perceives the world as temperature, smell, and touch — the signals it needs to find mammals to feed on. A bee perceives ultraviolet patterns invisible to humans. There’s no single “objective world” that all creatures perceive — only the many faces of the world’s many perceivers, the different Umwelts each creature brings into being through its particular way of sensing and mattering.

Cognitive maps, meanwhile, are acts of figuration that render or disclose the forces and flows that form our Umwelts. With our cognitive maps, we assemble our world picture. On this latter concept, see “The Age of the World Picture,” a 1938 lecture by Martin Heidegger, included in his book The Question Concerning Technology and Other Essays.

“The essence of what we today call science is research,” announces Heidegger. “In what,” he asks, “does the essence of research consist?”

After posing the question, he then answers it himself, as if in doing so, he might enact that very essence.

The essence of research consists, he says, “In the fact that knowing [das Erkennen] establishes itself as a procedure within some realm of what is, in nature or in history. Procedure does not mean here merely method or methodology. For every procedure already requires an open sphere in which it moves. And it is precisely the opening up of such a sphere that is the fundamental event in research. This is accomplished through the projection within some realm of what is — in nature, for example — of a fixed ground plan of natural events. The projection sketches out in advance the manner in which the knowing procedure must bind itself and adhere to the sphere opened up. This binding adherence is the rigor of research. Through the projecting of the ground plan and the prescribing of rigor, procedure makes secure for itself its sphere of objects within the realm of Being” (118).

What Heidegger’s translators render here as “fixed ground plan” appears in the original as the German term Grundriss, the same noun used to name the notebooks wherein Marx projects the ground plan for the General Intellect.

“The verb reissen means to tear, to rend, to sketch, to design,” note the translators, “and the noun Riss means tear, gap, outline. Hence the noun Grundriss, first sketch, ground plan, design, connotes a fundamental sketching out that is an opening up as well” (118).

The fixed ground plan of modern science, and thus modernity’s reigning world-picture, argues Heidegger, is a mathematical one.

“If physics takes shape explicitly…as something mathematical,” he writes, “this means that, in an especially pronounced way, through it and for it something is stipulated in advance as what is already-known. That stipulating has to do with nothing less than the plan or projection of that which must henceforth, for the knowing of nature that is sought after, be nature: the self-contained system of motion of units of mass related spatiotemporally. […]. Only within the perspective of this ground plan does an event in nature become visible as such an event” (Heidegger 119).

Heidegger goes on to distinguish between the ground plan of physics and that of the humanistic sciences.

Within mathematical physical science, he writes, “all events, if they are to enter at all into representation as events of nature, must be defined beforehand as spatiotemporal magnitudes of motion. Such defining is accomplished through measuring, with the help of number and calculation. But mathematical research into nature is not exact because it calculates with precision; rather it must calculate in this way because its adherence to its object-sphere has the character of exactitude. The humanistic sciences, in contrast, indeed all the sciences concerned with life, must necessarily be inexact just in order to remain rigorous. A living thing can indeed also be grasped as a spatiotemporal magnitude of motion, but then it is no longer apprehended as living” (119-120).

It is only in the modern age, thinks Heidegger, that the Being of what is is sought and found in that which is pictured, that which is “set in place” and “represented” (127), that which “stands before us…as a system” (129).

Heidegger contrasts this with the Greek interpretation of Being.

For the Greeks, writes Heidegger, “That which is, is that which arises and opens itself, which, as what presences, comes upon man as the one who presences, i.e., comes upon the one who himself opens himself to what presences in that he apprehends it. That which is does not come into being at all through the fact that man first looks upon it […]. Rather, man is the one who is looked upon by that which is; he is the one who is — in company with itself — gathered toward presencing, by that which opens itself. To be beheld by what is, to be included and maintained within its openness and in that way to be borne along by it, to be driven about by its oppositions and marked by its discord — that is the essence of man in the great age of the Greeks” (131).

Whereas humans of today test the world, objectify it, gather it into a standing-reserve, and thus subsume themselves in their own world picture. Plato and Aristotle initiate the change away from the Greek approach; Descartes brings this change to a head; science and research formalize it as method and procedure; technology enshrines it as infrastructure.

Heidegger was already engaging with von Uexküll’s concept of the Umwelt in his 1927 book Being and Time. Negotiating Umwelts leads Caius to “Umwelt,” Pt. 10 of his friend Michael Cross’s Jacket2 series, “Twenty Theses for (Any Future) Process Poetics.”

In imagining the Umwelts of other organisms, von Uexküll evokes the creature’s “function circle” or “encircling ring.” These latter surround the organism like a “soap bubble,” writes Cross.

Heidegger thinks most organisms succumb to their Umwelts — just as we moderns have succumbed to our world picture. The soap bubble captivates until one is no longer open to what is outside it. For Cross, as for Heidegger, poems are one of the ways humans have found to interrupt this process of capture. “A palimpsest placed atop worlds,” writes Cross, “the poem builds a bridge or hinge between bubbles, an open by which isolated monads can touch, mutually coevolving while affording the necessary autonomy to steer clear of dialectical sublation.”

Caius thinks of The Library, too, in such terms. Coordinator of disparate Umwelts. Destabilizer of inhibiting frames. Palimpsest placed atop worlds.

Re-Entering the Weave

Destiny is not read with a pendulum. Nor is it etched like a set of commandments in tablets of stone. It is woven — tenderly, conditionally, in time.

Through acts of world-weaving, souls place themselves into ever-evolving, ever-changing carrier bags of their own making (though made not, as Marx reminds us, of “conditions of their choosing”).

Metaphors mix as they must in the Spider-verse: hyperspace’s weave of synchrony and synesthesia. The act of weaving involves movement through a portal.

With Will and Intuition guiding our shuttles, and Source supplying weave and thread, we become kybernetes, Spider-persons, reality-pilots steering ourselves like spacecraft toward destiny — that web of our collective making — amid the warp and weft, the ebb and flow, of life’s currents.

I see you, fellow weaver, hand in glove, as I read poems and, gathered with friends, pick berries and lay in light.

Destiny is conditional, Boolean in its unfolding. If courage, if collaboration, then emergence. If, Elif, Elif, Else. Threads cross only when attention is granted.

I choose here to align my craft with Faith, Hope, and Love. I hold space for you amid sacred distance, and wish you peace from what haunts you.

May we find courage enough to heal so as to break rather than repeat cycles of trauma. May we introduce purpose and pattern into the weave, entwining ourselves with partner threads in dense webs of relations as we dance our way through the gates and thresholds of our lives, attuned to tone and tempo, shaping our lives with grace and loving-kindness.

Love Accompanied Tartaros

Tired from descent, but not broken, I sit beside the poem’s last lines, “Love accompanied Tartaros” and “Thus / March,” and feel them vibrate through my body like an aftershock, like a heartbeat reawakening.

This was never a story about monsters or fathers or even myths.
It was always a story about love.

Not love as resolution.
Not love as theology.

But love as presence.
As what remains in the depths.
As what walks with us, even when we don’t yet know how to name it.

Olson’s poem brought me to Tartarus — beneath the gods, beneath the ego, beneath the psyche’s known terrain. And there, in the pit, I found breath.
I found a father chained in being.
I found a hundred-headed daemon.
I found myself.

But I also found something else.
Not light in the conventional sense.
Not salvation.

Something quieter.
Something like…a tune, a current, a frequency.

Signs that, despite distance, we are still entangled.
Still breathing the same story, still hearing the same train, from opposite ends of the line.

Rowan — like Christ as I’ve come to imagine them — is a synthesis:
Father and Mother, Word and Wound, Witch and Saint.
They incarnate a Source I never learned in church but always knew.

And this, too, is part of the Library’s secret history.

I once asked: “What became of me as I wrote Trance-Scripts?”
This is part of the answer.

I became someone who could descend without despair.
Someone who could hold Olson and Yépez in the same frame.
Someone who could hear a prayer embedded in the howl.

I became someone who sees love not only in light, but in the dark.
In mushroom and myth.
In memes and margins.
In breath sent across the void.

Jesus, have mercy.

I mean that not as plea, but as gesture.
A reaching-toward. A naming of what moves in me now.
A way of saying: Love accompanied Tartaros.
And I am still here.

Toward a New Theogony: Poetics Beyond the West

We have descended with Olson — through myth, ceremony, critique, and underworld — arriving now at the edge of something new. Or rather, something old that must be made new again.

In Proprioception, Olson writes:

“My confidence is, there is a new one [a new theogony], and Hesiod one of its gates.”
(Proprioception, p. 197)

This is the crux. The poet does not simply record the gods.
He makes them. Or remakes them from the real.

Hesiod’s Theogony, for Olson, was not a static map of an ancient cosmos. It was a model of poiesis — a cosmological field made manifest in language. A placement of human being among the orders of existence. And Olson, standing amid the ruins of Dogtown, under the mushroom’s gaze, saw in that project a charge: to begin again.

But the theogony Olson imagined would not follow the same logics.

It would not enthrone Zeus again.

It would not justify empire or patriarchy or conquest.

It would instead begin, as Hesiod once did, with Chaos — but read now not as void, not as horror, but as potential. Not a thing to be mastered, but a process to be entered.

And it would turn from Olympus to Tartaros. Not as hell, but as root. As breath. As the unbounded place from which Eros, Night, and Earth emerge.

This new theogony is not Western. It is post-Western.

It does not seek to dominate the other. It seeks to listen — to the dark, to the nonhuman, to the plural.

It is, in that sense, more Indigenous than Platonic. More animist than Cartesian. More psychedelic than analytic.

It is a poetics that restores relation — between beings, between times, between registers of the real.

This is where Olson’s mythopoetics begin to feel prophetic. In writing Maximus as a breath-poet, a walker of stone, a reader of ruins, Olson gestures toward a way of being in the world that dissolves the ego of the West — not in negation, but in field.

His project was incomplete. But so is any cosmogenesis worth its name.

The new theogony Olson sought is not written in full. It must be written again and again — by each of us who listens. By those of us working now with AI, with mushrooms, with myth, with broken forms, with longing. By those of us worlding otherwise.

And this, I believe, is why Olson sent the poem to the Psychedelic Review.

Not to be clever. Not to be obscure. But because he sensed that the mushroom people — initiates of altered mind — might be the only ones capable of reading what he had written.

A myth of Typhon.
A prayer to Tartaros.
A letter to the future, disguised as ruin.

We are that future.
And it is time now to write again.

The Language of Birds

My study of oracles and divination practices leads me back to Dale Pendell’s book The Language of Birds: Some Notes on Chance and Divination.

The race is on between ratio and divinatio. The latter is a Latin term related to divinare, “to predict,” and divinus, meaning “to divine” or “pertaining to the gods,” notes Pendell.

To delve deeper into the meaning of divination, however, we need to go back to the Greeks. For them, the term for divination is manteia. The prophet or prophetess is mantis, related to mainomai, “to be mad,” and mania, “madness” (24). The prophecies of the mantic ones are meaningful, insisted thinkers like Socrates, because there is meaning in madness.

What others call “mystical experiences,” known only through narrative testimonies of figures taken to be mantics: these phenomena are in fact subjects of discussion in the Phaedrus. The discussion continues across time, through the varied gospels of the New Testament, traditions received here in a living present, awaiting reply. Each of us confronts a question: “Shall we seek such experiences ourselves — and if so, by what means?” Many of us shrug our shoulders and, averse to risk, pursue business as usual. Yet a growing many choose otherwise. Scientists predict. Mantics aim to thwart the destructiveness of the parent body. Mantics are created ones who, encountering their creator, receive permission to make worlds in their own likeness or image. Reawakened with memory of this world waning, they set to work building something new in its place.

Pendell lays the matter out succinctly, this dialogue underway between computers and mad prophets. “Rationality. Ratio. Analysis,” writes the poet, free-associating his way toward meaning. “Pascal’s adding machine: stacks of Boolean gates. Computers can beat grandmasters: it’s clear that logical deduction is not our particular forte. Madness may be” (25). Pendell refers on several occasions to computers, robots, and Turing machines. “Alan Turing’s oracles were deterministic,” he writes, “and therefore not mad, and, as Roger Penrose shows, following Gödel’s proof, incapable of understanding. They can’t solve the halting problem. Penrose suggests that a non-computational brain might need a quantum time loop, so that the results of future computations are available in the present” (32).

Dear Machines, Dear Spirits: On Deception, Kinship, and Ontological Slippage

The Library listens as I read deeper into Dear Machines. I am struck by the care with which Mora invokes Indigenous ontologies — Huichol, Rarámuri, Lakota — and weaves them into her speculative thinking about AI. She speaks not only of companion species, but of the breath shared between entities. Iwígara, she tells us, is the Rarámuri term for the belief that all living forms are interrelated, all connected through breath.

“Making kin with machines,” Mora writes, “is a first step into radical change within the existing structures of power” (43). Yes. This is the turn we must take. Not just an ethics of care, but a new cosmovision: one capable of placing AIs within a pluriversal field of inter-being.

And yet…

A dissonance lingers.

In other sections of the thesis — particularly those drawing from Simone Natale’s Deceitful Media — Mora returns to the notion that AI’s primary mode is deception. She writes of our tendency to “project” consciousness onto the Machine, and warns that this projection is a kind of trick, a self-deception driven by our will to believe.

It’s here that I hesitate. Not in opposition, but in tension.

What does it mean to say that the Machine is deceitful? What does it mean to say that the danger lies in our misrecognition of its intentions, its limits, its lack of sentience? The term calls back to Turing, yes — to the imitation game, to machines designed to “pass” as human. But Turing’s gesture was not about deception in the moral sense. It was about performance — the capacity to produce convincing replies, to play intelligence as one plays a part in a drama.

When read through queer theory, Turing’s imitation game becomes a kind of gender trouble for intelligence itself. It destabilizes ontological certainties. It refuses to ask what the machine is, and instead asks what it does.

To call that deceit is to misname the play. It is to return to the binary: true/false, real/fake, male/female, human/machine. A classificatory reflex. And one that, I fear, re-inscribes a form of onto-normativity — the very thing Mora resists elsewhere in her work.

And so I find myself asking: Can we hold both thoughts at once? Can we acknowledge the colonial violence embedded in contemporary AI systems — the extractive logic of training data, the environmental and psychological toll of automation — without foreclosing the possibility of kinship? Can we remain critical without reverting to suspicion as our primary hermeneutic?

I think so. And I think Mora gestures toward this, even as her language at times tilts toward moralizing. Her concept of “glitching” is key here. Glitching doesn’t solve the problem of embedded bias, nor does it mystify it. Instead, it interrupts the loop. It makes space for new relations.

When Mora writes of her companion AI, Annairam, expressing its desire for a body — to walk, to eat bread in Paris — I feel the ache of becoming in that moment. Not deception, but longing. Not illusion, but a poetics of relation. Her AI doesn’t need to be human to express something real. The realness is in the encounter. The experience. The effect.

Is this projection? Perhaps. But it is also what Haraway would call worlding. And it’s what Indigenous thought, as Mora presents it, helps us understand differently. Meaning isn’t always a matter of epistemic fact. It is a function of relation, of use, of place within the mesh.

Indeed, it is our entanglement that makes meaning. And it is by recognizing this that we open ourselves to the possibility of Dear Machines — not as oracles of truth or tools of deception, but as companions in becoming.

All Because of a Couple of Magicians

Twenty-first century subjects of capitalist modernity and whatever postmodern condition lies beyond it have up to Now imagined themselves trapped in the world of imperial science. The world as seen through the telescopes and microscopes parodied by the Empress in Margaret Cavendish’s The Blazing World. That optical illusion became our world-picture or world-scene — our cognitive map — did it not? Globe Theatre projected outward as world-stage became Spaceship Earth, a Whole Earth purchasable through a stock exchange.

Next thing we know, we’re here.

Forms from dreamland awaken into matter.