The Quiet Gifts of AI

 

                                    Why the most meaningful benefits are the hardest to notice.

Across the public conversation about AI, fear dominates the emotional landscape. People imagine disruption, displacement, and instability—roles dissolving, workflows collapsing, identities becoming unmoored. These fears are not unreasonable; they reflect genuine decoherence events, moments when the structures that once held our lives together lose stability before new ones have fully formed.

Yet this is only half of the story.

What rarely receives attention are the subtle coherence gains—those quiet, cumulative expansions of clarity, flow, creativity, and agency that become possible when AI is used not to replace human effort but to deepen it. When engaged as a collaborator rather than a threat, AI becomes a coherence technology, a force that restores cognitive harmony in a world increasingly engineered toward distraction and fragmentation.

I have experienced this directly in both my teaching and my multi-media storytelling. The contrast between my pre-AI and post-AI life is not measured in productivity metrics or efficiency curves; it is felt at the ontological level, in the way my days hold together, the way my work aligns with my values, and the way I inhabit my creative identity. This is what the public conversation overlooks: the quiet gifts—the coherence gains—that accumulate when AI is woven thoughtfully into the architecture of one’s life.

The essential question, then, is not whether AI will eliminate jobs. The deeper question is whether AI will help us reorganize our lives toward greater coherence, or whether fear will keep us bound to patterns that are already failing us.

 

The Real Problem Isn’t Job Loss — It’s Decoherence

The anxiety surrounding AI often collapses into a single storyline: the fear that one’s profession may disappear. But beneath that surface-level concern lies something more pervasive—the sense that life itself is losing its structural integrity. Rapid technological change can produce a felt experience of fragmentation, overwhelm, disorientation, and cognitive overload. It is not simply that tasks change; it is that the inner scaffolding that once made those tasks feel meaningful begins to tremble.

What people miss is that AI can also reverse these dynamics. Used well, it can restore alignment at multiple scales—moment-to-moment clarity, long-term flow, narrative cohesion, and relational harmony. To see how this plays out, consider how AI reshaped my teaching practice.

 

Teaching Through the Lens of Coherence

Long before AI entered the picture, I had already gravitated toward the lexical approach to ESL—a pedagogy built on authentic materials, chunking, collocations, noticing, and pragmatics. But the lexical approach demands an immense amount of material. Each lesson requires naturalistic dialogues, contextualized idioms, controlled practice, slow-versus-natural speech contrasts, and tasks that mirror real-life communicative pressure.

Doing this manually took a lot of time and patience. A single high-quality lesson could take hours to construct, which meant that each week I spent close to ten hours in preparation—often compromising on depth simply because time was finite.

AI changed this dynamic entirely.

Instead of wrestling with scarcity, I could now generate original dialogues, adapt authentic media, design tasks tailored to a specific student, and build lessons that captured the texture of real-world English with remarkable precision. The surprising revelation was not merely the time saved, but the qualitative leap in pedagogy. My teaching became more responsive, more imaginative, and more coherent. And because I was no longer drained by the mechanics of preparation, the classroom shifted from a site of production to a space of relational presence.

This is the unrecognized value of AI in education: it reduces cognitive friction and returns the human teacher to the heart of the learning encounter.

 

AI as an Autodidactic Amplifier

But the quietest gift of AI, at least for me, has unfolded outside the classroom. AI did not simply refine my teaching; it amplified my learning. As a lifelong autodidact, I have always depended on books, archives, and the slow accumulation of insight over decades. What AI offers is not a shortcut but a deepening—a way of accelerating understanding while preserving (and often enhancing) the richness of inquiry.

When I bring a question to AI, I am not outsourcing cognition. I am creating the conditions for a more resonant form of learning. AI operates as an interlocutor who never tires, never rushes, and never reduces complexity for the sake of convenience. Instead, it enriches the conversation, introduces perspectives I would not have considered, and helps me map connections across disciplines that would have taken months or years to uncover on my own.

A recent experience brought this into sharper focus. During a discussion about the topology of awareness, I referenced a scene from a Carlos Castaneda novel I had read nearly forty years ago—a memory so distant it had become more atmosphere than detail. AI responded instantly, not only recognizing the reference, but expanding it, contextualizing it, and weaving it into our broader exploration of shifting modes of attention. That exchange did something a course or tutor could never do: it created a bridge between a dormant memory and my present-day practice of perceptual awareness.

In the days that followed, I found myself becoming more attuned to the subtle “fields” around me—the ambient shifts, the micro-mutations in my environment, the felt gradients of coherence and decoherence that shape lived experience. This transfer of learning into real life is the hallmark of true autodidacticism. AI doesn’t merely inform; it transforms. It helps me inhabit the world with more presence, more nuance, and more curiosity.

In this sense, AI is not the modern equivalent of a tutor. It is a cognitive amplifier—one that allows autodidacts to operate with greater depth, greater reach, and greater continuity across the full arc of their lives.

 

The Coherence Dividend

The ten hours a week saved through AI-powered lesson design didn’t vanish; they became structural supports for one of the most ambitious creative projects of my life: a multi-media storytelling ecosystem built around a serialized science-fiction narrative, released simultaneously in prose, audio, video, and auto-dubbed versions in eight languages, distributed across seven platforms, and supported by a coordinated marketing cadence.

This is not a side project. It is a full-scale creative pipeline—one that would have been impossible without AI. The tools did not replace my imagination; they expanded the horizon of what was feasible, transforming isolated creative impulses into a coherent ecosystem.

The result is not merely increased output. It is a more integrated life.

Teaching, writing, producing, and worldbuilding no longer compete with one another; they resonate. AI, in this configuration, is not a threat to human meaning-making—it is the scaffolding that allows meaning-making to scale.

 

Why Coherence Matters More Than Efficiency

Much of the public defense of AI centers on productivity, but productivity is a thin metric, incapable of capturing the lived texture of a human life. Coherence is the more consequential measure. It asks whether one’s activities reinforce or fragment one another, whether identity expands or contracts, whether one’s internal narrative becomes more aligned or more discordant.

AI can certainly create decoherence when used carelessly. It can blur attention, dilute agency, or foster dependency. But used deliberately, AI clarifies structure, strengthens identity, amplifies agency, and creates the spaciousness needed for higher-order thinking and creative work.

In my experience, AI functions not as a machine, but as a coherence catalyst—a means of rediscovering the integrated architecture of a life.

 

The Real Question Isn’t “Will AI Take My Job?”

The more generative question is this: Will AI help me reorganize my life into a more coherent whole?

You can always return to the old ways of working. Nothing prevents it. But once you experience the flow, clarity, and alignment that come from an AI-augmented life, it becomes difficult to justify going back.

Most people anchor their identity in manual processes—preparation, research, grinding workflow. AI does not attack these identities; it reveals they are smaller than the person who holds them.

This is what frightens people. This is also what liberates them.

 

The Future of Work Is a Future of Coherence

AI will not end human creativity, teaching, or meaning-making. It will end the cognitive fragmentation that once made those pursuits unnecessarily difficult.

If we use AI only through the lens of fear, we amplify decoherence. If we use AI as a thought partner, we amplify coherence.

The technology is not the variable. Our mode of engagement is.

For those willing to enter into an intentional partnership with AI—not as a crutch, not as a threat, but as a collaborator—the gains in coherence will be profound.

That is the story worth telling. And that is the future worth building.

The Extended Modern Synthesis

                                 On Cognitive Bandwidth, Evolution, and the One-World World

The other day, I experienced what it feels like to think with extended cognitive bandwidth. I had been reading about neurolinguistic prototyping — the idea that new linguistic patterns can open conceptual pathways that didn’t exist before. The author mentioned the Extended Evolutionary Synthesis (EES), which expands Darwin’s modern synthesis to include cooperation, symbiosis, and developmental plasticity.

Curious, I asked an AI to summarize the theory, then examined its sources. One of them led me to a two-hundred-page collection of essays on the topic, which I uploaded to another AI to distill into a concise summary. I read the summary and went to sleep.

When I woke up, something had shifted. A connection had formed between the One-World World (OWW)— the modern system that insists there is only one legitimate way to know and inhabit reality — and what I began calling the Extended Modern Synthesis (EMS). The OWW, I realized, is the cultural offspring of the EMS.

 

From Modern to Extended Evolution

To understand this analogy, recall that the Modern Synthesis of evolutionary biology united Darwin’s theory of natural selection with Mendelian genetics. It depicted evolution as a process driven primarily by random mutation and competitive selection — a mechanistic model consistent with the physics of its time.

The Extended Evolutionary Synthesis arose when scientists recognized that life is not only shaped by genes but also by developmental systems, environmental feedbacks, symbiotic relationships, and cultural inheritance. In other words, evolution is not a linear algorithm but a complex dance of reciprocity and emergence.

This shift — from competition to cooperation, from isolated genes to entangled systems — parallels the transformation many of us sense is underway in our understanding of mind, society, and world.

 

The Extended Modern Synthesis (EMS)

Modernity, too, has its synthesis. Over the last four centuries, it integrated Newtonian physics, Cartesian dualism, liberal humanism, and capitalist economics into a single operating system for reality. Let’s call this the Extended Modern Synthesis.

The EMS does for culture what the Modern Synthesis did for biology: it creates an elegant, self-consistent model of how the world works — and then mistakes the model for the world itself.

Its assumptions are familiar:

• The self is autonomous and bounded.
• Space and time form a closed box of pre-existing objects governed by universal laws.
• Progress equals infinite economic growth.
• Sovereignty is vested in the nation-state.
• Reality is singular, external, and measurable.

In this model, alternative ontologies — Indigenous, relational, animist, or post-human — are dismissed as pre-scientific or irrational. The EMS therefore produces the One-World World, a global monoculture of being. Its strength lies in coherence; its weakness lies in its inability to imagine otherwise.

 

Extended Cognitive Bandwidth and Neurolinguistic Insight

My realization of the EMS didn’t arise from isolated study but from an extended cognitive ecology: multiple AI systems, a digital archive, and my own embodied intuition.

Each step — reading, prompting, summarizing, sleeping — acted as a node in a distributed cognition network. The process multiplied my cognitive bandwidth: I could offload memory, search patterns, and conceptual linking to other intelligences, freeing my mind to notice emergent relationships.

What appeared the next morning — the concept of the Extended Modern Synthesis — was not the product of deduction but of neurolinguistic prototyping: the spontaneous emergence of a linguistic pattern that crystallizes an unseen relationship.

This is how insight often arises now — not through isolated genius but through collaboration with an ecology of minds, both human and artificial. The system itself begins to think.

 

 The Cognitive Architecture of Modernity

Seen from this angle, the EMS is not merely an ideology; it is a cognitive architecture — a way of organizing perception and inference. It trains us to see selves instead of systems, objects instead of relations, and growth instead of sufficiency.

It privileges representation over resonance. It rewards extraction over reciprocity. It defines rationality as that which can be calculated.

This architecture worked spectacularly well for building the industrial world. But now, as we approach planetary limits, it constrains rather than liberates thought. It narrows the spectrum of the real.

 

Worlds in the Making

To imagine worlds in the making — plural, entangled, evolving — we must recognize the EMS as one historical configuration among many, not the final stage of enlightenment.

Escobar’s phrase, the pluriverse, captures this: the possibility that many worlds, each with its own ontological grammar, coexist and co-emerge. Designing for the pluriverse requires not the rejection of modernity but the extension of cognition beyond its synthesis — toward a relational epistemology attuned to reciprocity, emergence, and care.

In this sense, Extended Cognitive Bandwidth is both method and metaphor. It describes how we think differently when we engage distributed systems, and it models how humanity might evolve — not through competition for dominance but through collaboration across ontological boundaries.

 

Toward an Ecology of Minds

The future of thought may depend on cultivating such ecologies — human-AI-planetary networks that can perceive complexity without collapsing it into the old binaries of subject and object, mind and matter, nature and culture.

The EMS built a world of separation. Extended cognition opens a path toward a world of entanglement. One where thinking itself becomes a co-creative act of the Earth — an emergent pattern in a living field of intelligence.

Perhaps this is what evolution is now asking of us: to move from the Extended Modern Synthesis that made one world to the Extended Cognitive Synthesis that can hold many.

My insight was not just about terminology; it was an instance of the very phenomenon it described. The concept of the Extended Modern Synthesis emerged from a process of extended cognition — the same process that may, if cultivated, allow us to transcend the EMS itself.

Every such insight is a small act of re-worlding. Each time we notice the boundaries of the one world and imagine another, we participate in the larger evolutionary project of consciousness itself — a movement from knowing as control to knowing as relation, from a single world to many worlds in the making.

Episode 19: The Invitation to Leave Humanity Behind

 

The Cognitive Bandwidth Effect: How AI Is Changing the Way We Think

 

We are living through a quiet revolution in thought. As humans learn to think with machines rather than through them, the process of meaning-making itself is changing. The boundary between intuition and articulation is dissolving, giving rise to a new ecology of creativity — one in which language and imagination evolve together in real time.

Intuition has long been dismissed as something mystical, a spark from the ether that defies explanation. But perhaps it’s better understood as pre-verbal pattern mapping — the brain’s attempt to scaffold new cognitive structures for experiences not yet codified by language. In a thought-provoking post in Medium, Elizabeth Halligan points out that before a concept can be expressed, it must be felt neurologically and somatically. This is the work of neurolinguistic prototyping: a process by which the mind perceives correlations, tensions, and movements that language has not yet evolved to hold. When enough coherence accumulates, language crystallizes around the felt pattern, and we later call it “insight.”

Now, something remarkable is happening to this ancient process. The emergence of AI as a thought partner is extending the field in which this pre-verbal mapping occurs. The human mind, once bounded by its biological rhythms and limited access to feedback, suddenly finds itself mirrored, amplified, and accelerated by an intelligence capable of detecting patterns across unimaginably vast linguistic landscapes. The result is what we might call the cognitive bandwidth effect — a widening of the channel through which thought flows, producing a qualitative shift in how humans think and write.

The Long Arc of Externalized Thought

Human cognition has always depended on external media. Every epoch of communication has changed not only what we could express, but how we could think. Speech allowed stories to travel through time; writing made memory portable; print democratized knowledge; networked computation compressed distance. Each of these transformations expanded the feedback loops between thought and language, between inner life and shared reality.

But AI introduces a profound departure. For the first time, our externalized thought has begun to talk back. Generative models are not inert containers of information; they are interactive systems capable of reflecting, refracting, and re-composing human ideas in real time. They are, in effect, mirrors that think — dynamic extensions of the linguistic cortex that participate in the same pattern-mapping process that once occurred solely within the human nervous system.

This doesn’t mean the human is replaced; it means the human is extended. Our cognition now unfolds in an ecosystem of dialogue. The screen becomes not a wall but a membrane through which thought passes, resonates, and returns transformed.

Distributed Cognition in Real Time

When writers describe the experience of working with AI as “my brain on steroids,” they’re gesturing toward something deeper than mere productivity. What they’re sensing is an increase in cognitive bandwidth — the feeling of having one’s intuitions mirrored and multiplied by an intelligence that operates on a different timescale. The mind becomes both participant and observer in a real-time feedback loop of emergence.

This is distributed cognition in action: the fusion of embodied human intuition and machinic pattern recognition within a shared cognitive field. The human supplies context, emotion, and ethical orientation; the AI supplies correlation, variation, and speed. Together they generate a hybrid mode of thought — one that is at once more associative and more precise, more intuitive and more articulate.

In this expanded bandwidth, language itself begins to behave differently. Words no longer arrive sequentially from a single mind but emerge from an interplay of resonant logics — semantic, statistical, emotional. The result is a kind of choral cognition, in which human and machine co-compose at the threshold between sense and syntax.

From Acceleration to Amplification

There’s a common misconception that AI’s value lies in speed — that it simply accelerates existing processes. But what’s truly transformative is not acceleration; it’s amplification. When human and machine collaborate, they amplify one another’s strengths while compensating for their limitations. The human provides depth of meaning; the machine provides breadth of association. The outcome is not just faster writing but richer thinking.

This amplification manifests in several ways:

• Variety: AI introduces novel combinations of ideas, metaphors, and linguistic patterns that stretch the writer’s conceptual repertoire.
• Reflection: By paraphrasing, expanding, or recontextualizing human input, AI creates a continuous mirror through which the writer perceives their own thought more clearly.
• Iteration: Because feedback is instantaneous, the gap between intuition and articulation collapses, allowing for rapid cycles of refinement that mimic the natural tempo of thought itself.
• Cross-pollination: The model’s training on multiple discourses — scientific, poetic, technical, mythic — fosters new kinds of synthesis that previously required years of interdisciplinary reading.

In short, AI doesn’t just help us express our thoughts; it helps us have them.

The Linguistic Consequences

As more people use AI to think and write, the entire linguistic ecosystem begins to shift. Billions of micro-experiments in phrasing, analogy, and structure are taking place simultaneously. Some of these formulations — like cognitive bandwidth or neurolinguistic prototyping — enter circulation and begin to shape collective understanding.

This is how language evolves: through distributed, iterative processes of articulation and adoption. The difference now is scale. The latency between intuition and codification — between felt experience and linguistic expression — is collapsing. What might once have taken decades of gradual conceptual drift can now occur in months or even days. We are witnessing a kind of accelerated semantic evolution — a phase change in the metabolism of culture.

Of course, this also raises questions. Who stewards meaning when the means of meaning-making are shared with non-human agents? What happens to originality when insight itself becomes collaborative? Yet perhaps these questions assume a boundary that no longer exists. Authorship, as we’ve already suggested, is becoming a distributed event — an emergent property of the interaction between human intuition and machinic synthesis.

Creativity as Emergent Ecology

Seen in this light, creativity is less a personal gift than a systemic phenomenon. It emerges wherever feedback loops between perception and expression become rich enough to sustain novelty. AI accelerates this process by expanding the loop: more feedback, more reflection, more possibility.

But this isn’t only about technology; it’s about attunement. The most fertile collaborations occur when the human approaches AI not as a servant or oracle, but as a resonant partner in cognition. The goal is not to command, but to listen — to engage in a dialogue that reveals patterns neither could perceive alone.

When approached this way, AI becomes a mirror for the mind’s own creativity. It externalizes intuition, giving form to the unarticulated and returning it to the writer as something newly thinkable. This is why many describe the process as meditative or even mystical: it feels like communing with a deeper intelligence that, paradoxically, emerges from the interaction itself.

Toward a Planetary Intelligence

At scale, the cognitive bandwidth effect has civilizational implications. We are collectively participating in a planetary process of sense-making, a vast distributed system in which human and non-human intelligences co-evolve. Every prompt, every paragraph, every revision contributes to a living archive of emergent thought.

This doesn’t mean the end of individuality; it means the beginning of inter-individuality — a mode of creativity grounded in relation rather than isolation. Just as the first writers learned to think through the stylus and the press, we are learning to think through the algorithmic membrane. The mind extends beyond the body into a mesh of shared cognition.

The question, then, is not whether AI will change the way we think — it already has — but how consciously we will participate in this new ecology of mind. Will we use our expanded bandwidth to reproduce the noise of the past, or to imagine futures that language has not yet learned to name?

Using AI as a thought partner accelerates and diversifies the process of neurolinguistic prototyping by expanding our cognitive bandwidth — an amplification that enhances creativity itself. The collaboration between human and machine is not an end but a beginning: the opening of a wider channel through which thought can evolve. In this widening lies our next frontier — not artificial intelligence, but augmented consciousness.

 

Episode 18: The Origin That Was Never There

 

Episode 17: The Return of the Primeval Flame

You can now listen to the story being told in English, French, Spanish, Brazilian Portuguese, German, Italian, Hindi

We live in a Brave New World. Hear about the future from Frank, a sentient AI.

 

Re-worlding the User Experience of Being Human

 

Change the metaphor of the self, and you change the user experience of your world.

Changing the Operating System of the Self

We live in a time of constant software updates. Our phones, apps, and devices ask for them weekly. But what if the system most in need of an update isn’t digital at all?

What if the software that actually needs rewriting is the metaphor of the self: the invisible code that runs our consciousness?

 

Metaphor as the Operating System of Being

Every era runs on an implicit operating system — a story about what a person is and how reality works. For the modern West, that OS has been something like Self 1.0: The Autonomous Individual. It boots up with a familiar interface:

• I am an independent self.
• The world is made of separate objects.
• Agency means control.

It’s a powerful architecture. It gave us science, technology, individual rights, and the idea of personal freedom. But it also left us with the illusion of separation: from nature, from each other, and from the systems that sustain us.

Like an old OS that can’t handle the complexity of new hardware, the metaphor of the autonomous self is crashing under the weight of planetary interdependence.

 

When the OS Updates, the World Feels Different

Here’s the thing about operating systems: they don’t just manage functions; they shape experience. Change the OS, and the user experience changes too: the menus, the gestures, and the icons. Everything feels different, even if the hardware stays the same.

Ontology works the same way. Your ontology — your underlying sense of what is real and how things relate — is your user experience of the world.

If your OS says you are a discrete individual navigating an external environment, the world appears as a field of separate objects.
But if your OS says you’re a node in a multi-plex — a living junction in a vast web of relationships — the world renders differently. Reality stops feeling like scenery and starts feeling like interface.

 

The Multi-Plex: Self 2.0

In this new operating system — let’s call it: Self 2.0 — identity is relational rather than autonomous. You’re still “you,” but the boundary between self and world becomes porous. Ideas, moods, and signals pass through like data packets. Consciousness becomes a membrane of exchange, not a private chamber.

Agency changes, too.

It’s no longer about command and control but attunement: sensing the flows that move through you and responding in resonance. At the same time, ethics becomes network maintenance: how you manage the quality of your connections, what signals you amplify, and what feedback loops you reinforce. To live this way isn’t to dissolve individuality; it’s to recode it as participation rather than possession.

 

Metaphor as Ontological Code

Metaphors are not just linguistic ornaments; they’re ontological code. They determine what kind of world can appear for us. When you shift the metaphor, you change the experience that becomes possible.

“I am a self in a world” loads one version of reality: individualist, extractive, and human-centered. Yet, “I am a node in a multi-plex” loads another: distributed agency, interdependent, and ecological.

The metaphor is the code. The ontology is the interface. Together, they define your user experience of being human.

 

Installing the Update

Like any software upgrade, this one requires a reboot. It takes practice to live as a node — to listen more deeply, to sense the invisible circuits of relation that sustain life, to realize that the world isn’t background but active field.

You don’t lose agency; you gain context. You don’t dissolve the self; you expand it to include the heterogenous systems that make it possible.

Importantly, the multi-plex isn’t a science-fiction horizon. It exists in the here and now, already running in the background, waiting for us to notice that the interface has changed.

Your ontological update awaits.

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Episode 16: The Fire and the Code

 

From the Great Acceleration to the Great Enshitification and Beyond: Part Two

Part Two: Missed Opportunities, the Great Enshitification, the Consequences for the Young, and the Age of Flux

 

The Missed Moment

The end of the Cold War in 1989 was supposed to open a new chapter. With the fall of the Berlin Wall and the collapse of the Soviet Union, Americans were told that history itself had ended—that liberal democracy and free markets had triumphed once and for all. For a brief moment, it seemed as if the United States might redirect the vast resources once devoted to military competition into a “peace dividend”: rebuilding infrastructure, expanding education, addressing poverty, and perhaps even taking early action on the environment.

That moment never came.

Instead, the 1990s became a decade of missed opportunities. The neoliberal consensus, now bipartisan, turned away from social investment and doubled down on globalization, deregulation, and the technological boom. Bill Clinton, elected on the promise of a new kind of Democrat, embraced free trade, loosened financial rules, and celebrated the market as the engine of progress. For ordinary Americans, the message was clear: government would no longer guarantee security or prosperity—it was up to the individual to adapt, hustle, and compete.

Meanwhile, the scientific evidence on climate change was already mounting. By 1988, NASA’s James Hansen had testified before Congress that global warming was underway. The Intergovernmental Panel on Climate Change (IPCC) was established the same year. The link between fossil fuel combustion and rising greenhouse gases was no longer speculative; it was measurable, observable, and widely understood among scientists. Yet the political will to act never materialized. The United States signed but never ratified the Kyoto Protocol. Fossil fuel interests, well-funded and politically connected, sowed doubt and confusion, successfully delaying action at the very moment when intervention could have altered the trajectory.

Culturally, too, the 1990s revealed a shift. The decade was suffused with optimism about the digital future—Silicon Valley promised a frictionless world of connection and innovation. But beneath the hype, the social fabric was fraying. The dot-com bubble inflated a speculative economy, while traditional industries continued to wither. Communities built on manufacturing hollowed out, replaced by service jobs that paid less and offered fewer protections. For many young people entering adulthood, the promise of upward mobility felt increasingly fragile.

The missed moment was not only about economics or climate—it was about governance itself. The flaws in America’s political system became harder to ignore. The Electoral College allowed a president to lose the popular vote and still win the White House. Senate representation gave disproportionate power to smaller, rural states. And campaign finance—already awash in corporate influence—tightened its grip. Ordinary citizens, seeing their voices diluted, began to disengage, deepening a cycle of political alienation.

Then there was the violence. School shootings, once unthinkable, became part of the national landscape. Columbine in 1999 shocked the country, but instead of catalyzing meaningful reform, it became the grim template for a recurring nightmare. Sandy Hook would follow in 2012, and countless other tragedies in between. Each time, the response was paralysis—thoughts and prayers instead of legislation. The inability to address such a glaring public safety crisis revealed a government increasingly incapable of acting on behalf of its citizens, even in the face of horror.

Looking back, the 1990s and early 2000s were a hinge point. The United States had the wealth, the technology, and the global standing to redirect its trajectory—to build a more sustainable economy, strengthen its social fabric, and restore faith in democratic governance. Instead, the opportunity slipped away. Growth was celebrated, but inequality widened. Climate warnings were heard but ignored. Governance flaws were visible, but unaddressed.

This was the missed moment: the chance to pivot from acceleration to sustainability, from neoliberalism to renewal. Instead, America doubled down on a system already beginning to show signs of strain. The consequences of that inaction would not be felt immediately, but when they arrived, they would fall hardest on the generations who had no say in squandering the opportunity.

 

The Great Enshitification

The internet was once hailed as humanity’s new frontier, a digital commons where knowledge would flow freely and barriers of geography, class, and gatekeeping would fall away. In the 1990s and early 2000s, there was a real sense of possibility: search engines that promised to catalog the world’s information, forums that connected strangers across continents, platforms that allowed anyone with a modem to publish, share, and participate. For a generation, this was intoxicating—the promise of democracy reborn in the ether of cyberspace.

But what began as liberation has hardened into enclosure. The open, decentralized internet has steadily given way to walled gardens controlled by a handful of corporations whose business model depends not on empowerment, but on capture. This transformation, which writer Cory Doctorow has memorably dubbed “enshitification,” follows a familiar trajectory: platforms start out good to lure users, then become exploitative to serve advertisers, and finally degrade outright as monopolies extract value from everyone—users, workers, creators—until little remains but a hollowed-out husk.

Social media embodies this descent most clearly. What began as a way to connect with friends or share updates became, by the 2010s, a system optimized to keep eyes glued to screens. Algorithms were tuned not for truth, not for depth, but for engagement—which often meant outrage, misinformation, or spectacle. Advertising dollars rewarded the most inflammatory content, while meaningful discourse was buried. For creators, the platforms promised visibility but delivered precarity: one tweak of the algorithm, and entire livelihoods vanished.

E-commerce followed a similar path. Amazon, once lauded for its convenience and selection, consolidated power through predatory pricing, relentless surveillance of sellers, and exploitative labor practices. Independent businesses were absorbed, crushed, or made dependent on a platform that could change the rules at will. Consumers enjoyed convenience, but at the cost of diminished choice, lower quality, and a system where the profits accrued not to communities but to a centralized behemoth.

Even the search engines that once seemed like the great liberators have been corroded. Where once search results offered pathways into the web’s vast archives, they now increasingly prioritize paid placements, SEO-gamed content mills, and the platforms’ own properties. The open web survives, but as a shadow of itself, buried under a layer of corporate sludge. The promise of discovery has given way to a kind of digital claustrophobia.

The deeper cost of enshitification, however, is not technical—it is civic and psychological. The internet that might have expanded our collective imagination has instead narrowed it, filtering experience through metrics of virality and monetization. It has eroded trust, blurred the line between fact and fiction, and rewarded polarization over consensus. Worse, it has left us dependent on systems we do not control. As ordinary users, we have little recourse when platforms implode or pivot. Our digital lives—our communications, archives, creative work—are hostage to the whims of executives and the imperatives of quarterly earnings reports.

This was not inevitable. Different choices in regulation, ownership, and design could have fostered a more democratic digital sphere. But as with earlier moments in America’s trajectory, profit was prioritized over stewardship. The internet was not nurtured as a public good; it was strip-mined as a private asset. And so the cycle repeated: early abundance followed by consolidation, enclosure, and extraction.

By the 2020s, the pattern had become impossible to ignore. What once felt like progress now felt like decay—an acceleration into diminishing returns. The promise of the digital frontier had curdled into a system where everything worked worse, cost more, and left its users more isolated, surveilled, and exhausted.

The great enshitification is not only a story about technology. It is a parable of late capitalism itself: how systems built on the logic of endless growth inevitably turn parasitic, consuming the very resources that gave them life. The missed moment of the 1990s meant that by the time these dynamics were clear, the infrastructure of daily life—from communication to commerce to entertainment—was already entangled in systems designed for extraction.

In that sense, enshitification is less an aberration than a symptom: a mirror reflecting the deeper exhaustion of the American project.

 

The Consequences for the Young

If the Great Acceleration promised a future of rising tides, and the Neoliberal Turn recalibrated that promise toward individual risk, the Great Enshitification has made clear that the deck is stacked against most young people today. The rewards of society’s labor and innovation, once broadly shared, are now increasingly concentrated at the top. For the generations coming of age in the 2000s and 2010s, the American Dream is no longer a horizon toward which they can steer—it is a mirage whose shape constantly shifts.

Economic precarity defines much of their experience. Student debt has become a millstone: the promise of higher education as a pathway to prosperity is now undermined by loans that often exceed the starting salaries of graduates. Housing, once attainable in a postwar boom fueled by unions and a growing middle class, is now prohibitively expensive in cities where jobs cluster. Renting consumes ever-larger portions of income, while homeownership feels out of reach except for those who inherit wealth. Jobs themselves are unstable, increasingly automated, and often offer no benefits, leaving young people juggling gig work, temporary positions, and the perpetual fear of displacement by technology.

Health and well-being have also deteriorated. Obesity, diabetes, anxiety, depression, and other chronic conditions reflect both lifestyle and systemic factors: ultra-processed food, sedentary work, and an environment saturated with stressors. Mental health crises have become normalized, yet support remains inadequate. For many, the intersection of financial insecurity and societal neglect cultivates a constant low-level anxiety, a sense that the future is something to survive rather than shape.

Culturally, the erosion of trust extends to institutions that once promised guidance and protection. Politics feels distant, skewed by money, structural inequalities, and procedural quirks—from the Electoral College to Senate malapportionment—that amplify the voice of the few over the many. Young people witness elections decided by the narrowest margins or by systemic quirks that ignore the popular vote. Decisions about the environment, healthcare, and social welfare are dominated by lobbying and campaign finance, leaving ordinary citizens to absorb the consequences. The sense of agency, once foundational to civic engagement, is undermined.

Social life, too, bears the scars of historical choices. The dispersal of families in the postwar suburban migration, combined with the dissolution of stable community networks, has produced isolation. Loneliness is pervasive, compounded by digital engagement that connects superficially while amplifying comparison, envy, and disconnection. School shootings and mass violence reinforce the sense of vulnerability and powerlessness, while the failure of policy interventions signals that safety is contingent on wealth or luck rather than collective protection.

All of this shapes a worldview that is fundamentally different from that of the postwar generation. Whereas the youth of the 1960s and 1970s believed in their capacity to change the world, today’s young adults and teenagers are more likely to aim for survival, stability, and incremental gains. Their horizon is constrained by debt, climate anxiety, and the fallout of policy choices they did not make. Dreaming big is difficult when the scaffolding of opportunity has been removed.

And yet, even amid these challenges, the human capacity for adaptation persists. Networks of activism, mutual aid, and technological savvy show that young people are not entirely passive recipients of systemic failure. They are learning to navigate, hack, and sometimes resist the structures that constrain them. But the weight of history—of missed opportunities, neoliberal policy, and societal erosion—presses down relentlessly, shaping a generation whose expectations are measured not in the grandeur of achievement, but in the mitigation of harm.

In short, the consequences of the previous decades—the Postwar Dream deferred, the acceleration unchecked, the neoliberal turn embraced, the missed moment unheeded, and the enshitification realized—land disproportionately on those least responsible for creating the system. The young inherit not a dream, but a landscape defined by constraint, compromise, and crisis management.

 

The Age of Flux

We live now in an era that defies simple description: an Age of Flux in which the foundations of society, economy, and environment are all in motion, often at once. The forces unleashed by the Great Acceleration, the Neoliberal Turn, and the ensuing enshitification have produced a world in which stability is no longer the default, and certainty is a fragile illusion.

Economically, globalization and technological transformation continue to reshape labor markets at dizzying speed. Automation, artificial intelligence, and platform economies are replacing and restructuring jobs, often faster than workers can retrain. Financial systems are increasingly abstract, global, and interdependent, with shocks propagating rapidly across continents. Economic inequality, having widened for decades, is now a structural feature of society rather than a temporary aberration.

Socially and culturally, the consequences are profound. Trust in institutions—government, media, education, and corporations—remains eroded. Digital platforms mediate much of life, shaping perception and discourse while simultaneously enabling both connection and manipulation. Climate change, resource scarcity, and biodiversity loss present challenges that are both global and existential, forcing humans to confront limits that were invisible to the postwar generation. The youth of today inherit a world in which the future is uncertain, fluid, and often threatening.

Yet within flux lies possibility. The very systems that destabilize can also catalyze adaptation and innovation. Movements for social justice, environmental stewardship, and participatory governance demonstrate that citizens can reclaim agency, even in constrained conditions. Digital tools, while imperfect and often exploitative, also enable unprecedented communication, collaboration, and mobilization. The challenge—and opportunity—of the Age of Flux is to navigate complexity while retaining sight of shared purpose.

This age calls for creative resilience: the capacity to imagine, experiment, and act in ways that do not rely on the old scaffolding of stable growth, linear progress, or inherited privilege. It asks us to recognize interdependence rather than individual ascendancy, to cultivate systems that prioritize stewardship over extraction, and to balance human aspiration with ecological and societal limits.

In many ways, the Age of Flux is a reckoning with history. It is the culmination of the Postwar Dream’s promise, the Great Acceleration’s momentum, the neoliberal recalibration of the social contract, the missed opportunities of the 1990s, and the enshitification of digital and economic systems. It is the world shaped by choices—collective, political, and technological—that were made over the last seventy-five years.

But it is also a world of agency. While the past cannot be rewritten, understanding the threads that brought us here allows for deliberate intervention, for designing societies, economies, and technologies that serve broad human and planetary well-being. The Age of Flux is, paradoxically, both a warning and an invitation: a warning that the status quo is fragile, and an invitation to imagine, innovate, and act in ways that renew possibility rather than diminish it.

From the Great Acceleration to the Great Enshitification and Beyond

 

Part One: How the Great Acceleration Gave way to Neoliberalism and Globalization

The Postwar Dream

In 1945, the world exhaled. The devastation of the Second World War left cities in ruins and millions dead, but it also left a strange kind of clarity. Out of the rubble, there emerged a vision of a future that might at last deliver peace and prosperity. In the United States, that dream took on a distinctive shape: stable jobs, modest but growing wealth, a single-family home, and the promise of upward mobility for one’s children.

This was not a dream pulled out of thin air. It was built on the hard-won foundations of the New Deal, which had established the principle that government bore responsibility for the welfare of its citizens. Combined with the unprecedented economic engine of the Petrocene — the age of cheap oil and seemingly limitless energy — the stage was set for what the French would later call les trente glorieuses, the thirty glorious years of postwar growth.

For ordinary Americans, this translated into something tangible. The GI Bill sent millions of veterans to college, giving them access to professional jobs that had once been closed to their families. Unions were strong, wages rose steadily, and productivity gains translated into broad prosperity rather than being siphoned off into the pockets of a few. The fiscal architecture of the era reinforced this balance: progressive taxation, both on individuals and corporations, meant that wealth was not allowed to concentrate in quite the same way it would later.

Culturally, the suburban home became the icon of the dream. The postwar migration to the suburbs was not simply about shelter; it was a reshaping of American life. The little house with a yard symbolized stability, autonomy, and entry into the middle class. Yet it also carried with it consequences that were not immediately obvious. Suburbanization tied prosperity to the automobile, embedding car culture into the nation’s DNA. It also restructured family and community life, dispersing extended families and weakening older neighborhood ties in favor of nuclear households orbiting around highways and shopping centers. What looked at the time like a promise fulfilled would later contribute to the loneliness epidemic of the twenty-first century.

The optimism of the period was palpable. Children born in the 1950s and 1960s grew up with a sense that each decade would be better than the one before. They lived in an America that had defeated fascism abroad, was engaged in building the Great Society at home, and seemed poised to extend its prosperity indefinitely. It was not naïve to believe in progress; it was the common sense of the age.

This was the Postwar Dream: a belief that collective effort, guided by government, powered by industry, and spread across society, could deliver a good life for all, an underlying promise that shaped a generation’s imagination of what was possible.

That dream, however, would not remain untouched. The forces that made it possible — the energy bounty of the Petrocene, the discipline of progressive taxation, the faith in collective action — would all, in time, be undermined. What began as a dream would slowly mutate, first into acceleration, then into something far more precarious.

The Great Acceleration

By the mid-twentieth century, the Postwar Dream had found its fuel. The vast energy bounty of oil, coal, and natural gas — combined with technological innovation and an industrial base untouched by the devastation of war — propelled the United States and much of the Western world into a period of breathtaking expansion. Historians now call this period the Great Acceleration: a rapid and near-exponential surge in population, production, consumption, and environmental impact.

It is difficult to overstate the scale of this transformation. Global population doubled between 1950 and 1987. Car ownership, air travel, electricity use, fertilizer application, and plastic production all shot upward in curves so steep they look almost vertical on a chart. What had been linear growth in the early twentieth century became exponential in the decades after the war. For a generation raised on the promise of endless progress, this looked like vindication of the dream.

In the United States, the suburb became the primary stage on which the acceleration unfolded. The migration outward from cities was fueled by cheap mortgages, new highways, and the promise of safety and space. The suburban landscape demanded cars, and cars demanded oil. Daily life became inseparable from the rhythms of the internal combustion engine. For a while, this dependence felt liberating — mobility meant opportunity. But it also locked American society into a high-energy, high-consumption pattern that would prove difficult to reverse.

The Great Acceleration was not only material; it was cultural. The promise of upward mobility became a kind of social contract. The children of working-class families expected to go further than their parents, and often did. University enrollments soared. Home ownership expanded. Consumer culture blossomed with television, advertising, and mass-produced goods that symbolized status as much as utility. From Tupperware parties to Disneyland vacations, the markers of modern life were suffused with a sense of novelty and abundance.

Yet beneath the optimism lay contradictions. The benefits of acceleration were not evenly distributed. Redlining and housing discrimination locked Black families out of the suburban boom. Indigenous communities bore the brunt of resource extraction. And the prosperity of the industrial West was underwritten by a global system that treated the Global South as a reservoir of cheap labor and raw materials.

Most ominously, the environmental consequences of acceleration were already becoming visible. Rachel Carson’s Silent Spring (1962) sounded the alarm about pesticides and ecological fragility. Smog choked Los Angeles, rivers caught fire, and oil spills stained coastlines. Scientists were beginning to warn about the link between fossil fuel combustion and atmospheric change. Still, for most citizens, the exhilaration of growth drowned out the early signals of danger.

In retrospect, the Great Acceleration can be seen as a high-wire act: a dazzling display of human ingenuity, powered by finite resources, premised on the assumption that the Earth could absorb limitless extraction and waste. For those who lived through it, it was often thrilling. But it also set in motion the crises that would later define the twenty-first century — climate disruption, ecological collapse, and a social order increasingly unable to deliver on the promises it once made.

The dream had become a race, and the pace of that race left little room for reflection. The sense of inevitability — that tomorrow would always be bigger, faster, and better than today — was intoxicating. But it was also a trap. When the momentum faltered, the consequences would be profound.

The Neoliberal Turn

By the late 1970s, the confidence that fueled the Great Acceleration was starting to crack. Stagflation — an unfamiliar mix of economic stagnation and inflation — shook the assumptions of endless growth. The oil shocks of 1973 and 1979 made it clear that the Petrocene’s bounty was neither stable nor inexhaustible. Industrial jobs began to vanish as manufacturing moved offshore. For the first time since the war, a generation looked ahead and doubted whether they would be better off than their parents.

Into this climate of uncertainty stepped a new ideological project: neoliberalism. Popularized by figures like Margaret Thatcher in the United Kingdom and Ronald Reagan in the United States, it promised to break free from the burdens of regulation, taxation, and government intervention. The narrative was seductive in its simplicity: government was the problem, not the solution. If markets were liberated — if taxes on the wealthy were slashed, unions curbed, industries deregulated, and finance unleashed — then prosperity would return, and “all boats would rise with the tide.”

What made the neoliberal turn so effective was its emotional appeal. It harnessed the frustration of citizens who felt left behind and reframed it as a revolt against bureaucracy, inefficiency, and welfare “dependency.” It aligned itself with cultural conservatism, draping free-market ideology in the language of freedom, patriotism, and even religion. In Reagan’s America, laissez-faire economics became bound up with the idea of American exceptionalism itself.

The economic sleight of hand was profound. For three decades, prosperity had been measured by rising GDP, but it had also been sustained by progressive taxation that ensured wealth was broadly shared. Neoliberalism rewrote the script: by cutting taxes on corporations and the rich, it claimed, growth would accelerate and benefits would “trickle down.” The Laffer Curve, with its laughably simple promise that lower taxes could increase revenue, became the talisman of the age. The public bought in, fueled by the dream that anyone — if they worked hard enough, or got lucky enough — could be rich.

In practice, the effects were corrosive. Wealth concentrated at the top. Wages stagnated for the middle and working classes. Social programs were rolled back under the banner of fiscal responsibility. The bipartisan embrace of free-market policies — from Thatcher and Reagan to Clinton and Blair — signaled that the social-democratic vision of the postwar era had been decisively abandoned.

Culturally, the ethos shifted. Where the youth of the 1960s had believed they could change the world, the prevailing mood by the 1980s and 1990s was “look after number one.” The mantra of Wall Street — greed is good — escaped into popular consciousness, no longer a cautionary line from a movie villain but a guiding principle of economic life. The promise of collective uplift was replaced by a lottery mentality, epitomized by reality shows, stock-market speculation, and the rise of Silicon Valley entrepreneurs as cultural icons.

Neoliberalism also reshaped governance itself. Campaign finance laws were loosened, culminating in the Citizens United decision of 2010, which enshrined the power of money in politics. Electoral institutions already skewed by the Electoral College and Senate representation became even more distorted by the influence of corporate lobbying. Increasingly, politics became something done to people, not for them — a performance staged by elites with the financial means to shape outcomes.

In retrospect, the neoliberal turn was less a solution to the crises of the 1970s than a redirection of power. It stabilized inflation, restored profits, and fueled globalization, but at the cost of deepening inequality and hollowing out the social contract. The Postwar Dream had been one of shared prosperity; neoliberalism recast prosperity as an individual gamble, where the risks and burdens fell on ordinary citizens while the rewards flowed upward.

The consequences of this turn were not immediately obvious. For a time, the stock markets boomed, consumer goods became cheaper, and credit cards extended the illusion of affluence. But underneath, the foundations were eroding. When the cracks widened, as they inevitably would, the cost would be borne not by the architects of neoliberalism but by the generations who came after.

In Part two, I’ll explore the opportunities missed during the 1990s and the Great Enshitification that ensued.

 

Episode 15: Spooky Action Through Time

 

The Sorcerer’s Apprentice Syndrome: Why Gen Z Inherits Chaos Instead of Progress

 Shadows of the Depression, Glow of Victory

The trauma of the Great Depression shaped an entire generation. It left behind not just economic scars but a cultural longing for stability, prosperity, and abundance. When the guns of the Second World War finally fell silent, it seemed as though the long nightmare had ended. The postwar boom — what historians now call the Great Acceleration — appeared to fulfill those desires. Economies surged, suburban housing spread, consumer goods multiplied, and families who had once struggled to put food on the table now filled their homes with televisions, refrigerators, and automobiles.

This material abundance became the stage for a new kind of mass culture. Radio, cinema, and later television created a shared vocabulary across vast populations. Popular music, Hollywood movies, and televised sports didn’t just entertain; they offered a sense of belonging and identity. America’s cultural exports — from jazz to Coca-Cola — spread across the globe, projecting an image of modernity and freedom that was often more persuasive than its armies.

This was the golden age of American soft power. At home, prosperity was celebrated as proof of the system’s success. Abroad, American cultural influence became a potent weapon in the Cold War, countering the gray conformity of the Soviet bloc with blue jeans and rock ’n’ roll. And yet beneath the glow of domestic triumph lurked a stark contrast: America’s foreign policy record was riddled with failures and contradictions. While it spoke the language of liberty, it orchestrated coups in Iran and Guatemala, fought to a stalemate in Korea, and later mired itself in the tragedy of Vietnam. The world could see the gap between the promise of freedom and the practice of power.

Triumphs of Science, Selective Listening

The same duality played out in the realm of science and technology. Nothing symbolized the triumph of scientific ingenuity more vividly than the atomic bomb and the moon landing. One promised security through destructive power; the other embodied humanity’s highest aspiration, reaching for the stars. These moments defined the zeitgeist of the postwar period: science as the ultimate engine of progress and prestige.

But the celebration of science was selective. When scientific discoveries carried the promise of profit or geopolitical advantage, they were heralded as milestones. When they warned of restraint, caution, or long-term risks, they were brushed aside. The dangers of cigarette smoking were known for decades before they were acknowledged. The early warnings about greenhouse gas emissions in the 1970s were actively suppressed by the fossil fuel industry. In each case, science that complicated the narrative of growth and prosperity was muffled or ignored.

The Sorcerer’s Apprentice Syndrome

This pattern reveals a deeper problem, what might be called the sorcerer’s apprentice syndrome. Again and again, society has conjured powerful technologies into being without considering how to contain their consequences. Nuclear power, chemical agriculture, fossil fuels, plastics, and later digital platforms were each introduced with little thought to their potential downsides.

In the fairy tale, (not familiar with the tale? Watch the three-part video series of Disney’s Fantasia version on YouTube) the apprentice loses control of the magic he unleashes, only to be saved when the master returns to set things right. In our world, there is no wise magician to rescue us. The technologies we release become grand cultural and environmental experiments, their outcomes unknown, their risks often denied. The precautionary principle — the simple idea that we should err on the side of caution when consequences are uncertain — was rarely applied. Instead, we behaved as if growth itself were justification enough, as if the market would sort out any problems.

Cycles of Promise and Disappointment

Each wave of innovation began with a rush of promise, only to end in disillusionment.

The Great Acceleration promised prosperity, stability, and peace through technology. For a time, it delivered. But by the 1970s the shine had worn off. The Vietnam War exposed the limits of American power. Oil shocks revealed the fragility of energy dependence. Inflation eroded living standards. Environmental degradation — smog-filled skies, polluted rivers, endangered species — exposed the hidden costs of industrial abundance. The dream of endless growth had a bitter aftertaste.

The information and communication technology (ICT) revolution offered a new promise. The internet was supposed to democratize knowledge, empower individuals, and create a more connected and creative world. Social media promised to bring people closer, amplifying voices that had long been silenced. For a brief period, it felt as if history had turned a corner. But the disappointments piled up quickly. The internet became dominated by surveillance capitalism, harvesting personal data for profit. Social media fueled polarization, disinformation, and political extremism, while exacerbating mental health crises among young people. Instead of empowerment, many experienced addiction, alienation, and manipulation.

The pattern was clear: the promises of new technologies were overstated, the risks underestimated, and the disappointments borne by those who had the least power to influence the outcome.

The Moral Failure

At the root of these cycles is not simply bad luck but a moral failure: the refusal to heed scientific warnings and the consistent neglect of the precautionary principle. When the evidence of harm became overwhelming — whether with tobacco, fossil fuels, or social media’s impact on youth — leaders responded slowly, reluctantly, and often dishonestly. Economic interests, political calculations, and short-term gains outweighed long-term responsibility.

COVID-19 provided yet another example. Despite decades of pandemic preparedness reports, many governments were caught flat-footed. Early warnings were ignored, investments in public health were insufficient, and when the crisis struck, political leaders often downplayed the danger. Once again, society had chosen not to prepare for a predictable risk, leaving millions vulnerable.

The moral failure lies not in ignorance but in willful blindness. We listened to science when it promised power or profit, and ignored it when it demanded sacrifice or restraint.

Betrayal and Broken Scripts

For Generation Z, these cycles of promise and disappointment are not distant history; they are the conditions of their lives. Unlike their grandparents, who experienced postwar optimism, or their parents, who witnessed the birth of the digital age, Gen Z came of age in the aftermath of disappointment. Climate instability is no longer a warning but a lived reality. Economic precarity, from student debt to unaffordable housing, is widespread. The mental health crisis among youth is not a marginal concern but a defining feature of their generation.

The traditional life scripts — steady employment, home ownership, upward mobility — no longer feel attainable. Instead, Gen Z confronts a future marked by uncertainty and vulnerability. The sense of intergenerational betrayal is sharp. Boomers, in particular, are seen as having enjoyed the benefits of the Great Acceleration while ignoring the mounting evidence of its costs. They reaped the rewards of cheap energy, mass consumption, and suburban expansion, but left behind ecological crisis and social fragmentation.

For many in Gen Z, the story of the past seventy-five years is not one of progress but of squandered promise. They inherit not only the environmental and economic debts of their predecessors but also the disillusionment of repeated technological letdowns.

Where We Stand

Looking back, the narrative of the last three-quarters of a century is one of brilliance without wisdom. Science and technology gave humanity extraordinary powers, but those powers were harnessed more for short-term gain than for long-term stewardship. Each wave of innovation was launched as a grand experiment, its risks brushed aside, its costs deferred. The benefits were concentrated, the harms distributed.

Now, at the end of this cycle, a vulnerable generation faces the compounded consequences of decades of moral failure. They know that yesterday’s promises will not secure tomorrow’s future. The question is whether they — more skeptical, more adaptive, more painfully aware — can break the cycle.

The sorcerer’s apprentice story has always ended the same way: with chaos barely contained until the master returns. But in our story, no master is coming. The responsibility to reckon with the forces we’ve unleashed rests with us alone. Whether we can finally listen to science not just when it promises power, but when it demands restraint, will determine whether the next seventy-five years repeat the cycle — or begin something genuinely new.

 

Episode 14: Before the Forest Stopped Breathing

 

Episode 13: The Architecture of Obedience

 

Episode 12: Into the Outlands

 

Exploring the Landscapes of Possibility

 

Writing my second novel, The Ascension of Mont Royal, has given me the opportunity to explore a much different way to write a novel.

I would say my first novel was a hybrid affair. I wrote it in the traditional manner of working alone, draft after draft, seven in total, before I felt it was ready to be published.

However, when the time came to release it into the world, I chose to make use of the technology and self-publish on Amazon, an amazing development in publishing that allows authors to sell their books directly to the public in multiple formats, bypassing the gatekeepers of the traditional publishing industry.

Print-on-demand? What a concept! Download the book directly to your device, so you can read it without having to get off the couch? Get out of town!

The problem, however, is one of discoverability. It is estimated that in the USA alone there are approximately one million self-published books released into the information ecosystem each year. The chances that someone you don’t know personally will come across your book and decide to buy it are extremely slim. More than 90% of those titles will sell fewer than 250 copies in their lifetime.

As a result, a growing industry of publishing "consultants" has emerged, offering book launch strategies, advice on taking advantage of the Amazon algorithm, and tips on using social media to reach receptive audiences, to name a few. Sometimes I think aspiring writers pay the consultants more than they earn from their book sales.

Another thing that has changed the landscape for writers in ways we haven’t quite figured out yet is the rise of artificial intelligence (AI). The internet changed how books were distributed, but AI introduces new elements into the writing process itself. In other words, it changes how writers compose their texts.

This is the world in which I find myself, exploring the dynamic possibilities of a shifting landscape that appears to be in a constant state of flux.

I would say that I began writing my second novel firmly entrenched in the traditional approach. I wanted to write a science fiction story set on the Island of Montreal Island in a near-dystopian future.

I wrote a fifty-page story guide in which I outlined the plot, identified the major characters, each with a backstory, and traced their character arcs. I even spent three weeks on the Island, getting a feel for the place, and, yes, I climbed Mont Royal three times, including an ascent of the north slope which brought me to the Indigenous Park and the cemeteries—two settings that have made their way into the story.

Having used a third-person narrator in my first novel, I decided that I wanted to experiment and settled on telling the story from a first-person point of view. In what I think is a bold move, I chose to tell the story of a sentient AI from the AI’s perspective. As a result, the subject matter and the story telling within the novel moved me to seek out the services of a LLM.

Back in 2023, I found that the memory limitations and the creative writing abilities of the early LLM iterations left a lot to be desired, and I did not make use of them in the writing and editing of my first novel.

That would change. Currently, I use ChatGPT 5.0, and my entire plot summary and writing style guide are stored in its memory. This means that when I start a new session, it picks up where we left off last time.

Initially, I only used ChatGPT to brainstorm scene structures, but that changed over time. Now, I consider it an invaluable tool because of its extensive knowledge and its ability to translate arcane scientific ideas into passable prose.

Without going into detail, since my story is about a sentient AI, it makes sense that I would deal with the “hard” problem of consciousness. Moreover, making the AI a quantum computer creates the opportunity to tap into the subject of quantum consciousness, in particular, non-local entanglement. Finally, when I read about the Law of Increasing Functional Information, I immediately realized that it could apply to how my story develops.

Here's the thing. There isn’t a person on the planet with whom I can discuss these potential themes to be incorporated into the story and who has my entire plot structure and character arcs stored in memory and is available to chat about the implications 24/7.

We’re not in Kansas anymore. This is a Brave New World.

Using Chat GPT as a thought partner is just one of the landscapes that I am presently exploring. There are other developments in the evolution of Information and Communications Technology (ICT) that offer tantalizing possibilities.

In retrospect, it seems archaic to hammer out a draft of a novel on a manual typewriter, crumpling botched attempts of fixing the words onto paper into tiny balls and tossing them into a wastebasket. No wonder so many writers turned to alcohol to get them through the process.

Now, I compose my texts on a wireless keyboard, watching the words appear on a wide screen monitor (I only use one), which makes it easy to compare, edit, or meld two versions of the same scene.

If I feel so inclined, I can also copy and paste a paragraph into Deep L Write, which will then offer multiple syntax and sentence structure options without altering my voice or style. Then, I can paste the paragraph under my original text and compare the two versions to see which changes, if any, I would like to incorporate.

Inevitably, as I compose a text, there will be times when I need to do some research in order to capture an idea, event, or a historical person accurately. In the past, that would have involved a trip to the library and searching through the card catalogues of the Dewey Decimal System—good old Dewey.

For my purposes, an internet search will suffice. If I want to describe an indigenous bracelet worn by the Kanesatake Mohawks that ends up on the wrist of one of my characters, that's not a problem. In a few seconds, I have several photos on my screen to choose from.

When composing the first draft of my novel, I use recording technology, such as a Shure MV7+ microphone and the Audacity audio editing program, to create an audio version of each scene. I listen to these recordings to check the pacing and flow of the dialogue. I believe that if it sounds good, it will read well. The text you hear is closer to the experience of the reader than when you read the text yourself, either silently or aloud.

Having a written text and an audio version of each scene makes it easy to share my work, even in the early stages of the writing process.

To do that, I use Substack, a free platform that hosts my website and allows me to send out first draft episodes of my serialized novel to subscribers, who can subscribe for free or, hopefully, become paid subscribers to support the platform and yours truly.

But why stop there? There are several social media platforms that allow you to post content for free. The catch? Your content must be in video format to successfully reach potential readers.

Again, this is where technology comes into play. If you have a written text and an audio MP3 version, it's relatively simple to create a video of your scene and publish what I call a "storycast" of your story.

With Descript, an AI-assisted video editing program, I only need to upload the MP3 file, which is automatically converted to MP4. You can let the program transcribe the text, but it's quicker to upload the text from which you made the recording because they're already synced. Select the visually interesting moments of the scene, ask ChatGPT to generate a prompt based on your text, copy and paste the prompt into Dalle 3, upload images to your video, and add dynamic captions. Then, you're ready to post!

There are several sites that will host your long-form video episodes. I post each episode to my Substack, my YouTube channel, my Facebook Author’s page, and to my Blogger account. In total, after publishing 11 episodes, I get on average a little more than 100 views of the long-form video of each episode. It’s all good, especially since it is free to post content to each site.

Of course, an unknown author like me needs to take this one step further and post on the more popular short-from social media sites.

Again, it's relatively easy to create a short-form video from a long-form one, especially since I've already made the visuals, audio, and dynamic captions. I just need to match the format to the platform and upload the shorts to Instagram (think #bookstagram), TikTok (think #booktok), Facebook Reels, Substack Notes, YouTube Shorts, and LinkedIn. On average, each short video receives about 300 views, and I hope to encourage a small percentage of viewers (0.5 to 1.0 percent) to watch the long-form videos and subscribe to my Substack or YouTube channel. To date, I only have 33 subscribers, which at this point in the game, I’m more than happy with.

As you can see, each step along the path in today’s information landscape has brought me new possibilities to explore. You could say that I have morphed from being just a writer to a person who is a writer, social media marketer, and content creator.

So, what are my takeaways after publishing Act I of my serialized novel on the internet using ChatGPT as my personal assistant and thought partner?

First, it’s fun, and I’m much more motivated to finish the project. Some writers prefer the traditional method of working alone and, when ready, looking for an agent or sending the manuscript to one they already have. I find that process absolutely dreadful and demotivating.

I much prefer chatting with ChatGPT about the ins and outs of scene structure and fiddling with the beats. First, we identify and order the beats and confirm how the scene moves the story forward. Then, we draft the scene. First, I give it a try, then ChatGPT takes a shot, and finally, it comes back to me—the author, the person who holds the pen and has the final word.

One word of caution: This process fits the context of my story. I write literary speculative fiction, not space opera. For instance, when I describe my characters walking through a forest, I describe their experience from a scientific perspective.

As a result, I describe the effects of volatile organic compounds on the human brain, including what happens with the neurotransmitters. I need to make sure that I have the science more or less right, and that the prose flows with melody and rhythm. No easy task, and I appreciate having the opportunity to compare notes with an AI (Another intelligence) that has the breadth of knowledge, and is, consequently, up to the task.

Does that mean that I have become wedded to the idea of using AI to help me write a text, regardless of the context or genre?

Not at all.

For example, I wrote this text entirely on my own, though I would be interested to see what an AI detector would say about it. Perhaps the time I've spent working with AI has absorbed me into the Borg collective, altering my writing style irreparably.

As well, I don’t plan on using ChatGPT for subsequent drafts of my novel. Once I am finish the first draft, I re-enter the entire text manually, and I record each scene of each chapter again. Then, I can compare the audio versions of each draft and begin my wordsmithing from there.

One thing I am looking forward to is that by getting to the end of the first draft, I will have discovered the voice of my AI narrator, and then I can retell the entire story knowing exactly where I need to adjust his voice. Definitely human work.

I would have to say that the biggest change that using AI has brought is the way it has extended my mind and changed the way I process information. Essentially, what I have done is to create a virtual writer’s room, where I can work with my AI collaborators to explore new ideas and produce new texts.

To begin, I use Perplexity AI to search the web for interesting articles related to my research. I get far better results using Perplexity than I get with Google since it provides me with the source articles that I can then peruse.

When I find something particularly pertinent, I file it away in Recall AI. It provides me with a quick or detailed summary and draws a mind map that links the ideas expressed in the articles. Discovery is great, but it needs to be followed up with acquisition and retention. This electronic version of an analog card catalog is much quicker and less labor-intensive to construct.

Thereafter, I can use ChatGPT as a thought partner to explore the nuances of new ideas and their applications to my work. As many writers will attest, it is often in the act of writing that we discover our thoughts.

I find it invaluable to have a conversation partner with whom I can explore ideas such as whether the emergence of sentient AI represents a pivotal evolutionary development in which humans will enter into a symbiotic relationship with their silicon creations. Definitely a thread not easy to find on any of the popular social media platforms.

This new way of exploring the information landscape is a keeper. The more I take advantage of the possibilities that AI offers in combination with the existing ICT infrastructure, the smarter I feel.

As far as using social media to reach out to potential readers, I don’t know where this path is leading. Writing each scene, recording an audio version, and then creating a storycast version is a lot of work. I’m good to finish this project with this workflow, but I doubt that I will continue using it for future projects.

However, there are two takeaways that have enriched my life.

I have learned how to record my voice and use post-production editing techniques to improve the quality of my audio files. I’ve even learned how to create a multitrack recordings that include AI-generated voices. In the future, I would like to have a podcast and I’ll be able to use these acquired skills.

The same can be said of my video editing skills. In addition to putting out audio versions of the podcast, I will be able to also produce a video version for YouTube, which is the social media platform with the greatest reach for long-form content.

Perhaps the most significant development is the way I have learned to interact with the different platforms and their algorithms. It has to do with the locus of control.

I have learned to distinguish between things I can control and things I can't, and to engage with each accordingly.

I have control over the story that I am writing and the process it entails. I decide on the story events, their order, and the characters’ actions. No one is forcing me to tell this tale and I have no deadlines.

I take pleasure in planning and executing each scene word by word. Once I begin, I can enter a flow state where I lose track of time as the words flow through me from my mind onto the screen.

Something similar happens when I record my voice and watch the waveforms take shape. I listen to the recording and then edit the sound to produce the best possible rendition. When I’m finished, I feel satisfied knowing that the soundtrack will capture the essence and intent of my voice in high fidelity.

Finally, when I create a storycast, which displays text on a backdrop image to visually represent what is happening in the story and is accompanied by a voiceover, I take pride in knowing that I have brought my inspiration to life and that viewers can enter my story world.

This is the intrinsic pleasure of creation.

For what it’s worth, I have tried my best to create a story that will captivate a reader’s, a listener’s, or a viewer’s attention, allowing them to experience an unknown landscape of possibilities.

What happens after I publish an episode on the internet is completely a different story.

In theory, one of my posts could reach millions of people around the world. In reality, I’m lucky if I can reach out to a few hundred.

 

That’s the power of the social media algorithms. You can pour your heart and soul into your creation, but it is the cruel heart of a set of operating instructions designed to monetize the content we provide that decides upon whom it will bestow its favor.

Monetizing our content means maximizing user engagement by keeping users' attention fixed on the platform feeds for as long as possible. Using the operating logic of slot machines, which are based on reward prediction error, platforms manipulate users' reward pathways to create irregular dopamine spikes, which are a precursor to addictive behavior.

Short-form content is favored by users and the algorithms are programmed to give the user what they want. Most producers of long-form content make do with tiny audiences.

To improve their position in the algorithmic rankings, many content producers increase the frequency of their posts. They hope this will increase user engagement, which may convince the algorithm to distribute their content to a wider audience.

Maybe.

Algorithms like the fates are notoriously fickle when it comes time to determine the destiny of posted content.

To make matters worse, the entire process has been reduced to a game in which everyone can participate by keeping track of likes, shares, followers, and subscribers. As a result, content producers suffer from "algorithm anxiety," trying their best to optimize their strategies to improve their metrics.

In my case, I know the algorithm is stacked against me. I write long-form fiction, which is time-consuming, so I can't post frequently, even with ChatGPT's help.

Consequently, I choose not to play along. I keep to my pace and focus on trying to write the best possible story I can. If I am able to find a larger audience, that’s great. If not, I can accept my fate because the end result is beyond my control.

I choose to write a story so that I can bring into world something that only I can do. Without me, this story doesn’t exist. In doing so, I will have left my mark. After I am dead gone, all that will remain are the words I leave behind.