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AI Panic and the Long History of Bad Predictions
“When you're going through hell, keep going." This podcast is about failure and how it breeds success. Every week, we talk to remarkable people who have accomplished great things but have also faced failure along the way. By exploring their experiences, we can learn how to build, succeed, and stay humble. The podcast is hosted by author and former TechCrunch and New York Times journalist John Biggs. He also hosts The Innovators, a podcast focused on brand new startups and C-Level Executives and Creators. If you’d like to appear on either show, email john@biggs.cc. Our theme music is by Policy, AKA Mark Buchwald. (https://freemusicarchive.org/music/policy/) AI Panic and the Long History of Bad PredictionsDon't be afraid of AI but don't fall in love with it, either.
A bearded man with a thick accent sits in a podcast studio. An earnest, British interviewer sits across from him. He asks a simple question: what will happen to AI in 2027? The expert’s response? Based on “prediction markets” and comments by “tops of labs,” artificial general intelligence and robotics will combine to create 99% unemployment. Humans will be rendered useless and robots will take over our menial tasks like raking leaves, brain surgery, and childcare. The result? To quote the great Dr. Peter Venkman, “Human sacrifice, dogs and cats living together... mass hysteria!” What do we do to survive the coming AIpocalypse? Should we shut everything down? Install OpenClaw? Ask AI how to save ourselves? Fortunately, all of that won’t be necessary. Doomers have landed on every intellectual shore since the invention of the written word and this situation is no different. Let’s explore why the End is Not Near. Idle HandsThe Jura Mountains are harsh in the winter months. Snow settles over the glades and pastures where, all summer, farmers fatten cattle and sheep and prepare cheeses for sale in town. For generations, these mountains moved between two states, open and green under the sun, then sealed in ice as winter took hold. Families crowded into small houses, often sharing beds for warmth, and worked through the dark months to keep the hearth alive. Travel was hard. Roads disappeared under snow, and the valleys turned inward. Life in these hollows was cold and uncertain, shaped by isolation and the slow passing of days. For much of that time, survival was the only goal. Families conserved what they had, stretched food as far as it would go, and waited for the thaw. The summer paid for the winter, and little more. Then, in the 1700s, something changed. Watchmaking grew into a major trade across Switzerland, France, and parts of Germany, with thousands of pocket watches produced each year. Swiss makers in particular built a reputation for precision and careful work. In Geneva, shaped by Calvinism, cultural norms favored restraint in dress and limited displays of wealth. Craftsmen who once worked in jewelry moved toward watchmaking, which could be framed as useful rather than decorative. Over time, watches still carried status, often richly finished, especially for buyers beyond these stricter communities. To meet rising demand, watchmakers developed a system known as établissage. Organizers based in towns like La Chaux-de-Fonds and Le Locle spread work across the mountains. They supplied parts, tools, and instructions to farming families. In return, those families produced components through the winter. Wheels were cut and polished. Cases were shaped. Springs were finished by hand at small benches set near windows for light. It was not a factory system in the modern sense. It was a network. Each household handled a narrow task. The finished pieces moved back down the valleys, where they were assembled into complete watches and sent out into the wider market. The geography made this possible. The Jura valleys were remote, yet still tied to trade routes. Winters were long, and time indoors could be turned into labor. Protestant refugees, including Huguenot watchmakers, carried technical knowledge into the region. That knowledge did not stay in the towns. It spread, slowly, into the farms. By the 18th century, the region had become a watchmaking belt without the appearance of one. There were no large industrial buildings, no central floor of machines. There were houses, small rooms, and steady hands, each part of a system that reached far beyond the mountains. Many of these établissage towns became hubs for watchmaking and remain so today. Then something else changed. Trenton Makes, the World TakesIn the 19th century, this system began to weaken. In about 1760, England began mass-producing textiles with machines, bringing the advent of the Industrial Revolution. The primary job for humans moved from an agrarian society to an industrial one, and nearly everything changed. The Industrial Revolution did not eliminate handwork, but it reduced its central role in production and placed it alongside methods that were faster, more consistent, and easier to scale. Nearly everything, from dishes to cigars to pocket watches, became cheaper and more widely available, and that shift rested on a new kind of labor system that concentrated workers in factories where time, motion, and output were closely managed. The great hubs of manufacturing, Murano for glass, Lyon for silk, and the expanding factory towns in Britain and the United States, showed how production could be organized differently. Work moved into larger, centralized spaces where tasks were divided into repeatable steps, tools and machines ensured uniformity, and output could be increased without relying on the pace of individual craftsmen working at home. The Industrial Revolution did not eliminate handwork, but it reduced its central role in production and placed it alongside methods that were faster, more consistent, and easier to scale. Nearly everything, from dishes to cigars to pocket watches, became cheaper and more widely available, but the system that produced them depended on dense industrial labor, where, as Engels wrote, “the filth and tottering ruin surpass all description.” At the same moment, defenders of the factory system pointed to its output and its order. As Adam Smith wrote in The Wealth of Nations, dividing production into small, repeatable tasks could multiply output many times over. In his example of a pin workshop, a group of workers, each performing a single step, could produce thousands of pins per day, far more than any one craftsman working alone.
The result of this societal explosion was never fully resolved. Goods that had once been rare became common. A pocket watch, once a sign of wealth, moved into the reach of a broader public. At the same time, the conditions under which many of those goods were made drew sustained criticism. Charles Dickens captured the atmosphere in fiction, describing industrial towns as places of “ red brick, or of brick that would have been red if the smoke and ashes had allowed it,” an image that reflects how pervasive and inescapable factory life could feel. For regions like the Jura, this shift changed the entire economy. The home workshop, tied to the rhythm of the seasons, could not match the steady output of centralized production. As factories expanded elsewhere, they set expectations for price and volume that the older system struggled to meet. Handwork did not vanish, but it moved into a narrower role, often reserved for finishing, adjustment, or higher-end production where precision and reputation still carried weight. The true experts in the Jura could eke out a living making watches by hand, a desirable product for dandies who valued authenticity over mass production. But most people were fine with a watch pressed out of tin that eventually only managed to be right twice a day. All of this is to say that upheavals have hit humankind in waves, each one reshaping how people live, work, and understand the world around them. The Industrial Revolution did not just alter production; it reordered society and set the stage for what became the Victorian period in the United Kingdom and beyond, a time marked by expansion, classification, and a growing belief that the world could be measured, cataloged, and controlled. During this period, knowledge itself began to function like an organized field of work. The deciphering of Egyptian hieroglyphs by Jean-François Champollion in 1822 turned ancient Egypt from a field of speculation into something that could be read, studied, and placed within a broader account of human history. Museums filled with objects brought back from expeditions, and scholars set about classifying languages, plants, and human societies into ordered systems that reflected both curiosity and a drive to impose structure. At the same time, cities drew in those with aptitude and gave them space to develop skills that did not depend on physical labor alone. Children who might otherwise have remained tied to agricultural work were, in some cases, pulled into schools, workshops, and offices where literacy, calculation, and analysis mattered more than strength or endurance. This did not replace manual labor, which remained widespread and necessary, but it did create room for new kinds of work centered on planning, interpretation, and administration, work that depended more on the mind than on the hand. Education expanded in a more formal way. Systems of public instruction grew across Europe, shaped by earlier models in Prussia that emphasized discipline, literacy, and standardized curricula. These systems produced clerks, engineers, administrators, and officers who could operate within large institutions, whether those institutions were factories, governments, or imperial bureaucracies. Learning was no longer limited to a narrow elite, and it began to serve the needs of a society that required coordination at scale. It was now possible to send an educated young man anywhere in the world — to India, say — and he could, through the benefit of rote memorization and codified rules, mimetically copy an entire culture. This expansion of knowledge and education ran alongside the outward movement of European powers. Industrial capacity supported longer voyages, larger armies, and more complex supply chains, which in turn enabled the extension of control over distant territories. For example, Nicolas Appert, a French candy maker, heard Napoleon’s call for a method of food conservation that would allow the General to march harder and longer. Appert, understanding the value of bottling wine and milk, began to bottle entire meals, from soups to eggs to whole chickens. Unaware of bacteria, he simply stuffed the bottles with food, corked them, and heated them for an arbitrary length of time, which we now recognize as an early form of pasteurization. An army that marched on its stomach could now march much further, leading to Napoleon’s downfall as he marched to distant Moscow. Education, mass production, and administration became tools of expansion, providing the structure needed to govern far from home. The same systems that organized factories and cities were applied, often unevenly and with lasting consequences, to the management of colonies. The pattern is unmissable: a technological shift increases capacity. That capacity produces more goods, more information, and more movement. Institutions rise to manage the flow. People adapt, sometimes slowly, sometimes under pressure, and the shape of daily life changes in ways that are difficult to reverse. And so we come back to our cranky scientist and his erstwhile interlocutor. The End Is Not NearI have always loved the work of James Burke and his Connections series. Found in magazines and on television, Burke walked through history like a drunk, stumbling eventually into the bright lights of our modern age. From the compass to the nuclear bomb, from a stirrup to the Internet, Burke saw the thread that connected each innovation to the next, inexorably. I’ll try to do the same here. The aforementioned dark oracle, Dr. Roman Yampolskiy, is right to raise an alarm about AGI. He is talking about a system that, once it crosses a certain line, will no longer behave in ways we can predict or correct. This fear, according to many experts, is unwarranted and will never happen under the banner of generative AI, aka anything that burbles out of ChatGPT. Instead, we have to look at the long thread of history. Ed Zitron writes about a bit of Kevin Roose AI doomslop that posits that AGI is only years away. He notes:
Zitron hits the nail on the head: the plant manager of the pin factory is telling everyone they will need 1,000 pins in their homes in the next few years. What the AI doomers are right about is that the world is changing drastically, especially in the realm of menial work primarily associated with parcel delivery and manufacturing. Robots will definitely take away trucking jobs and warehouse work. AI will make middle management roles redundant, forcing folks with “email jobs” to rethink their positions. Short-sighted bosses will set up OpenClaw and think they’ve replaced their accountant, logistics team, and Human Resources crew. They will very quickly find out they are wrong. Because, as we’ve learned, every groundbreaking technology is absorbed into humanity like a paramecium gobbling up a passing cell, drawn in, broken down, and folded into the body until it is no longer foreign but part of the organism itself, changing its shape, its habits, and its reach, without ever replacing the thing it set out to consume. AI is supercharging our intellects. Decisions that once took hours now take seconds. Judgments that once required experience are being handed to systems trained on vast, uneven datasets. That’s true. Robotics are going to replace truck drivers very shortly. This displaces a massive number of human drivers who will have to figure something else out. AI has already become a cognitive crutch, not unlike the calculator or the smartphone, but more invasive. A calculator replaces arithmetic. A phone replaces memory. AI begins to replace judgment, voice, even the act of thinking through a problem. People are not just using it to check answers. They are using it to form the answers in the first place. That changes the relationship between the user and the tool. It also changes the user. There is also a psychological layer that is harder to measure. AI psychosis is no longer a fringe concern. Users begin to treat outputs as insight rather than synthesis. They assign intent where there is none. They build a sense of dialogue with a system that has no awareness. The danger comes from the form. These systems speak in complete sentences. They mirror tone and they simulate caring all in an effort to keep you paying $20 a month for a Claude subscription. The human brain responds to that pattern as if there is a mind on the other side and when the computers get fast enough it will seem like that mind is truly thinking. But all of that is a symptom of a body sick due to a new invader. And thus far, that body has fought off those invaders with ease and the organism that blew out of that sickness is almost always (eventually) fitter, happier, and more productive. Yampolskiy’s warning is valid. There is a very real chance that if AGI arrives in the form he describes, 99% of us could be displaced, not gradually, but all at once, and on a scale that would wipe out all commerce and growth. In that framing, ninety-nine percent is less a statistic and more of a flashing red sign that says “Ice on Road” in July: it’s helpful, but not right now. His warning is worth taking seriously. Dismissing him outright would be a mistake. But the chances of that outcome unfolding in any clean, total way remain slim. History does not move in straight lines, and it rarely delivers the full weight of a prediction all at once. Systems resist change, even when change is inevitable. People find uses for tools that their creators did not intend, and they hold on to roles long after those roles seem obsolete on paper. We have heard versions of this warning before. Thomas Malthus believed population growth would outstrip food supply and push humanity into scarcity and collapse. The Industrial Revolution canceled his prediction. But in his time, he was observing real pressures and projecting them forward. What he missed was the capacity of systems to change under stress. Agriculture did not stand still. Technology did not stand still. Human behavior did not stand still. The pressure did not disappear, but it shifted. David Ricardo warned that mechanization would drive workers into permanent unemployment as capital replaced labor. He saw the machine as a force that would strip away livelihoods faster than society could adjust. What he did not account for was the way new industries would absorb labor, often in forms that looked nothing like the work that came before. John Maynard Keynes wrote about “technological unemployment,” the idea that machines would outpace our ability to create new jobs. He expected a future where people would struggle to find purpose in a world with too little work. Instead, work persisted, though it changed shape, and in many cases expanded into domains that had not existed in his time. The same pattern appears again and again. Each wave of automation raises the same question: what happens when machines take over the work? The answer? Some work disappears. Some work changes. Some work emerges in places that were not visible before. The transition can be painful, even destabilizing, but it is rarely total. That does not mean Yampolskiy is wrong. It means his warning sits at the edge of possibility rather than at its center. AGI, if it comes, will not land on a blank slate. It will land in a world full of regulation, inertia, politics, fear, and habit. It will be shaped by those forces, slowed by them, redirected by them. The outcome will not be a single moment where everything ends. It will be a series of adjustments, some sharp, some slow, all uneven. In short, AGI will be born into a world with two terrible foes: human brilliance and human incompetence. We’re already seeing one of those personified by the modern rise of populist governments. We’re just waiting on the brilliance. Sheep herders in the Jura Mountains turned into watchmakers, who, in turn, turned into bureaucrats. A lacemaker began running a loom, and that lacemaker’s children went on to spread industry globally and build trade routes and technologies that brought distant lands close to home. At the risk of sounding like Buck Rogers, I’ll spare you my expectations of what will happen to the countless people made redundant by AI and robotics (Hint: we’ll need people in space), but in the end, we’ll still need people. We often forget that humans, when faced with cold winters, will always strive to create their own invincible summers. You’re currently a free subscriber to Keep Going - A Guide to Unlocking Success. For the full experience, upgrade your subscription. If you’ve been reading or listening to Keep Going for free, you’ve already seen the value of having independent work that isn’t shaped by corporate sponsors or the news cycle’s noise. But independence has a cost. If you find something useful here, if these words make you pause or think, I’m asking you to step up. A few dollars each month means I can keep doing this work without compromise. Without your support, this project stays fragile, balanced on the backs of a few. © 2026 John Biggs |








Generated Weekly: Who killed Tilly Norwood?
A quick look at the Generated Video space from my other newsletter.
Generated Weekly: Who killed Tilly Norwood?
Plus AI slop and 3 tools to replace Sora
If you have been following the Tilly Norwood saga, you might have noticed something odd on April 1. The AI actress and singer announced she was shutting down, effective immediately:
After careful consideration, we’ve made the difficult decision to deactivate Tilly Norwood indefinitely and retreat from the public eye.
While Tilly remains grateful for the support of her fans, the volume of negativity and criticism has become impossible to ignore. It’s clear that the world is simply not yet ready.
Thank you for being part of her journey.
As you might have guessed, Tilly’s demise was an April Fool’s joke, one aimed at the countless detractors of Norwoods particular brand of uncanny valley video.
Norwood’s creators claim that 18 humans were involved in the production of her videos, from production designers to costumers to prompters. They also claim that a human actor took part in the production, probably in some form of motion capture. It’s unclear how much of Tilly is real but we can assume that no human was involved in writing “They think I’m just a dollar dream/ But I’ve got more than they believe/ I’m not a puppet, I’m the star/ Guided by the heart, that's who we are.”
As expected, the “shutdown” was an April Fool’s joke, aimed as much at her critics as at her fans. It also served as a reminder of how strange the reaction to Norwood has been. Few synthetic performers have drawn this level of attention, or this level of irritation.
Norwood’s creators claim that as many as 18 people were involved in producing her videos, including production designers, costumers, and prompt writers. They also suggest that a human performer contributed, likely through motion capture or reference acting. What remains unclear is how much of Tilly is authored by humans and how much is generated. It is safe to assume, however, that no songwriter sat down and earnestly wrote lines like: “They think I’m just a dollar dream / But I’ve got more than they believe.”
Tilly is the product of Particle6, a London-based studio focused on building AI actors and comedians. She functions as both a proof of concept and a marketing tool, a way to show that AI video production can be structured, staffed, and, at least in theory, controlled. The goal is not just to entertain but it is to convince skeptics, particularly in film and advertising, that this kind of production is viable and not simply a form of automated plagiarism. Tilly’s creator, Eline van der Velden, even claims to have received death threats.
The response has been uneven. When one of Norwood’s videos appeared around the time of the Oscars, critics focused on what they saw as a lack of presence. The performance felt hollow and the music felt assembled rather than written. There was a sense that something essential was missing, even if viewers struggled to define what that was.
The criticism has not been limited to aesthetics. It has also drifted into philosophy and even theology. One essay, published in a religious context, compared Tilly to the early Christian heresy of Docetism, the belief that Christ only appeared to have a physical body and did not truly exist in material form. The argument is not entirely absurd. Tilly presents the image of a human being without any of the underlying reality. She appears to feel, to perform, to exist, but there is nothing behind the surface.
This may be the first time, outside of early reactions to the printing press or photography, that a new medium has been criticized not for failing to capture reality, but for simulating it too cleanly. The complaint is not that it is broken but that that it lacks friction, and without friction, it feels unreal.
Tilly Norwood is not going away. The April Fool’s post made that clear. If anything, the reaction proves the opposite. She has found a nerve, and for now, she’ll on the last of it.
News Roundup for April 2, 2026
Chuck Norris’ family left furious over AI-generated videos of star after his death
The family of Chuck Norris has spoken out after a wave of AI-generated videos spread false claims about his death. Norris died at age 86 following a medical emergency in Hawaii, and his family said online clips have circulated misleading details about his health, the circumstances of his passing, and even family relationships. In a public statement, they urged fans to rely only on official sources and not to share unverified content.
The response comes amid widespread online attention following Norris’s death, with tributes from public figures and emotional messages from his children. While the family reflected on his life and legacy, they also pushed back against what they described as fabricated narratives driven by AI content. The situation highlights how quickly misinformation can spread after a public figure’s death, especially when synthetic media is involved.
Google Faces Calls to Prohibit AI Videos for Kids on YouTube
More than 200 child development experts, advocacy groups, and educators are urging Google and its video platform YouTube to stop showing or recommending AI-generated videos to children. In a letter addressed to CEO Sundar Pichai and YouTube head Neal Mohan, the group warned that much of this content, often labeled “AI slop,” is low quality, mass-produced, and designed to capture attention rather than educate. They argue that these videos may harm children’s attention spans, blur the line between reality and fiction, and replace activities that are important for social and emotional development. The letter was signed by figures including Jonathan Haidt, along with organizations like Fairplay and the American Federation of Teachers.
YouTube responded by saying it already limits AI-generated content in YouTube Kids to select channels and requires labeling of synthetic material, while also allowing parents to block content. Still, advocates argue these safeguards are not enough, especially for very young viewers who cannot understand such labels. The debate comes as AI-generated children’s content grows rapidly, driven by creators who can produce videos cheaply at scale, and as broader scrutiny mounts over social media’s impact on young users. Google has also invested in AI-driven kids’ content through companies like Animaj, a move critics say contradicts concerns about screen time and child safety.
Sora is gone — but these 3 AI video tools are already replacing it
The TechRadar piece argues that while OpenAI’s Sora has been shut down, the broader AI video space is not slowing down, it is fragmenting and maturing. Instead of one dominant tool, users are now choosing from several specialized platforms that match or exceed Sora’s capabilities in different areas. The article highlights three main replacements: Google’s Veo 3.1, which focuses on high-quality, multi-scene video generation with integrated audio; Runway Gen-4.5, aimed at more advanced users who want deeper editing control; and Kling AI 3.0, a simpler, more accessible tool that can generate longer clips and is easier for beginners to use.
The takeaway is that Sora’s disappearance does not mark the end of AI video, but a shift in how the market is structured. Instead of a single, general-purpose tool, the space is now defined by competing systems with different strengths, pricing models, and levels of complexity. This makes the ecosystem harder to navigate, but also more flexible, with options tailored to both casual creators and professionals.
Generated is a newsletter about the craft behind AI-powered video. Edited by John Biggs, it looks at what happens when video production and AI tools start to merge. The focus is on the people, tools, and techniques we are using in the fascinating medium.
© 2026 John Biggs
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