The Long Tomorrow — AI and Robotics Takeover (5/12)
What Happens to the People?
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The machines aren’t coming. They’re already here — and they’re replacing people faster than we’re willing to admit. If you think that’s alarmist, I’d encourage you to look around. The entire premise that we can see this wave coming and simply step aside, reskill, or out-hustle it, has become not just outdated but delusional. In the span of just a few weeks and months, entire sectors have begun to buckle under the weight of automation and artificial intelligence, and we’ve barely scratched the surface of what’s to come. The mood in the professional world has shifted, almost imperceptibly, from a sense of resilient optimism to a low, persistent anxiety — the feeling that, for the first time in living memory, there may simply not be a meaningful place for most people in the future of work.
A month ago, in both my The Professional Collapse ebook and my Substack post that inspired it, I outlined the deep, structural transformation now underway in white-collar work — a kind of slow-motion implosion that’s rippling outward from traditional professions, engulfing everyone from junior accountants to radiologists to mid-career attorneys. The professional class, for all its advantages and prestige, is not immune to creative destruction; in fact, it is now among the first and most vulnerable targets of the new automation paradigm. In that work, I tried to illuminate a truth we’ve been dancing around for decades: the “knowledge economy” was always a transitional phase, not a final destination. Now, as AI and robotics sweep across the landscape, it is becoming brutally clear that professional collapse is not just possible — it is inevitable, unless we fundamentally rethink how we define contribution, value, and purpose in a society where work, as we know it, is no longer required of most people.
Artificial Intelligence Is Not a Distant Future Event
As we all already know all too well, artificial intelligence is not a science-fiction scenario or a decades-away problem for our children to figure out. It is already reshaping industries, rewriting job descriptions, and eliminating roles that just ten years ago seemed unassailable. This transformation is happening both at the visible margins — where self-checkout kiosks quietly replace cashiers, or chatbots handle customer service inquiries — and at the invisible core, where algorithms are now making decisions (or at least making wisened suggestions) that once required years of specialized training and judgment. Across sectors as diverse as logistics, medicine, law, marketing, and finance, the hard truth is that automation is not just displacing people at the edges of careers. It is hollowing out the center.
From the outside, it’s tempting to assume that these changes will unfold gradually, with plenty of time for society to adapt, retrain, and find new equilibrium. But this is wishful thinking. As anyone who has watched the rapid deployment of AI systems just this year alone knows, the pace is not incremental. It’s exponential. Roles that were considered “safe” only a year or two ago are now under existential threat, and the people who filled them are already feeling the ground shift beneath their feet.
Displacement at Scale
What makes this moment so unsettling is not simply that jobs are being lost, but that the pattern of loss is fundamentally different from any previous wave of technological disruption. In the past, when factories shut down or industries went into decline, the process was visible, dramatic, and — crucially — localized. Entire towns could be upended, but the crisis was at least contained, and the nature of the disruption was clear: a plant closed, a new technology took over, people moved (or didn’t), and new jobs eventually appeared somewhere else. It’s also greatly, fundamentally different than the Industrial Revolution.
This time, the disruption is silent and systemic. It’s not a headline-grabbing event; it’s a quiet process of replacement. Algorithms are replacing analysts, bots are replacing brokers, generative models are replacing marketers and designers, autonomous systems are replacing service workers — and this is all happening in parallel, across every sector, with no natural endpoint in sight. What’s especially alarming is the breadth of roles at risk: not only are blue-collar and service jobs being eroded by robotics and intelligent platforms (from warehouse automation to self-driving vehicles), but white-collar work — the backbone of the middle and upper-middle class — is being targeted as well.
Legal assistants, medical coders, junior financial analysts, even software engineers: all are now vulnerable. The supposed immunity of the professional class was always a comforting myth, but now it’s been exposed as just that — a myth. Machines that don’t sleep, don’t age, don’t unionize, and don’t slow down are absorbing entire categories of work that, until very recently, were the province of well-paid, well-educated humans. (Just read what I achieved, for example, in 16 hours only nine days ago: A Case Study in the Incredible Power of AI-Assisted Professional Work.) This is not a temporary phase or a bump in the road. It is a structural reset — a reordering of what it means to be economically relevant in the 21st century.
Even the Creative Fields Are Not Safe
For a long time, there was a narrative — repeated by pundits, HR departments, and even some tech visionaries — that creativity was the final frontier. That the arts, content creation, and human imagination were so uniquely personal, so dependent on the ineffable spark of inspiration, that they would remain beyond the reach of machines. In the past year, that narrative has collapsed. Nowhere is this more evident than in the media and entertainment industries, where generative AI has begun not just to assist, but to originate.
Just 13 short days ago, I published an article about the short film Barney—The End of Lawyers (if you haven’t yet seen the short film or read my commentary on it, you need to — get on it!), a surprisingly affecting animated work created entirely by artificial intelligence and stitched together 8-second-clip by 8-second-clip. What struck me — and many others who saw the film — was not just its technical polish and lack of continuity issues, but how quickly the technology behind it had advanced since Veo3 debuted on May 20th. It wasn’t simply that the AI could generate visuals and dialogue indistinguishable from human output; it was that a human was even still necessary to assemble those elements into a coherent, moving story. The implications for Hollywood, for advertising, for animation, for music — really, for any field that has long rested on the assumption of irreplaceable human genius — are profound. If a generative model can spin up a 8.5-minute short film so quickly (even with human stitching still required for now), what does that mean for the thousands of screenwriters, storyboard artists, voice actors, and editors who, until recently, considered their livelihoods untouchable?
It isn’t just “low-end” creative work at risk. Already, some of the most lucrative and prestigious roles in writing, music composition, design, and illustration are being threatened by tools that can, at the push of a button, create commercial-grade output at a fraction of the traditional time and cost. The shift is not theoretical. It is happening in real time, and the result is a kind of creative disruption that doesn’t just augment or empower humans, but increasingly renders them unnecessary. The old idea — that creativity would be a permanent refuge — is evaporating in the face of generative models that can mimic, iterate, and even innovate in ways that most people simply can’t keep up with.
And, the Disney / Universal Studios v. Midjourney IP infringement lawsuit be damned! That’s just not going to play out like what happened to Napster in 2001.
The Myth of the Retrainable Worker
Whenever the conversation turns to job loss and automation, the all-too-familiar refrain quickly emerges: “Sure, jobs will go away, but new jobs will be created. People will retrain, upskill, and find new ways to add value.” It’s a comforting story, and in some cases, it’s even true — for a subset of the population. But as I’ve debated with some people the past three months, the idea that every displaced worker can simply be retooled for the new economy is both historically naïve and, increasingly, mathematically impossible.
The reality is far starker. Many of the people being displaced today are over 50, undereducated, or already economically insecure. These are not the ideal candidates for rapid reskilling into the high-demand, high-complexity jobs of the future. Even for those with the right aptitude and motivation, the supply of new, well-compensated roles is nowhere near large enough to absorb the scale of current and projected dislocation. Most retraining programs, when you look beyond the press releases, are chronically underfunded, poorly designed, and rarely matched to the actual demands of the labor market. Success rates are low, especially for mid-life workers — and the “new collar” jobs that are available often pay less, offer less security, and require a level of digital fluency that’s simply not attainable for all.
And what about the young? Here, too, the narrative is breaking down. Many Gen Z graduates and early-career professionals are discovering, sometimes before they even enter the workforce, that the jobs they trained for are already being automated out of existence. In my College Majors for 2030 article, I examined the growing disconnect between higher education and economic reality. The skills that were considered “future-proof” only a few years ago are now, in some cases, obsolete before a diploma is even conferred. What are you supposed to retrain into when your “future-ready” skillset never even gets a chance to be tested in the marketplace? The result is a profound collapse of relevance, not just for older workers, but for millions of young people whose economic futures are being foreclosed before they begin. Talk about demoralization!
Longer Lives, Fewer Roles
This would be a grim enough scenario if it was only a matter of short-term dislocation — but it’s not. The timing of these changes is colliding with a second, equally momentous trend: the extension of healthy human lifespan. As life extension science improves, we can expect people not only to live longer, but to remain active, alert, and physically capable well into their 90s and beyond. The traditional model — retire at 65, enjoy a few years of leisure, and quietly exit the stage — was already out of sync with demographic reality decades ago. In the decades ahead, it will become even more completely untenable.
So, what happens when tens of millions of people are displaced from economic life in their 50s or 60s, but live another 30, 40, or even 50 years in good health? What fills that void? Work has always provided more than income. It structures our days, shapes our identities, offers a sense of contribution and purpose. Remove it, and you don’t just lose productivity — you risk mass psychological erosion, cultural stagnation, and political volatility.
This is the real risk: not just mass unemployment, but mass meaninglessness. We are facing a future in which millions of people will be healthy, connected, and (in some cases) well-resourced, but existentially adrift. The idea that volunteerism, hobbies, or passive leisure will be enough to fill that void seems, at best, untested and, at worst, dangerously naive. The broader social costs — in terms of health, cohesion, and civic life — could be staggering. And, breaking the news to Gen X and the younger generations that they’re going to have to work longer and later into life is radioactive at best.
What Happens to Human Dignity?
If you strip away all the technical jargon and economic theory, the core question at the heart of the AI and robotics revolution is one of dignity. What happens to human dignity when machines outperform us in every economic role? What fills the day — or the soul — when the structures that organized our lives and identities for centuries suddenly vanish?
If people are displaced in their 50s and live into their 90s, what will fill those 40 years? How do we maintain social order, individual mental health, and a sense of progress when most people are, in effect, surplus to the requirements of the formal economy? Are we capable, as a society, of building new structures of meaning and purpose that are decoupled from employment — or are we hardwired, both biologically and culturally, to require usefulness in order to feel whole?
This isn’t just an academic question. It’s an urgent challenge for policymakers, educators, and, frankly, all of us. If we do not grapple with it now — if we continue to assume that “something will come along” or that market forces alone will sort it out — we are courting not just an economic crisis, but a civilizational one.
Consider These Questions:
What happens to human dignity when machines outperform us in every economic role?
If people are displaced in their 50s and live into their 90s — what will fill those 40 years?
Can we build a society where purpose is decoupled from employment — or are we hardwired to need usefulness to feel whole?
The speed of change, the scale of displacement, and the absence of a workable societal plan all but guarantee that we will be living with these questions — and their consequences — for a long time to come. And as life expectancy continues to rise, these issues will only become more acute, more urgent, and more impossible to ignore.
Looking Ahead
In the sixth The Long Tomorrow article, I’ll challenge the comforting assumption that we can “just retrain” our way through this — and examine why most of the current models for reskilling are deeply flawed at both a practical and philosophical level. The era of easy answers is over. The Long Tomorrow demands that we confront hard realities — and find the courage to imagine new ways of living, contributing, and finding meaning in a world where the machines, for better or worse, are here to stay.
Let me know your answers to and thoughts on the three questions posed above.
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