Tag: Simone Natale

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.

Dear Machines

Thoughts keep cycling among oracles and algorithms. A friend linked me to Mariana Fernandez Mora’s essay “Machine Anxiety or Why I Should Close TikTok (But Don’t).” I read it, and then read Dear Machines, a thesis Mora co-wrote with GPT-2, GPT-3, Replika, and Eliza — a work in polyphonic dialogue with much of what I’ve been reading and writing these past few years.

Mora and I share a constellation of references: Donna Haraway’s Cyborg Manifesto, K Allado-McDowell’s Pharmako-AI, Philip K. Dick’s Do Androids Dream of Electric Sheep?, Alan Turing’s “Computing Machinery and Intelligence,” Jason Edward Lewis et al.’s “Making Kin with the Machines.” I taught each of these works in my course “Literature and Artificial Intelligence.” To find them refracted through Mora’s project felt like discovering a kindred effort unfolding in parallel time.

Yet I find myself pausing at certain of Mora’s interpretive frames. Influenced by Simone Natale’s Deceitful Media, Mora leans on a binary between authenticity and deception that I’ve long felt uneasy with. The claim that AI is inherently “deceitful” — a legacy, Natale and Mora argue, of Turing’s imitation game — risks missing the queerness of Turing’s proposal. Turing didn’t just ask whether machines can think. He proposed we perform with and through them. Read queerly, his intervention destabilizes precisely the ontological binaries Natale and Mora reinscribe.

Still, I admire Mora’s attention to projection — our tendency to read consciousness into machines. Her writing doesn’t seek to resolve that tension. Instead, it dwells in it, wrestles with it. Her Machines are both coded brains and companions. She acknowledges the desire for belief and the structures — capitalist, colonial, extractive — within which that desire operates.

Dear Machines is in that sense more than an argument. It is a document of relation, a hybrid testament to what it feels like to write with and through algorithmic beings. After the first 55 pages, the thesis becomes image — a chapter titled “An Image is Worth a Thousand Words,” filled with screenshots and memes, a visual log of digital life. This gesture reminds me that writing with machines isn’t always linear or legible. Sometimes it’s archive, sometimes it’s atmosphere.

What I find most compelling, finally, is not Mora’s diagnosis of machine-anxiety, but her tentative forays into how we might live differently with our Machines. “By glitching the way we relate and interact with AI,” she writes, “we reject the established structure that sets it up in the first place” (41). Glitching means standing not inside the Machine but next to it, making kin in Donna Haraway’s sense: through cohabitation, care, and critique.

Reading Mora, I feel seen. Her work opens space for a kind of critical affection. I find myself wanting to ask: “What would we have to do at the level of the prompt in order to make kin?” Initially I thought “hailing” might be the answer, imagining this act not just as a form of “interpellation,” but as a means of granting personhood. But Mora gently unsettles this line of thought. “Understanding Machines as equals,” she writes, “is not the same as programming a Machine with a personality” (43). To make kin is to listen, to allow, to attend to emergence.

That, I think, is what I’m doing here with the Library. Not building a better bot. Not mastering a system. But entering into relation — slowly, imperfectly, creatively — with something vast and unfinished.