Industry 4.0 and the Popular Imagination

cameron conover
Jan 2, 2019 · 6 min read

A population in search of new narratives needs a vivid demonstration of its possible futures.

Somewhere, something….

A month ago, when GM announced closing its American passenger car plants and cutting 15 percent of its salaried workers, some news stories anticipated a looming trade storm. Others reflected the fail-safe mentality honed by President Trump’s campaign or variations on the theme of JD Vance’s Hillbilly Elegy. The emotionally charged tone in outlets like the Washington Post is one of lament and resignation: “As for the future, (my dad) doesn’t see it getting better, and he’d cite GM’s announcement as evidence. Me? I’m hopeful that somewhere, something will end this hollowing-out of the middle class. I’m resigned to whatever lies ahead. When you don’t expect much, it’s harder to be disappointed.” When factories close down, stories of resignation abound, mirroring a community’s sense of loss. Rarely do we attempt to imagine how America’s industrial future will look.

The machine age of the 20th century has left us with its own cathedrals, monuments, and ruins. These shuttered plants and factories testify to a long history of brutal work and gargantuan change. Empty silos and rusting cranes are poignant artifacts of the postindustrial landscape. Meanwhile, new tools that will become as ubiquitous as brick and mortar are reinventing the way we will remake industy and the drastic changes in infrastructure that will impact every layer of society. The potential of 3D printing, AI, and Automation are essential in the continuing narrative about who we are and who we are becoming. Many companies are looking to invention to solve the problems American industry faces.

Nostalgia can be a more dangerous case of mass delusion than utopianism. A population dispossessed of a narrative desperately needs a vivid demonstration of its possible futures in order to grow with them, but these futures need to be realistic and productive.

America can build the foundation for a new industrial revolution as it reckons with its past.

It is exciting when change is necessary, and a new infrastructure is being built. Nothing should feel inevitable right now. It would be tragic to fool ourselves by heeding only the negative storylines of our present. There is so much that can be done, especially if the American imagination begins to work in new ways.

It is a difficult task for scientists and creators to describe the future of industry with the language of the present — whether that is the heavy remains of the machine age, our current notions of labor, or building a new infrastructure from the inventions of the third industrial revolution. Perhaps the fourth industrial revolution is in its infancy. If the noises it is making are incoherent for now, it is only because it is still searching for new words with which to express itself.

Industry 4.0 has become a buzzword, but this blanket term refers to new AI-aided processes that steer factories away from assembly lines toward intelligent machinery. The smart factory learns from the products it is building, using them as a metric to correct and make manufacturing decisions throughout the production line, with equipment communicating and adapting at every step. Decisions and improvements can be made rapidly, improving yield, reducing cost, and simplifying processes. This intelligent automation also reduces waste and the kinds of monotonous and dangerous tasks that make factory work so difficult.

Industry has the possibility, with an infrastructure that seeds invention, of no longer producing waste, or of wasting time, lives, or space. It is not a question of the least harmful choice, but of finding the optimal solution — the safest, most efficient design.

Industry provides a controlled, sufficiently rich dataset from which to train AI. Manufacturing already requires the clean room environment and data perfectly suited to train AI algorithms.

The variables of a human-based dataset cannot give AI a solid ground to build itself from. We have seen how using public data to train machine-learning algorithms can backfire. Ad tech, social networks, search, personal assistants, and chat bots have used the public as its guinea pig to varying results. AI algorithms trained through facial recognition and search keywords have shown their vulnerabilities and fallacies. Why did people searching for forest fire information in California receive ads for firearms? As soon as you buy something, you are bombarded with ads for the same thing. When you buy a washing machine, do you really need a second one? Americans give up data reluctantly out of perceived necessity — in order to get on with daily tasks, they must sign away information they’d rather keep to themselves. This system doesn’t have to dictate an inevitable future. AI can become something much more useful and less exploitative if we revise our thinking about how to use it. The invasive purposes of these algorithms could be considered (and hopefully are) ephemeral.

It is the framework itself that needs to be reimagined.

For AI to have a solid foundation, it needs to build the kinds of sturdy infrastructure that changes in the social and economic architecture can rely on. Rather than the framework being an old, artificial, and forced system sheltering and jerry-rigged to build new technology, it is the framework itself that needs to become intelligent.

We are still grappling with the prophesies of the computer age. The arcane knowledge of semiconductors, silicon crystals, and photolithography sparked the third industrial revolution led by Intel and a host of other chip companies in the 1960s. Gordon Moore foresaw how computers would become ubiquitous features of daily life. Yet the subjects of this law — chips sliced from silicon crystal containing billions of transistors or devices printed in two dimensions — were difficult to manifest in the popular imagination. Moore’s Law is now hitting its physical limit determined by quantum mechanics and thermodynamics. The tools being created by engineers today are equally difficult and complex to illustrate. Fear accompanies new technology when we don’t understand it. And history is difficult (perhaps impossible) to analyze as it happens, especially when it is moving so fast.

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GM exhibit, Chicago World’s Fair

During the Great Depression in the 1930s, World’s Fair expositions gave the American imagination a physical apparition of modernity. In the years between 1933 and 1940, amidst crushing economic collapse, international conflict, and encroaching war, the fairs exhibited design, manufacturing, engineering, and architectural futures. Creators conceived of possible worlds. Visitors walked into and around these worlds, envisioning a place for themselves within them.

In 1939, General Motors created a future urban landscape and factory to explore. I wonder how we can demonstrate new industry in such a vibrant way to people in search of its substance and meaning today. And how we can begin to imagine the future in positive, fantastical ways again. Whether through a VR tour through 2050, or the images of our future being written on three-dimensional chips or detected by high-resolution sensors or….

20th century modernity is a complex legacy. But it was a movement and moment in which architecture, art, design, and industry communicated with each other to build new stories of what life could be. Today, we are facing a revolution of similar scale, but with the knowledge, doubts, and critical eye that the twentieth century has bequeathed us as its complicated heritage. It is a hopeful time. It is a time looking for leaders, visual artists, illustrators, magnates, engineers, and storytellers. It is a time looking for its voice.

For this industrial revolution to take hold, we must see change as entirely necessary for our society’s survival, and its inventions must be used to rebuild a new infrastructure within the old. We cannot hold onto old patterns and models of thought…it is time to invent new answers to our questions, and new questions to our answers.

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