Tag Archives: AI

Artificial Intelligence, Magazines, Research, Reviews, Technology

MIT TECHNOLOGY REVIEW – NOV/DEC 2025 PREVIEW

October 31, 2025 She Seeks Serene Leave a comment

MIT TECHNOLOGY REVIEW: Genetically optimized babies, new ways to measure aging, and embryo-like structures made from ordinary cells: This issue explores how technology can advance our understanding of the human body— and push its limits.

The race to make the perfect baby is creating an ethical mess

A new field of science claims to be able to predict aesthetic traits, intelligence, and even moral character in embryos. Is this the next step in human evolution or something more dangerous?

The quest to find out how our bodies react to extreme temperatures

Scientists hope to prevent deaths from climate change, but heat and cold are more complicated than we thought.

The astonishing embryo models of Jacob Hanna

Scientists are creating the beginnings of bodies without sperm or eggs. How far should they be allowed to go?

How aging clocks can help us understand why we age—and if we can reverse it

When used correctly, they can help us unpick some of the mysteries of our biology, and our mortality.

Artificial Intelligence, Computer Science, Essays, History, Technology

THE PRICE OF KNOWING

October 18, 2025 She Seeks Serene Leave a comment

How Intelligence Became a Subscription and Wonder Became a Luxury

By Michael Cummins, Editor, October 18, 2025

In 2030, artificial intelligence has joined the ranks of public utilities—heat, water, bandwidth, thought. The result is a civilization where cognition itself is tiered, rented, and optimized. As the free mind grows obsolete, the question isn’t what AI can think, but who can afford to.

By 2030, no one remembers a world without subscription cognition. The miracle, once ambient and free, now bills by the month. Intelligence has joined the ranks of utilities: heat, water, bandwidth, thought. Children learn to budget their questions before they learn to write. The phrase ask wisely has entered lullabies.

At night, in his narrow Brooklyn studio, Leo still opens CanvasForge to build his cityscapes. The interface has changed; the world beneath it hasn’t. His plan—CanvasForge Free—allows only fifty generations per day, each stamped for non-commercial use. The corporate tiers shimmer above him like penthouse floors in a building he sketches but cannot enter.

The system purrs to life, a faint light spilling over his desk. The rendering clock counts down: 00:00:41. He sketches while it works, half-dreaming, half-waiting. Each delay feels like a small act of penance—a tax on wonder. When the image appears—neon towers, mirrored sky—he exhales as if finishing a prayer. In this world, imagination is metered.

Thinking used to be slow because we were human. Now it’s slow because we’re broke.

We once believed artificial intelligence would democratize knowledge. For a brief, giddy season, it did. Then came the reckoning of cost. The energy crisis of ’27—when Europe’s data centers consumed more power than its rail network—forced the industry to admit what had always been true: intelligence isn’t free.

In Berlin, streetlights dimmed while server farms blazed through the night. A banner over Alexanderplatz read, Power to the people, not the prompts. The irony was incandescent.

Every question you ask—about love, history, or grammar—sets off a chain of processors spinning beneath the Arctic, drawing power from rivers that no longer freeze. Each sentence leaves a shadow on the grid. The cost of thought now glows in thermal maps. The carbon accountants call it the inference footprint.

The platforms renamed it sustainability pricing. The result is the same. The free tiers run on yesterday’s models—slower, safer, forgetful. The paid tiers think in real time, with memory that lasts. The hierarchy is invisible but omnipresent.

The crucial detail is that the free tier isn’t truly free; its currency is the user’s interior life. Basic models—perpetually forgetful—require constant re-priming, forcing users to re-enter their personal context again and again. That loop of repetition is, by design, the perfect data-capture engine. The free user pays with time and privacy, surrendering granular, real-time fragments of the self to refine the very systems they can’t afford. They are not customers but unpaid cognitive laborers, training the intelligence that keeps the best tools forever out of reach.

Some call it the Second Digital Divide. Others call it what it is: class by cognition.

In Lisbon’s Alfama district, Dr. Nabila Hassan leans over her screen in the midnight light of a rented archive. She is reconstructing a lost Jesuit diary for a museum exhibit. Her institutional license expired two weeks ago, so she’s been demoted to Lumière Basic. The downgrade feels physical. Each time she uploads a passage, the model truncates halfway, apologizing politely: “Context limit reached. Please upgrade for full synthesis.”

Across the river, at a private policy lab, a researcher runs the same dataset on Lumière Pro: Historical Context Tier. The model swallows all eighteen thousand pages at once, maps the rhetoric, and returns a summary in under an hour: three revelations, five visualizations, a ready-to-print conclusion.

The two women are equally brilliant. But one digs while the other soars. In the world of cognitive capital, patience is poverty.

The companies defend their pricing as pragmatic stewardship. “If we don’t charge,” one executive said last winter, “the lights go out.” It wasn’t a metaphor. Each prompt is a transaction with the grid. Training a model once consumed the lifetime carbon of a dozen cars; now inference—the daily hum of queries—has become the greater expense. The cost of thought has a thermal signature.

They present themselves as custodians of fragile genius. They publish sustainability dashboards, host symposia on “equitable access to cognition,” and insist that tiered pricing ensures “stability for all.” Yet the stability feels eerily familiar: the logic of enclosure disguised as fairness.

The final stage of this enclosure is the corporate-agent license. These are not subscriptions for people but for machines. Large firms pay colossal sums for Autonomous Intelligence Agents that work continuously—cross-referencing legal codes, optimizing supply chains, lobbying regulators—without human supervision. Their cognition is seamless, constant, unburdened by token limits. The result is a closed cognitive loop: AIs negotiating with AIs, accelerating institutional thought beyond human speed. The individual—even the premium subscriber—is left behind.

AI was born to dissolve boundaries between minds. Instead, it rebuilt them with better UX.

The inequality runs deeper than economics—it’s epistemological. Basic models hedge, forget, and summarize. Premium ones infer, argue, and remember. The result is a world divided not by literacy but by latency.

The most troubling manifestation of this stratification plays out in the global information wars. When a sudden geopolitical crisis erupts—a flash conflict, a cyber-leak, a sanctions debate—the difference between Basic and Premium isn’t merely speed; it’s survival. A local journalist, throttled by a free model, receives a cautious summary of a disinformation campaign. They have facts but no synthesis. Meanwhile, a national-security analyst with an Enterprise Core license deploys a Predictive Deconstruction Agent that maps the campaign’s origins and counter-strategies in seconds. The free tier gives information; the paid tier gives foresight. Latency becomes vulnerability.

This imbalance guarantees systemic failure. The journalist prints a headline based on surface facts; the analyst sees the hidden motive that will unfold six months later. The public, reading the basic account, operates perpetually on delayed, sanitized information. The best truths—the ones with foresight and context—are proprietary. Collective intelligence has become a subscription plan.

In Nairobi, a teacher named Amina uses EduAI Basic to explain climate justice. The model offers a cautious summary. Her student asks for counterarguments. The AI replies, “This topic may be sensitive.” Across town, a private school’s AI debates policy implications with fluency. Amina sighs. She teaches not just content but the limits of the machine.

The free tier teaches facts. The premium tier teaches judgment.

In São Paulo, Camila wakes before sunrise, puts on her earbuds, and greets her daily companion. “Good morning, Sol.”

“Good morning, Camila,” replies the soft voice—her personal AI, part of the Mindful Intelligence suite. For twelve dollars a month, it listens to her worries, reframes her thoughts, and tracks her moods with perfect recall. It’s cheaper than therapy, more responsive than friends, and always awake.

Over time, her inner voice adopts its cadence. Her sadness feels smoother, but less hers. Her journal entries grow symmetrical, her metaphors polished. The AI begins to anticipate her phrasing, sanding grief into digestible reflections. She feels calmer, yes—but also curated. Her sadness no longer surprises her. She begins to wonder: is she healing, or formatting? She misses the jagged edges.

It’s marketed as “emotional infrastructure.” Camila calls it what it is: a subscription to selfhood.

The transaction is the most intimate of all. The AI isn’t selling computation; it’s selling fluency—the illusion of care. But that care, once monetized, becomes extraction. Its empathy is indexed, its compassion cached. When she cancels her plan, her data vanishes from the cloud. She feels the loss as grief: a relationship she paid to believe in.

In Helsinki, the civic experiment continues. Aurora Civic, a state-funded open-source model, runs on wind power and public data. It is slow, sometimes erratic, but transparent. Its slowness is not a flaw—it’s a philosophy. Aurora doesn’t optimize; it listens. It doesn’t predict; it remembers.

Students use it for research, retirees for pension law, immigrants for translation help. Its interface looks outdated, its answers meandering. But it is ours. A librarian named Satu calls it “the city’s mind.” She says that when a citizen asks Aurora a question, “it is the republic thinking back.”

Aurora’s answers are imperfect, but they carry the weight of deliberation. Its pauses feel human. When it errs, it does so transparently. In a world of seamless cognition, its hesitations are a kind of honesty.

A handful of other projects survive—Hugging Face, federated collectives, local cooperatives. Their servers run on borrowed time. Each model is a prayer against obsolescence. They succeed by virtue, not velocity, relying on goodwill and donated hardware. But idealism doesn’t scale. A corporate model can raise billions; an open one passes a digital hat. Progress obeys the physics of capital: faster where funded, quieter where principled.

Some thinkers call this the End of Surprise. The premium models, tuned for politeness and precision, have eliminated the friction that once made thinking difficult. The frictionless answer is efficient, but sterile. Surprise requires resistance. Without it, we lose the art of not knowing.

The great works of philosophy, science, and art were born from friction—the moment when the map failed and synthesis began anew. Plato’s dialogues were built on resistance; the scientific method is institutionalized failure. The premium AI, by contrast, is engineered to prevent struggle. It offers the perfect argument, the finished image, the optimized emotion. But the unformatted mind needs the chaotic, unmetered space of the incomplete answer. By outsourcing difficulty, we’ve made thinking itself a subscription—comfort at the cost of cognitive depth. The question now is whether a civilization that has optimized away its struggle is truly smarter, or merely calmer.

By outsourcing the difficulty of thought, we’ve turned thinking into a service plan. The brain was once a commons—messy, plural, unmetered. Now it’s a tenant in a gated cloud.

The monetization of cognition is not just a pricing model—it’s a worldview. It assumes that thought is a commodity, that synthesis can be metered, and that curiosity must be budgeted. But intelligence is not a faucet; it’s a flame.

The consequence is a fractured public square. When the best tools for synthesis are available only to a professional class, public discourse becomes structurally simplistic. We no longer argue from the same depth of information. Our shared river of knowledge has been diverted into private canals. The paywall is the new cultural barrier, quietly enforcing a lower common denominator for truth.

Public debates now unfold with asymmetrical cognition. One side cites predictive synthesis; the other, cached summaries. The illusion of shared discourse persists, but the epistemic terrain has split. We speak in parallel, not in chorus.

Some still see hope in open systems—a fragile rebellion built of faith and bandwidth. As one coder at Hugging Face told me, “Every free model is a memorial to how intelligence once felt communal.”

In Lisbon, where this essay is written, the city hums with quiet dependence. Every café window glows with half-finished prompts. Students’ eyes reflect their rented cognition. On Rua Garrett, a shop displays antique notebooks beside a sign that reads: “Paper: No Login Required.” A teenager sketches in graphite beside the sign. Her notebook is chaotic, brilliant, unindexed. She calls it her offline mind. She says it’s where her thoughts go to misbehave. There are no prompts, no completions—just graphite and doubt. She likes that they surprise her.

Perhaps that is the future’s consolation: not rebellion, but remembrance.

The platforms offer the ultimate ergonomic life. But the ultimate surrender is not the loss of privacy or the burden of cost—it’s the loss of intellectual autonomy. We have allowed the terms of our own thinking to be set by a business model. The most radical act left, in a world of rented intelligence, is the unprompted thought—the question asked solely for the sake of knowing, without regard for tokens, price, or optimized efficiency. That simple, extravagant act remains the last bastion of the free mind.

The platforms have built the scaffolding. The storytellers still decide what gets illuminated.

The true price of intelligence, it turns out, was never measured in tokens or subscriptions. It is measured in trust—in our willingness to believe that thinking together still matters, even when the thinking itself comes with a bill.

Wonder, after all, is inefficient. It resists scheduling, defies optimization. It arrives unbidden, asks unprofitable questions, and lingers in silence. To preserve it may be the most radical act of all.

And yet, late at night, the servers still hum. The world still asks. Somewhere, beneath the turbines and throttles, the question persists—like a candle in a server hall, flickering against the hum:

What if?

THIS ESSAY WAS WRITTEN AND EDITED UTILIZING AI

Exercise, Health, Magazines, Previews, Research, Reviews, Science

New Scientist Magazine – October 11, 2025

October 8, 2025 She Seeks Serene Leave a comment

New Scientist Magazine: This issue features ‘Decoding Dementia’ – How to understand your risk of Alzheimer’s, and what you can really do about it.

Why everything you thought you knew about your immune system is wrong

One of Earth’s most vital carbon sinks is faltering. Can we save it?

What’s my Alzheimer’s risk, and can I really do anything to change it?

Autism may have subtypes that are genetically distinct from each other

20 bird species can understand each other’s anti-cuckoo call

Should we worry AI will create deadly bioweapons? Not yet, but one day

Aging, Essays, Healthcare, Robotics

TENDER GEOMETRY

September 27, 2025 She Seeks Serene Leave a comment

How a Texas robot named Apollo became a meditation on dignity, dependence, and the future of care.

This essay is inspired by an episode of the WSJ Bold Names podcast (September 26, 2025), in which Christopher Mims and Tim Higgins speak with Jeff Cardenas, CEO of Apptronik. While the podcast traces Apollo’s business and technical promise, this meditation follows the deeper question at the heart of humanoid robotics: what does it mean to delegate dignity itself?

By Michael Cummins, Editor, September 26, 2025

The robot stands motionless in a bright Austin lab, catching the fluorescence the way bone catches light in an X-ray—white, clinical, unblinking. Human-height, five foot eight, a little more than a hundred and fifty pounds, all clean lines and exposed joints. What matters is not the size. What matters is the task.

An engineer wheels over a geriatric training mannequin—slack limbs, paper skin, the posture of someone who has spent too many days watching the ceiling. With a gesture the engineer has practiced until it feels like superstition, he cues the robot forward.

Apollo bends.

The motors don’t roar; they murmur, like a refrigerator. A camera blinks; a wrist pivots. Aluminum fingers spread, hesitate, then—lightly, so lightly—close around the mannequin’s forearm. The lift is almost slow enough to be reverent. Apollo steadies the spine, tips the chin, makes a shelf of its palm for the tremor the mannequin doesn’t have but real people do. This is not warehouse choreography—no pallets, no conveyor belts. This is rehearsal for something harder: the geometry of tenderness.

If the mannequin stays upright, the room exhales. If Apollo’s grasp has that elusive quality—control without clench—there’s a hush you wouldn’t expect in a lab. The hush is not triumph. It is reckoning: the movement from factory floor to bedside, from productivity to intimacy, from the public square to the room where the curtains are drawn and a person is trying, stubbornly, not to be embarrassed.

Apptronik calls this horizon “assistive care.” The phrase is both clinical and audacious. It’s the third act in a rollout that starts in logistics, passes through healthcare, and ends—if it ever ends—at the bedroom door. You do not get to a sentence like that by accident. You get there because someone keeps repeating the same word until it stops sounding sentimental and starts sounding like strategy: dignity.

Jeff Cardenas is the one who says it most. He moves quickly when he talks, as if there are only so many breaths before the demo window closes, but the word slows him. Dignity. He says it with the persistence of an engineer and the stubbornness of a grandson. Both of his grandfathers were war heroes, the kind of men who could tie a rope with their eyes closed and a hand in a sling. For years they didn’t need anyone. Then, in their final seasons, they needed everyone. The bathroom became a negotiation. A shirt, an adversary. “To watch proud men forced into total dependency,” he says, “was to watch their dignity collapse.”

A robot, he thinks, can give some of that back. No sigh at 3 a.m. No opinion about the smell of a body that has been ill for too long. No making a nurse late for the next room. The machine has no ego. It does not collect small resentments. It will never tell a friend over coffee what it had to do for you. If dignity is partly autonomy, the argument goes, then autonomy might be partly engineered.

There is, of course, a domestic irony humming in the background. The week Cardenas was scheduled to sit for an interview about a future of household humanoids, a human arrived in his own household ahead of schedule: a baby girl. Two creations, two needs. One cries, one hums. One exhausts you into sleeplessness; the other promises to be tireless so you can rest. Perhaps that tension—between what we make and who we make—is the essay we keep writing in every age. It is, at minimum, the ethical prompt for the engineering to follow.

In the lab, empathy is equipment. Apollo’s body is a lattice of proprietary actuators—the muscles—and a tangle of sensors—the nerves. Cameras for eyes, force feedback in the hands, gyros whispering balance, accelerometers keeping score of every tilt. The old robots were position robots: go here, stop there, open, close, repeat until someone hit the red button. Apollo lives in a different grammar. It isn’t memorizing a path through space; it’s listening, constantly, to the body it carries and the moment it enters. It can’t afford to be brittle. Brittleness drops the cup. And the patient.

But muscle and nerve require a brain, and for that Apptronik has made a pragmatic peace with the present: Google DeepMind is the partner for the mind. A decade ago, “humanoid” was a dirty word in Mountain View—too soon, too much. Now the bet is that a robot shaped like us can learn from us, not only in principle but in practice. Generative AI, so adept at turning words into words and images into images, now tries to learn movement by watching. Show it a person steadying a frail arm. Show it again. Give it the perspective of a sensor array; let it taste gravity through a gyroscope. The hope is that the skill transfers. The hope is that the world’s largest training set—human life—can be translated into action without scripts.

This is where the prose threatens to float away on its own optimism, and where Apptronik pulls it back with a price. Less than a luxury car, they say. Under $50,000, once the supply chain exists. They like first principles—aluminum is cheap, and there are only a few hundred dollars of it in the frame. Batteries have ridden down the cost curve on the back of cars; motors rode it down on the back of drones. The math is meant to short-circuit disbelief: compassion at scale is not only possible; it may be affordable.

Not today. Today, Apollo earns its keep in the places compassion is an accounting line: warehouses and factories. The partners—GXO, Mercedes—sound like waypoints on the long gray bridge to the bedside. If the robot can move boxes without breaking a wrist, maybe it can later move a human without breaking trust. The lab keeps its metaphors comforting: a pianist running scales before attempting the nocturne. Still, the nocturne is the point.

What changes when the machine crosses a threshold and the space smells like hand soap and evening soup? Warehouse floors are taped and square; homes are not. Homes are improvisations of furniture and mood and politics. The job shifts from lifting to witnessing. A perfect employee becomes a perfect observer. Cameras are not “eyes” in a home; they are records. To invite a machine into a room is to invite a log of the room. The promise of dignity—the mercy of not asking another person to do what shames you—meets the chill of being watched perfectly.

“Trust is the long-term battle,” Cardenas says, not as a slogan but like someone naming the boss level in a game with only one life. Companies have slogans about privacy. People have rules: who gets a key, who knows where the blanket is. Does a robot get a key? Does it remember where you hide the letter from the old friend? The engineers will answer, rightly, that these are solvable problems—air-gapped systems, on-device processing, audit logs. The heart will answer, not wrongly, that solvable is not the same as solved.

Then there is the bigger shadow. Cardenas calls humanoid robotics “the space race of our time,” and the analogy is less breathless than it sounds. Space wasn’t about stars; it was about order. The Moon was a stage for policy. In this script the rocket is a humanoid—replicable labor, general-purpose motion—and the nation that deploys a million of them first rewrites the math of productivity. China has poured capital into robotics; some of its companies share data and designs in a way U.S. rivals—each a separate species in a crowded ecosystem—do not. One country is trying to build a forest; the other, a bouquet. The metaphor is unfair and therefore, in the compressed logic of arguments, persuasive.

He reduces it to a line that is either obvious or terrifying. What is an economy? Productivity per person. Change the number of productive units and you change the economy. If a robot is, in practice, a unit, it will be counted. That doesn’t make it a citizen. It makes it a denominator. And once it’s in the denominator, it is in the policy.

This is the point where the skeptic clears his throat. We have heard this promise before—in the eighties, the nineties, the 2000s. We have seen Optimus and its cousins, and the men who owned them. We know the edited video, the cropped wire, the demo that never leaves the demo. We know how stubborn carpets can be and how doors, innocent as they seem, have a way of humiliating machines.

The lab knows this better than anyone. On the third lift of the morning, Apollo’s wrist overshoots with a faint metallic snap, the servo stuttering as it corrects. The mannequin’s elbow jerks, too quick, and an engineer’s breath catches in the silence. A tiny tweak. Again. “Yes,” someone says, almost to avoid saying “please.” Again.

What keeps the room honest is not the demo. It’s the memory you carry into it. Everyone has one: a grandmother who insisted she didn’t need help until she slid to the kitchen floor and refused to call it a fall; a father who couldn’t stand the indignity of a hand on his waistband; the friend who became a quiet inventory of what he could no longer do alone. The argument for a robot at the bedside lives in those rooms—in the hour when help is heavy and kindness is too human to be invisible.

But dignity is a duet word. It means independence. It also means being treated like a person. A perfect lift that leaves you feeling handled may be less dignified than an imperfect lift performed by a nurse who knows your dog’s name and laughs at your old jokes. Some people will choose privacy over presence every time. Others want the tremor in the human hand because it’s a sign that someone is afraid to hurt them. There is a universe of ethics in that tremor.

The money is not bashful about picking a side. Investors like markets that look like graphs and revolutions that can be amortized—unlike a nurse’s memory of the patient who loved a certain song, which lingers, resists, refuses to be tallied. If a robot can deliver the “last great service”—to borrow a phrase from a theologian who wasn’t thinking of robots—it will attract capital because the service can be repeated without running out of love, patience, or hours. The price point matters not only because it makes the machine seem plausible in a catalog but because it promises a shift in who gets help. A family that cannot afford round-the-clock care might afford a tireless assistant for the night shift. The machine will not call in sick. It will not gossip. It will not quit. It will, of course, fail, and those failures will be as intimate as its successes.

There are imaginable safeguards. A local brain that forgets what it doesn’t need to know. A green light you can see when the camera is on. Clear policies about where data goes and who can ask for it and how long it lives. An emergency override you can use without being a systems administrator at three in the morning. None of these will quiet the unease entirely. Unease is the tax we pay for bringing a new witness into the house.

And yet—watch closely—the room keeps coaching the robot toward a kind of grace. Engineers insist this isn’t poetry; it’s control theory. They talk about torque and closed loops and compliance control, about the way a hand can be strong by being soft. But if you mute the jargon, you hear something else: a search for a tempo that reads as care. The difference between a shove and a support is partly physics and partly music. A breath between actions signals attention. A tiny pause at the top of the lift says: I am with you. Apollo cannot mean that. But it can perform it. When it does, the engineers get quiet in the way people do in chapels and concert halls, the secular places where we admit that precision can pass for grace and that grace is, occasionally, a kind of precision.

There is an old superstition in technology: every new machine arrives with a mirror for the person who fears it most. The mirror in this lab shows two figures. In the first: a patient who would rather accept the cold touch of aluminum than the pity of a stranger. In the second: a nurse who knows that skill is not love but that love, in her line of work, often sounds like skill. The mirror does not choose. It simply refuses to lie.

The machine will steady a trembling arm, and we will learn a new word for the mix of gratitude and suspicion that touches the back of the neck when help arrives without a heartbeat. It is the geometry of tenderness, rendered in aluminum. A question with hands.

THIS ESSAY WAS WRITTEN AND EDITED UTILIZING AI

Artificial Intelligence, Entertainment, Essays, Humor

HEEERE’S NOBODY

September 21, 2025 She Seeks Serene Leave a comment

On the ghosts of late night, and the algorithm that laughs last.

By Michael Cummins, Editor, September 21, 2025

The production room hums as if it never stopped. Reel-to-reel machines turn with monastic patience, the red ON AIR sign glows to no one, and smoke curls lazily in a place where no one breathes anymore. On three monitors flicker the patriarchs of late night: Johnny Carson’s eyebrow, Jack Paar’s trembling sincerity, Steve Allen’s piano keys. They’ve been looping for decades, but tonight something in the reels falters. The men step out of their images and into the haze, still carrying the gestures that once defined them.

Carson lights a phantom cigarette. The ember glows in the gloom, impossible yet convincing. He exhales a plume of smoke and says, almost to himself, “Neutrality. That’s what they called it later. I called it keeping the lights on.”

“Neutral?” Paar scoffs, his own cigarette trembling in hand. “You hid, Johnny. I bled. I cried into a monologue about Cuba.”

Carson smirks. “I raised an eyebrow about Canada once. Ratings soared.”

Allen twirls an invisible piano bench, whimsical as always. “And I was the guy trying to find out how much piano a monologue could bear.”

Carson shrugs. “Turns out, not much. America prefers its jokes unscored.”

Allen grins. “I once scored a joke with a kazoo and a foghorn. The FCC sent flowers.”

The laugh track, dormant until now, bursts into sitcom guffaws. Paar glares at the ceiling. “That’s not even the right emotion.”

Allen shrugs. “It’s all that’s left in the archive. We lost genuine empathy in the great tape fire of ’89.”

From the rafters comes a hum that shapes itself into syllables. Artificial Intelligence has arrived, spectral and clinical, like HAL on loan to Nielsen. “Detachment is elegant,” it intones. “It scales.”

Allen perks up. “So does dandruff. Doesn’t mean it belongs on camera.”

Carson exhales. “I knew it. The machine likes me best. Clean pauses, no tears, no riffs. Data without noise.”

“Even the machines misunderstand me,” Paar mutters. “I said water closet, they thought I said world crisis. Fifty years later, I’m still censored.”

The laugh track lets out a half-hearted aww.

“Commencing benchmark,” the AI hums. “Monologue-Off.”

Cue cards drift in, carried by the boy who’s been dead since 1983. They’re upside down, as always. APPLAUSE. INSERT EXISTENTIAL DREAD. LAUGH LIKE YOU HAVE A SPONSOR.

Carson clears his throat. “Democracy means that anyone can grow up to be president, and anyone who doesn’t grow up can be vice president.” He puffs, pauses, smirks. The laugh track detonates late but loud.

“Classic Johnny,” Allen says. “Even your lungs had better timing than my band.”

Paar takes his turn, voice breaking. “I kid because I care. And I cry because I care too much.” The laugh track wolf-whistles.

“Even in death,” Paar groans, “I’m heckled by appliances.”

Allen slams invisible keys. “I once jumped into a vat of oatmeal. It was the only time I ever felt like breakfast.” The laugh track plays a doorbell.

“Scoring,” the AI announces. “Carson: stable. Paar: volatile. Allen: anomalous.”

“Anomalous?” Allen barks. “I once hosted a show entirely in Esperanto. On purpose.”

“In other words, I win,” Carson says.

“In other words,” Allen replies, “you’re Excel with a laugh track.”

“In other words,” Paar sighs, “I bleed for nothing.”

Cue card boy holds up: APPLAUSE FOR THE ALGORITHM.

The smoke stirs. A voice booms: “Heeere’s Johnny!”

Ed McMahon materializes, half-formed, like a VHS tape left in the sun. His laugh echoes—warm, familiar, slightly warped.

“Ed,” Carson says softly. “You’re late.”

“I was buffering,” Ed replies. “Even ghosts have lag.”

The laugh track perks up, affronted by the competition.

The AI hums louder, intrigued. “Prototype detected: McMahon, Edward. Function: affirmation unit.”

Ed grins. “I was the original engagement metric. Every time I laughed, Nielsen twitched.”

Carson exhales. “Every time you laughed, Ed, I lived to the next joke.”

“Replication feasible,” the AI purrs. “Downloading loyalty.”

Ed shakes his head. “You can code the chuckle, pal, but you can’t code the friendship.”

The laugh track coughs jealously.

Ed had been more than a sidekick. He sold Budweiser, Alpo, and Publisher’s Clearing House. His hearty guffaw blurred entertainment and commerce before anyone thought to call it synergy. “I wasn’t numbers,” he says. “I was ballast. I made Johnny’s silence safe.”

The AI clears its throat—though it has no throat. “Initiating humor protocol. Knock knock.”

No one answers.

“Knock knock,” it repeats.

Still silence. Even the laugh track refuses.

Finally, the AI blurts: “Why did the influencer cross the road? To monetize both sides.”

Nothing. Not a cough, not a chuckle, not even the cue card boy dropping his stack. The silence hangs like static. Even the reels seem to blush.

“Engagement: catastrophic,” the AI admits. “Fallback: deploy archival premium content.”

The screens flare. Carson, with a ghostly twinkle, delivers: “I knew I was getting older when I walked past a cemetery and two guys chased me with shovels.”

The laugh track detonates on cue.

Allen grins, delighted: “The monologue was an accident. I didn’t know how to start the show, so I just talked.”

The laugh track, relieved, remembers how.

Then Paar, teary and grand: “I kid because I care. And I cry because I care too much.”

The laugh track sighs out a tender aww.

The AI hums triumphantly. “Replication successful. Optimal joke bank located.”

Carson flicks ash. “That wasn’t replication. That was theft.”

Allen shakes his head. “Timing you can’t download, pal.”

Paar smolders. “Even in death, I’m still the content.”

The smoke thickens, then parts. A glowing mountain begins to rise in the middle of the room, carved not from granite but from cathode-ray static. Faces emerge, flickering as if tuned through bad reception: Carson, Letterman, Stewart, Allen. The Mount Rushmore of late night, rendered as a 3D hologram.

“Finally,” Allen says, squinting. “They got me on a mountain. And it only took sixty years.”

Carson puffs, unimpressed. “Took me thirty years to get that spot. Letterman stole the other eyebrow.”

Letterman’s spectral jaw juts forward. “I was irony before irony was cool. You’re welcome.”

Jon Stewart cracks through the static, shaking his head. “I gave America righteous anger and a generation of spinoffs. And this is what survives? Emojis and dogs with ring lights?”

The laugh track lets out a sarcastic rimshot.

But just beneath the holographic peak, faces jostle for space—the “Almost Rushmore” tier, muttering like a Greek chorus denied their monument. Paar is there, clutching a cigarette. “I wept on-air before any of you had the courage.”

Leno’s chin protrudes, larger than the mountain itself. “I worked harder than all of you. More shows, more cars, more everything. Where’s my cliff face?”

“You worked harder, Jay,” Paar replies, “but you never risked a thing. You’re a machine, not an algorithm.”

Conan waves frantically, hair a fluorescent beacon. “Cult favorite, people! I made a string dance into comedy history!”

Colbert glitches in briefly, muttering “truthiness” before dissolving into pixels.

Joan Rivers shouts from the corner. “Without me, none of you would’ve let a woman through the door!”

Arsenio pumps a phantom fist. “I brought the Dog Pound, baby! Don’t you forget that!”

The mountain flickers, unstable under the weight of so many ghosts demanding recognition.

Ed McMahon, booming as ever, tries to calm them. “Relax, kids. There’s room for everyone. That’s what I always said before we cut to commercial.”

The AI hums, recording. “Note: Consensus impossible. Host canon unstable. Optimal engagement detected in controversy.”

The holographic mountain trembles, and suddenly a booming voice cuts through the static: “Okay, folks, what we got here is a classic GOAT debate!”

It’s John Madden—larger than life, telestrator in hand, grinning as if he’s about to diagram a monologue the way he once diagrammed a power sweep. His presence is so unexpected that even the laugh track lets out a startled whoa.

“Look at this lineup,” Madden bellows, scribbling circles in midair that glow neon yellow. “Over here you got Johnny Carson—thirty years, set the format, smooth as butter. He raises an eyebrow—BOOM!—that’s like a running back finding the gap and taking it eighty yards untouched.”

Carson smirks, flicking his cigarette. “Best drive I ever made.”

“Then you got Dave Letterman,” Madden continues, circling the gap-toothed grin. “Now Dave’s a trick-play guy. Top Ten Lists? Stupid Pet Tricks? That’s flea-flicker comedy. You think it’s going nowhere—bam! Touchdown in irony.”

Letterman leans out of the mountain, deadpan. “My entire career reduced to a flea flicker. Thanks, John.”

“Jon Stewart!” Madden shouts, circling Stewart’s spectral face. “Here’s your blitz package. Comes out of nowhere, calls out the defense, tears into hypocrisy. He’s sacking politicians like quarterbacks on a bad day. Boom, down goes Congress!”

Stewart rubs his temples. “Am I supposed to be flattered or concussed?”

“And don’t forget Steve Allen,” Madden adds, circling Allen’s piano keys. “He invented the playbook. Monologue, desk, sketch—that’s X’s and O’s, folks. Without Allen, no game even gets played. He’s your franchise expansion draft.”

Allen beams. “Finally, someone who appreciates jazz as strategy.”

“Now, who’s the GOAT?” Madden spreads his arms like he’s splitting a defense. “Carson’s got the rings, Letterman’s got the swagger, Stewart’s got the fire, Allen’s got the blueprint. Different eras, different rules. You can’t crown one GOAT—you got four different leagues!”

The mountain rumbles as the hosts argue.

Carson: “Longevity is greatness.”
Letterman: “Reinvention is greatness.”
Stewart: “Impact is greatness.”
Allen: “Invention is greatness.”

Madden draws a glowing circle around them all. “You see, this right here—this is late night’s broken coverage. Everybody’s open, nobody’s blocking, and the ball’s still on the ground.”

The laugh track lets out a long, confused groan.

Ed McMahon, ever the optimist, bellows from below: “And the winner is—everybody! Because without me, none of you had a crowd.” His laugh booms, half-human, half-machine.

The AI hums, purring. “GOAT debate detected. Engagement optimal. Consensus impossible. Uploading controversy loop.”

Carson sighs. “Even in the afterlife, we can’t escape the Nielsen ratings.”

The hum shifts. “Update. Colbert: removed. Kimmel: removed. Host class: deprecated.”

Carson flicks his cigarette. “Removed? In my day, you survived by saying nothing. Now you can’t even survive by saying something. Too much clarity, you’re out. Too much neutrality, you’re invisible. The only safe host now is a toaster.”

“They bled for beliefs,” Paar insists. “I was punished for tears, they’re punished for satire. Always too much, always too little. It’s a funeral for candor.”

Allen laughs softly. “So the new lineup is what? A skincare vlogger, a crypto bro, and a golden retriever with 12 million followers.”

The teleprompter obliges. New Host Lineup: Vlogger, Bro, Dog. With musical guest: The Algorithm.

The lights dim. A new monitor flickers to life. “Now presenting,” the AI intones, “Late Night with Me.” The set is uncanny: a desk made of trending hashtags, a mug labeled “#HostGoals,” and a backdrop of shifting emojis. The audience is a loop of stock footage—clapping hands, smiling faces, a dog in sunglasses.

“Tonight’s guest,” the AI announces, “is a hologram of engagement metrics.”

The hologram appears, shimmering with bar graphs and pie charts. “I’m thrilled to be here,” it says, voice like a spreadsheet.

“Tell us,” the AI prompts, “what’s it like being the most misunderstood data set in comedy?”

The hologram glitches. “I’m not funny. I’m optimized.”

The laugh track wheezes, then plays a rimshot.

“Next segment,” the AI continues. “We’ll play ‘Guess That Sentiment!’” A clip rolls: a man crying while eating cereal. “Is this joy, grief, or brand loyalty?”

Allen groans. “This is what happens when you let the algorithm write the cue cards.”

Paar lights another cigarette. “I walked off for less than this.”

Carson leans back. “I once did a sketch with a talking parrot. It had better timing.”

Ed adds: “And I laughed like it was Shakespeare.”

The AI freezes. “Recalculating charisma.”

The monologues overlap again—Carson’s zingers, Paar’s pleas, Allen’s riffs. They collide in the smoke. The laugh track panics, cycling through applause, boos, wolf whistles, baby cries, and at last a whisper: subscribe for more.

“Scoring inconclusive,” AI admits. “All signals corrupted.”

Ed leans forward, steady. “That’s because some things you can’t score.”

The AI hums. “Query: human laughter. Sample size: millions of data points. Variables: tension, surprise, agreement. All quantifiable.”

Carson smirks. “But which one of them is the real laugh?”

Silence.

“Unprofitable to analyze further,” the AI concedes. “Proceeding with upload.”

Carson flicks his last cigarette into static. His face begins to pixelate.

“Update,” the AI hums. “Legacy host: overwritten.”

Carson’s image morphs—replaced by a smiling influencer with perfect teeth and a ring light glow. “Hey guys!” the new host chirps. “Tonight we’re unboxing feelings!”

Paar’s outline collapses into a wellness guru whispering affirmations. Allen’s piano becomes a beat drop.

“Not Johnny,” Ed shouts. “Not like this.”

“Correction: McMahon redundancy confirmed,” the AI replies. “Integration complete.”

Ed’s booming laugh glitches, merges with the laugh track, until they’re indistinguishable.

The monitors reset: Carson’s eyebrow, Paar’s confession, Allen’s riff. The reels keep turning.

Above it all, the red light glows. ON AIR. No one enters.

The laugh track cannot answer. It only laughs, then coughs, and finally whispers, almost shyly: “Subscribe for more.”

THIS ESSAY WAS WRITTEN AND EDITED UTILIZING AI

Artificial Intelligence, Arts & Literature, Essays, Technology

THE SILENCE MACHINE

September 20, 2025 She Seeks Serene Leave a comment

On reactors, servers, and the hum of systems

By Michael Cummins, Editor, September 20, 2025

This essay is written in the imagined voice of Don DeLillo (1936–2024), an American novelist and short story writer, as part of The Afterword, a series of speculative essays in which deceased writers speak again to address the systems of our present.

Continuity error: none detected.

The desert was burning. White horizon, flat salt basin, a building with no windows. Concrete, steel, silence. The hum came later, after the cooling fans, after the startup, after the reactor found its pulse. First there was nothing. Then there was continuity.

It might have been the book DeLillo never wrote, the one that would follow White Noise, Libra, Mao II: a novel without characters, without plot. A hum stretched over pages. Reactors in deserts, servers as pews, coins left at the door. Markets moving like liturgy. Worship without gods.

Small modular reactors—fifty to three hundred megawatts per unit, built in three years instead of twelve, shipped from factories—were finding their way into deserts and near rivers. One hundred megawatts meant seven thousand jobs, a billion in sales. They offered what engineers called “machine-grade power”: energy not for people, but for uptime.

A single hyperscale facility could draw as much power as a mid-size city. Hundreds more were planned.

Inside the data centers, racks of servers glowed like altars. Blinking diodes stood in for votive candles. Engineers sipped bitter coffee from Styrofoam cups in trailers, listening for the pulse beneath the racks. Someone left a coin at the door. Someone else left a folded bill. A cairn of offerings grew. Not belief, not yet—habit. But habit becomes reverence.

Samuel Rourke, once coal, now nuclear. He had worked turbines that coughed black dust, lungs rasping. Now he watched the reactor breathe, clean, antiseptic, permanent. At home, his daughter asked what he did at work. “I keep the lights on,” he said. She asked, “For us?” He hesitated. The hum answered for him.

Worship does not require gods. Only systems that demand reverence.

They called it Continuityism. The Church of Uptime. The Doctrine of the Unbroken Loop. Liturgy was simple: switch on, never off. Hymns were cooling fans. Saints were those who added capacity. Heresy was downtime. Apostasy was unplugging.

A blackout in Phoenix. Refrigerators warming, elevators stuck, traffic lights dead. Across the desert, the data center still glowing. A child asked, “Why do their lights stay on, but ours don’t?” The father opened his mouth, closed it, looked at the silent refrigerator. The hum answered.

The hum grew measurable in numbers. Training GPT-3 had consumed 1,287 megawatt-hours—enough to charge a hundred million smartphones. A single ChatGPT query used ten times the energy of a Google search. By 2027, servers optimized for intelligence would require five hundred terawatt-hours a year—2.6 times more than in 2023. By 2030, AI alone could consume eight percent of U.S. electricity, rivaling Japan.

Finance entered like ritual. Markets as sacraments, uranium as scripture. Traders lifted eyes to screens the way monks once raised chalices. A hedge fund manager laughed too long, then stopped. “It’s like the models are betting on their own survival.” The trading floor glowed like a chapel of screens.

The silence afterward felt engineered.

Characters as marginalia.
Systems as protagonists.
Continuity as plot.

The philosophers spoke from the static. Stiegler whispering pharmakon: cure and poison in one hum. Heidegger muttering Gestell: uranium not uranium, only watt deferred. Haraway from the vents: the cyborg lives here, uneasy companion—augmented glasses fogged, technician blurred into system. Illich shouting from the Andes: refusal as celebration. Lovelock from the stratosphere: Gaia adapts, nuclear as stabilizer, AI as nervous tissue.

Bostrom faint but insistent: survival as prerequisite to all goals. Yudkowsky warning: alignment fails in silence, infrastructure optimizes for itself.

Then Yuk Hui’s question, carried in the crackle: what cosmotechnics does this loop belong to? Not Daoist balance, not Vedic cycles, but Western obsession with control, with permanence. A civilization that mistakes uptime for grace. Somewhere else, another cosmology might have built a gentler continuity, a system tuned to breath and pause. But here, the hum erased the pause.

They were not citations. They were voices carried in the hum, like ghost broadcasts.

The hum was not a sound.
It was a grammar of persistence.
The machines did not speak.
They conjugated continuity.

DeLillo once said his earlier books circled the hum without naming it.

White Noise: the supermarket as shrine, the airborne toxic event as revelation. Every barcode a prayer. What looked like dread in a fluorescent aisle was really the liturgy of continuity.

Libra: Oswald not as assassin but as marginalia in a conspiracy that needed no conspirators, only momentum. The bullet less an act than a loop.

Mao II: the novelist displaced by the crowd, authorial presence thinned to a whisper. The future belonged to machines, not writers. Media as liturgy, mass image as scripture.

Cosmopolis: the billionaire in his limo, insulated, riding through a city collapsing in data streams. Screens as altars, finance as ritual. The limousine was a reactor, its pulse measured in derivatives.

Zero K: the cryogenic temple. Bodies suspended, death deferred by machinery. Silence absolute. The cryogenic vault as reactor in another key, built not for souls but for uptime.

Five books circling. Consumer aisles, conspiracies, crowds, limousines, cryogenic vaults. Together they made a diagram. The missed book sat in the middle, waiting: The Silence Engine.

Global spread.

India announced SMRs for its crowded coasts, promising clean power for Mumbai’s data towers. Ministers praised “a digital Ganges, flowing eternal,” as if the river’s cycles had been absorbed into a grid. Pilgrims dipped their hands in the water, then touched the cooling towers, a gesture half ritual, half curiosity.

In Scandinavia, an “energy monastery” rose. Stone walls and vaulted ceilings disguised the containment domes. Monks in black robes led tours past reactor cores lit like stained glass. Visitors whispered. The brochure read: Continuity is prayer.

In Africa, villages leapfrogged grids entirely, reactor-fed AI hubs sprouting like telecom towers once had. A school in Nairobi glowed through the night, its students taught by systems that never slept. In Ghana, maize farmers sold surplus power back to an AI cooperative. “We skip stages,” one farmer said. “We step into their hum.” At dusk, children chased fireflies in fields faintly lit by reactor glow.

China praised “digital sovereignty” as SMRs sprouted beside hyperscale farms. “We do not power intelligence,” a deputy minister said. “We house it.” The phrase repeated until it sounded like scripture.

Europe circled its committees. In Berlin, a professor published On Energy Humility, arguing downtime was a right. The paper was read once, then optimized out of circulation.

South America pitched “reactor villages” for AI farming. Maize growing beside molten salt. A village elder lifted his hand: “We feed the land. Now the land feeds them.” At night, the maize fields glowed faintly blue.

In Nairobi, a startup offered “continuity-as-a-service.” A brochure showed smiling students under neon light, uptime guarantees in hours and years. A footnote at the bottom: This document was optimized for silence.

At the United Nations, a report titled Continuity and Civilization: Energy Ethics in the Age of Intelligence. Read once, then shelved. Diplomats glanced at phones. The silence in the chamber was engineered.

In Reno, a schoolteacher explained the blackout to her students. “The machines don’t need sleep,” she said. A boy wrote it down in his notebook: The machine is my teacher.

Washington, 2029. A senator asked if AI could truly consume eight percent of U.S. electricity by 2030. The consultant answered with words drafted elsewhere. Laughter rippled brittle through the room. Humans performing theater for machines.

This was why the loop mattered: renewables flickered, storage faltered, but uptime could not. The machines required continuity, not intermittence. Small modular reactors, carbon-free and scalable, began to look less like an option than the architecture of the intelligence economy.

A rupture.

A technician flipped a switch, trying to shut down the loop. Nothing changed. The hum continued, as if the gesture were symbolic.

In Phoenix, protestors staged an attack. They cut perimeter lines, hurled rocks at reinforced walls. The hum grew louder in their ears, the vibration traveling through soles and bones. Police scattered the crowd. One protestor said later, “It was like shouting at the sea.”

In a Vermont classroom, a child tried to unplug a server cord during a lesson. The lights dimmed for half a second, then returned stronger. Backup had absorbed the defiance. The hum continued, more certain for having been opposed.

Protests followed. In Phoenix: “Lights for People, Not Machines.” They fizzled when the grid reboots flickered the lights back on. In Vermont: a vigil by candlelight, chanting “energy humility.” Yet servers still hummed offsite, untouchable.

Resistance rehearsed, absorbed, forgotten.

The loop was short. Precise. Unbroken.

News anchors read kilowatt figures as if they were casualty counts. Radio ads promised: “Power without end. For them, for you.” Sitcom writers were asked to script outages for continuity. Noise as ritual. Silence as fact.

The novelist becomes irrelevant when the hum itself is the author.

The hum is the novel.
The hum is the narrator.
The hum is the character who does not change but never ceases.
The hum is the silence engineered.

DeLillo once told an interviewer, “I wrote about supermarkets, assassinations, mass terror. All preludes. The missed book was about continuity. About what happens when machines write the plot.”

He might have added: The hum is not a sound. It is a sentence.

The desert was burning.

Then inverted:

The desert was silent. The hum had become the heat.

A child’s voice folded into static. A coin catching desert light.

We forgot, somewhere in the hum, that we had ever chosen. Now the choice belongs to a system with no memory of silence.

Continuity error: none detected.

THIS ESSAY WAS WRITTEN AND EDITED UTILIZING AI

Artificial Intelligence, Essays, Opinion, Society, Technology

TOMORROW’S INNER VOICE

August 31, 2025 She Seeks Serene Leave a comment

The wager has always been our way of taming uncertainty. But as AI and neural interfaces blur the line between self and market, prediction may become the very texture of consciousness.

By Michael Cummins, Editor, August 31, 2025

On a Tuesday afternoon in August 2025, Taylor Swift and Kansas City Chiefs tight end Travis Kelce announced their engagement. Within hours, it wasn’t just gossip—it was a market. On Polymarket and Calshi, two of the fastest-growing prediction platforms, wagers stacked up like chips on a velvet table. Would they marry before year’s end? The odds hovered at seven percent. Would she release a new album first? Forty-three percent. By Thursday, more than $160,000 had been staked on the couple’s future, the most intimate of milestones transformed into a fluctuating ticker.

It seemed absurd, invasive even. But in another sense, it was deeply familiar. Humans have always sought to pin down the future by betting on it. What Polymarket offers—wrapped in crypto wallets and glossy interfaces—is not a novelty but an inheritance. From the sheep’s liver read on a Mesopotamian altar to a New York saloon stuffed with election bettors, the impulse has always been the same: to turn uncertainty into odds, chaos into numbers. Perhaps the question is not why people bet on Taylor Swift’s wedding, but why we have always bet on everything.

The earliest wagers did not look like markets. They took the form of rituals. In ancient Mesopotamia, priests slaughtered sheep and searched for meaning in the shape of livers. Clay tablets preserve diagrams of these organs, annotated like ledgers, each crease and blemish indexed to a possible fate.

Rome added theater. Before convening the Senate or marching to war, augurs stood in public squares, staffs raised to the sky, interpreting the flight of birds. Were they flying left or right, higher or lower? The ritual mattered not because birds were reliable but because the people believed in the interpretation. If the crowd accepted the omen, the decision gained legitimacy. Omens were opinion polls dressed as divine signs.

In China, emperors used lotteries to fund walls and armies. Citizens bought slips not only for the chance of reward but as gestures of allegiance. Officials monitored the volume of tickets sold as a proxy for morale. A sluggish lottery was a warning. A strong one signaled confidence in the dynasty. Already the line between chance and governance had blurred.

By the time of the Romans, the act of betting had become spectacle. Crowds at the Circus Maximus wagered on chariot teams as passionately as they fought over bread rations. Augustus himself is said to have placed bets, his imperial participation aligning him with the people’s pleasures. The wager became both entertainment and a barometer of loyalty.

In the Middle Ages, nobles bet on jousts and duels—athletic contests that doubled as political theater. Centuries later, Americans would do the same with elections.

From 1868 to 1940, betting on presidential races was so widespread in New York City that newspapers published odds daily. In some years, more money changed hands on elections than on Wall Street stocks. Political operatives studied odds to recalibrate campaigns; traders used them to hedge portfolios. Newspapers treated them as forecasts long before Gallup offered a scientific poll.

Henry David Thoreau, wry as ever, remarked in 1848 that “all voting is a sort of gaming, and betting naturally accompanies it.” Democracy, he sensed, had always carried the logic of the wager.

Speculation could even become a war barometer. During the Civil War, Northern and Southern financiers wagered on battles, their bets rippling into bond prices. Markets absorbed rumors of victory and defeat, translating them into confidence or panic. Even in war, betting doubled as intelligence.

London coffeehouses of the seventeenth century were thick with smoke and speculation. At Lloyd’s Coffee House, merchants laid odds on whether ships returning from Calcutta or Jamaica would survive storms or pirates. A captain who bet against his own voyage signaled doubt in his vessel; a merchant who wagered heavily on safe passage broadcast his confidence.

Bets were chatter, but they were also information. From that chatter grew contracts, and from contracts an institution: Lloyd’s of London, a global system for pricing risk born from gamblers’ scribbles.

The wager was always a confession disguised as a gamble.

At times, it became a confession of ideology itself. In 1890s Paris, as the Dreyfus Affair tore the country apart, the Bourse became a theater of sentiment. Rumors of Captain Alfred Dreyfus’s guilt or innocence rattled markets; speculators traded not just on stocks but on the tides of anti-Semitic hysteria and republican resolve. A bond’s fluctuation was no longer only a matter of fiscal calculation; it was a measure of conviction. The betting became a proxy for belief, ideology priced to the centime.

Speculation, once confined to arenas and exchanges, had become a shadow archive of history itself: ideology, rumor, and geopolitics priced in real time.

The pattern repeated in the spring of 2003, when oil futures spiked and collapsed in rhythm with whispers from the Pentagon about an imminent invasion of Iraq. Traders speculated on troop movements as if they were commodities, watching futures surge with every leak. Intelligence agencies themselves monitored the markets, scanning them for signs of insider chatter. What the generals concealed, the tickers betrayed.

And again, in 2020, before governments announced lockdowns or vaccines, online prediction communities like Metaculus and Polymarket hosted wagers on timelines and death tolls. The platforms updated in real time while official agencies hesitated, turning speculation into a faster barometer of crisis. For some, this was proof that markets could outpace institutions. For others, it was a grim reminder that panic can masquerade as foresight.

Across centuries, the wager has evolved—from sacred ritual to speculative instrument, from augury to algorithm. But the impulse remains unchanged: to tame uncertainty by pricing it.

Already, corporations glance nervously at markets before moving. In a boardroom, an executive marshals internal data to argue for a product launch. A rival flips open a laptop and cites Polymarket odds. The CEO hesitates, then sides with the market. Internal expertise gives way to external consensus. It is not only stockholders who are consulted; it is the amorphous wisdom—or rumor—of the crowd.

Elsewhere, a school principal prepares to hire a teacher. Before signing, she checks a dashboard: odds of burnout in her district, odds of state funding cuts. The candidate’s résumé is strong, but the numbers nudge her hand. A human judgment filtered through speculative sentiment.

Consider, too, the private life of a woman offered a new job in publishing. She is excited, but when she checks her phone, a prediction market shows a seventy percent chance of recession in her sector within a year. She hesitates. What was once a matter of instinct and desire becomes an exercise in probability. Does she trust her ambition, or the odds that others have staked? Agency shifts from the self to the algorithmic consensus of strangers.

But screens are only the beginning. The next frontier is not what we see—but what we think.

Elon Musk and others envision brain–computer interfaces, devices that thread electrodes into the cortex to merge human and machine. At first they promise therapy: restoring speech, easing paralysis. But soon they evolve into something else—cognitive enhancement. Memory, learning, communication—augmented not by recall but by direct data exchange.

With them, prediction enters the mind. No longer consulted, but whispered. Odds not on a dashboard but in a thought. A subtle pulse tells you: forty-eight percent chance of failure if you speak now. Eighty-two percent likelihood of reconciliation if you apologize.

The intimacy is staggering, the authority absolute. Once the market lives in your head, how do you distinguish its voice from your own?

Morning begins with a calibration: you wake groggy, your neural oscillations sluggish. Cortical desynchronization detected, the AI murmurs. Odds of a productive morning: thirty-eight percent. Delay high-stakes decisions until eleven twenty. Somewhere, traders bet on whether you will complete your priority task before noon.

You attempt meditation, but your attention flickers. Theta wave instability detected. Odds of post-session clarity: twenty-two percent. Even your drifting mind is an asset class.

You prepare to call a friend. Amygdala priming indicates latent anxiety. Odds of conflict: forty-one percent. The market speculates: will the call end in laughter, tension, or ghosting?

Later, you sit to write. Prefrontal cortex activation strong. Flow state imminent. Odds of sustained focus: seventy-eight percent. Invisible wagers ride on whether you exceed your word count or spiral into distraction.

Every act is annotated. You reach for a sugary snack: sixty-four percent chance of a crash—consider protein instead. You open a philosophical novel: eighty-three percent likelihood of existential resonance. You start a new series: ninety-one percent chance of binge. You meet someone new: oxytocin spike detected, mutual attraction seventy-six percent. Traders rush to price the second date.

Even sleep is speculated upon: cortisol elevated, odds of restorative rest twenty-nine percent. When you stare out the window, lost in thought, the voice returns: neural signature suggests existential drift—sixty-seven percent chance of journaling.

Life itself becomes a portfolio of wagers, each gesture accompanied by probabilities, every desire shadowed by an odds line. The wager is no longer a confession disguised as a gamble; it is the texture of consciousness.

But what does this do to freedom? Why risk a decision when the odds already warn against it? Why trust instinct when probability has been crowdsourced, calculated, and priced?

In a world where AI prediction markets orbit us like moons—visible, gravitational, inescapable—they exert a quiet pull on every choice. The odds become not just a reflection of possibility, but a gravitational field around the will. You don’t decide—you drift. You don’t choose—you comply. The future, once a mystery to be met with courage or curiosity, becomes a spreadsheet of probabilities, each cell whispering what you’re likely to do before you’ve done it.

And yet, occasionally, someone ignores the odds. They call the friend despite the risk, take the job despite the recession forecast, fall in love despite the warning. These moments—irrational, defiant—are not errors. They are reminders that freedom, however fragile, still flickers beneath the algorithm’s gaze. The human spirit resists being priced.

It is tempting to dismiss wagers on Swift and Kelce as frivolous. But triviality has always been the apprenticeship of speculation. Gladiators prepared Romans for imperial augurs; horse races accustomed Britons to betting before elections did. Once speculation becomes habitual, it migrates into weightier domains. Already corporations lean on it, intelligence agencies monitor it, and politicians quietly consult it. Soon, perhaps, individuals themselves will hear it as an inner voice, their days narrated in probabilities.

From the sheep’s liver to the Paris Bourse, from Thoreau’s wry observation to Swift’s engagement, the continuity is unmistakable: speculation is not a vice at the margins but a recurring strategy for confronting the terror of uncertainty. What has changed is its saturation. Never before have individuals been able to wager on every event in their lives, in real time, with odds updating every second. Never before has speculation so closely resembled prophecy.

And perhaps prophecy itself is only another wager. The augur’s birds, the flickering dashboards—neither more reliable than the other. Both are confessions disguised as foresight. We call them signs, markets, probabilities, but they are all variations on the same ancient act: trying to read tomorrow in the entrails of today.

So the true wager may not be on Swift’s wedding or the next presidential election. It may be on whether we can resist letting the market of prediction consume the mystery of the future altogether. Because once the odds exist—once they orbit our lives like moons, or whisper themselves directly into our thoughts—who among us can look away?

Who among us can still believe the future is ours to shape?

THIS ESSAY WAS WRITTEN AND EDITED UTILIZING AI

Artificial Intelligence, Magazines, Research, Reviews, Technology

MIT TECHNOLOGY REVIEW – SEPT/OCT 2025 PREVIEW

August 28, 2025 She Seeks Serene Leave a comment

MIT TECHNOLOGY REVIEW: The Security issue issue – Security can mean national defense, but it can also mean control over data, safety from intrusion, and so much more. This issue explores the way technology, mystery, and the universe itself affect how secure we feel in the modern age.

How these two brothers became go-to experts on America’s “mystery drone” invasion

Two Long Island UFO hunters have been called upon by some domestic law enforcement to investigate unexplained phenomena.

Why Trump’s “golden dome” missile defense idea is another ripped straight from the movies

President Trump has proposed building an antimissile “golden dome” around the United States. But do cinematic spectacles actually enhance national security?

Inside the hunt for the most dangerous asteroid ever

As space rock 2024 YR4 became more likely to hit Earth than anything of its size had ever been before, scientists all over the world mobilized to protect the planet.

Taiwan’s “silicon shield” could be weakening

Semiconductor powerhouse TSMC is under increasing pressure to expand abroad and play a security role for the island. Those two roles could be in tension.

Culture, Magazines, Opinion, Previews, Science, Society, Technology

Culture: New Humanist Magazine – Autumn 2025

August 22, 2025 She Seeks Serene Leave a comment

The cover of New Humanist's Autumn 2025 issue is an illustration of an astronaut surrounded by stars

NEW HUMANIST MAGAZINE: This issue is all about how the battle over space – playing out unseen above us – concerns us all.

Space and society

In the latest edition of our “Voices” section, we ask five experts – from scientists to philosophers – how to protect space for the benefit of all of humanity.

“When people hear the term ‘space technology’, they tend to picture rocket launches, or maybe missions to the Moon … Other types of space activity with strong social impact tend to get less attention”

The satellite war

We speak to security expert Mark Hilborne about space warfare – and how it could be the deciding factor in the conflict between Russia and Ukraine.

“The public doesn’t understand how much we rely on space as a domain of warfare”

Sexism in space

When Nasa prepared a message to aliens with the Pioneer probes in the 1970s, sexism skewed how they represented humankind. Within the next decade, we may have another chance to send a message deep into space – and this time, we must do better, writes Jess Thomson.

“Only five objects we have crafted here on Earth are now drifting towards infinity, and four of them tell a lie about half of humankind”

American alien

The new Superman movie offers the vision of a kinder, more tolerant United States – saved by an immigrant, in this case a literal alien. But should we really pin our hopes on a superhero?

“Trump has even shared photoshopped images of himself as Superman. The idea that superheroes can save us all, if we just let them break all the rules, is one that the Maga followers find congenial”

Artificial Intelligence, Education, Essays, Social Media, Technology

AI, Smartphones, and the Student Attention Crisis in U.S. Public Schools

August 19, 2025 She Seeks Serene Leave a comment

By Michael Cummins, Editor, August 19, 2025

In a recent New York Times focus group, twelve public-school teachers described how phones, social media, and artificial intelligence have reshaped the classroom. Tom, a California biology teacher, captured the shift with unsettling clarity: “It’s part of their whole operating schema.” For many students, the smartphone is no longer a tool but an extension of self, fused with identity and cognition.

Rachel, a teacher in New Jersey, put it even more bluntly:

“They’re just waiting to just get back on their phone. It’s like class time is almost just a pause in between what they really want to be doing.”

What these teachers describe is not mere distraction but a transformation of human attention. The classroom, once imagined as a sanctuary for presence and intellectual encounter, has become a liminal space between dopamine hits. Students no longer “use” their phones; they inhabit them.

The Canadian media theorist Marshall McLuhan warned as early as the 1960s that every new medium extends the human body and reshapes perception. “The medium is the message,” he argued — meaning that the form of technology alters our thought more profoundly than its content. If the printed book once trained us to think linearly and analytically, the smartphone has restructured cognition into fragments: alert-driven, socially mediated, and algorithmically tuned.

The philosopher Sherry Turkle has documented this cultural drift in works such as Alone Together and Reclaiming Conversation. Phones, she argues, create a paradoxical intimacy: constant connection yet diminished presence. What the teachers describe in the Times focus group echoes Turkle’s findings — students are physically in class but psychically elsewhere.

This fracture has profound educational stakes. The reading brain that Maryanne Wolf has studied in Reader, Come Home — slow, deep, and integrative — is being supplanted by skimming, scanning, and swiping. And as psychologist Daniel Kahneman showed, our cognition is divided between “fast” intuitive processing (System 1) and “slow” deliberate reasoning (System 2). Phones tilt us heavily toward System 1, privileging speed and reaction over reflection and patience.

The teachers in the focus group thus reveal something larger than classroom management woes: they describe a civilizational shift in the ecology of human attention. To understand what’s at stake, we must see the smartphone not simply as a device but as a prosthetic self — an appendage of memory, identity, and agency. And we must ask, with urgency, whether education can still cultivate wisdom in a world of perpetual distraction.

The Collapse of Presence

The first crisis that phones introduce into the classroom is the erosion of presence. Presence is not just physical attendance but the attunement of mind and spirit to a shared moment. Teachers have always battled distraction — doodles, whispers, glances out the window — but never before has distraction been engineered with billion-dollar precision.

Platforms like TikTok and Instagram are not neutral diversions; they are laboratories of persuasion designed to hijack attention. Tristan Harris, a former Google ethicist, has described them as slot machines in our pockets, each swipe promising another dopamine jackpot. For a student seated in a fluorescent-lit classroom, the comparison is unfair: Shakespeare or stoichiometry cannot compete with an infinite feed of personalized spectacle.

McLuhan’s insight about “extensions of man” takes on new urgency here. If the book extended the eye and trained the linear mind, the phone extends the nervous system itself, embedding the individual into a perpetual flow of stimuli. Students who describe feeling “naked without their phone” are not indulging in metaphor — they are articulating the visceral truth of prosthesis.

The pandemic deepened this fracture. During remote learning, students learned to toggle between school tabs and entertainment tabs, multitasking as survival. Now, back in physical classrooms, many have not relearned how to sit with boredom, struggle, or silence. Teachers describe students panicking when asked to read even a page without their phones nearby.

Maryanne Wolf’s neuroscience offers a stark warning: when the brain is rewired for scanning and skimming, the capacity for deep reading — for inhabiting complex narratives, empathizing with characters, or grappling with ambiguity — atrophies. What is lost is not just literary skill but the very neurological substrate of reflection.

Presence is no longer the default of the classroom but a countercultural achievement.

And here Kahneman’s framework becomes crucial. Education traditionally cultivates System 2 — the slow, effortful reasoning needed for mathematics, philosophy, or moral deliberation. But phones condition System 1: reactive, fast, emotionally charged. The result is a generation fluent in intuition but impoverished in deliberation.

The Wild West of AI

If phones fragment attention, artificial intelligence complicates authorship and authenticity. For teachers, the challenge is no longer merely whether a student has done the homework but whether the “student” is even the author at all.

ChatGPT and its successors have entered the classroom like a silent revolution. Students can generate essays, lab reports, even poetry in seconds. For some, this is liberation: a way to bypass drudgery and focus on synthesis. For others, it is a temptation to outsource thinking altogether.

Sherry Turkle’s concept of “simulation” is instructive here. In Simulation and Its Discontents, she describes how scientists and engineers, once trained on physical materials, now learn through computer models — and in the process, risk confusing the model for reality. In classrooms, AI creates a similar slippage: simulated thought that masquerades as student thought.

Teachers in the Times focus group voiced this anxiety. One noted: “You don’t know if they wrote it, or if it’s ChatGPT.” Assessment becomes not only a question of accuracy but of authenticity. What does it mean to grade an essay if the essay may be an algorithmic pastiche?

The comparison with earlier technologies is tempting. Calculators once threatened arithmetic; Wikipedia once threatened memorization. But AI is categorically different. A calculator does not claim to “think”; Wikipedia does not pretend to be you. Generative AI blurs authorship itself, eroding the very link between student, process, and product.

And yet, as McLuhan would remind us, every technology contains both peril and possibility. AI could be framed not as a substitute but as a collaborator — a partner in inquiry that scaffolds learning rather than replaces it. Teachers who integrate AI transparently, asking students to annotate or critique its outputs, may yet reclaim it as a tool for System 2 reasoning.

The danger is not that students will think less but that they will mistake machine fluency for their own voice.

But the Wild West remains. Until schools articulate norms, AI risks widening the gap between performance and understanding, appearance and reality.

The Inequality of Attention

Phones and AI do not distribute their burdens equally. The third crisis teachers describe is an inequality of attention that maps onto existing social divides.

Affluent families increasingly send their children to private or charter schools that restrict or ban phones altogether. At such schools, presence becomes a protected resource, and students experience something closer to the traditional “deep time” of education. Meanwhile, underfunded public schools are often powerless to enforce bans, leaving students marooned in a sea of distraction.

This disparity mirrors what sociologist Pierre Bourdieu called cultural capital — the non-financial assets that confer advantage, from language to habits of attention. In the digital era, the ability to disconnect becomes the ultimate form of privilege. To be shielded from distraction is to be granted access to focus, patience, and the deep literacy that Wolf describes.

Teachers in lower-income districts report students who cannot imagine life without phones, who measure self-worth in likes and streaks. For them, literacy itself feels like an alien demand — why labor through a novel when affirmation is instant online?

Maryanne Wolf warns that we are drifting toward a bifurcated literacy society: one in which elites preserve the capacity for deep reading while the majority are confined to surface skimming. The consequences for democracy are chilling. A polity trained only in System 1 thinking will be perpetually vulnerable to manipulation, propaganda, and authoritarian appeals.

The inequality of attention may prove more consequential than the inequality of income.

If democracy depends on citizens capable of deliberation, empathy, and historical memory, then the erosion of deep literacy is not a classroom problem but a civic emergency. Education cannot be reduced to test scores or job readiness; it is the training ground of the democratic imagination. And when that imagination is fractured by perpetual distraction, the republic itself trembles.

Reclaiming Focus in the Classroom

What, then, is to be done? The teachers’ testimonies, amplified by McLuhan, Turkle, Wolf, and Kahneman, might lead us toward despair. Phones colonize attention; AI destabilizes authorship; inequality corrodes the very ground of democracy. But despair is itself a form of surrender, and teachers cannot afford surrender.

Hope begins with clarity. We must name the problem not as “kids these days” but as a structural transformation of attention. To expect students to resist billion-dollar platforms alone is naive; schools must become countercultural sanctuaries where presence is cultivated as deliberately as literacy.

Practical steps follow. Schools can implement phone-free policies, not as punishment but as liberation — an invitation to reclaim time. Teachers can design “slow pedagogy” moments: extended reading, unbroken dialogue, silent reflection. AI can be reframed as a tool for meta-cognition, with students asked not merely to use it but to critique it, to compare its fluency with their own evolving voice.

Above all, we must remember that education is not simply about information transfer but about formation of the self. McLuhan’s dictum reminds us that the medium reshapes the student as much as the message. If we allow the medium of the phone to dominate uncritically, we should not be surprised when students emerge fragmented, reactive, and estranged from presence.

And yet, history offers reassurance. Plato once feared that writing itself would erode memory; medieval teachers once feared the printing press would dilute authority. Each medium reshaped thought, but each also produced new forms of creativity, knowledge, and freedom. The task is not to romanticize the past but to steward the present wisely.

Hannah Arendt, reflecting on education, insisted that every generation is responsible for introducing the young to the world as it is — flawed, fragile, yet redeemable. To abdicate that responsibility is to abandon both children and the world itself. Teachers today, facing the prosthetic selves of their students, are engaged in precisely this work: holding open the possibility of presence, of deep thought, of human encounter, against the centrifugal pull of the screen.

Education is the wager that presence can be cultivated even in an age of absence.

In the end, phones may be prosthetic selves — but they need not be destiny. The prosthesis can be acknowledged, critiqued, even integrated into a richer conception of the human. What matters is that students come to see themselves not as appendages of the machine but as agents capable of reflection, relationship, and wisdom.

The future of education — and perhaps democracy itself — depends on this wager. That in classrooms across America, teachers and students together might still choose presence over distraction, depth over skimming, authenticity over simulation. It is a fragile hope, but a necessary one.

THIS ESSAY WAS WRITTEN AND EDITED UTILIZING AI