The War of the Eyeballs begins today, with the initial public offering of Google Glass. To mark the occasion, I give you my all-time favorite Marshall McLuhan quote:
Once we have surrendered our senses and nervous systems to the private manipulation of those who would try to benefit by taking a lease on our eyes and ears and nerves, we don’t really have any rights left.
Just a heads-up.
Toyota, which just yesterday announced a recall of more than six million cars for a variety of defects, is having second thoughts about its robot culture. A longtime pacesetter in factory automation, the company is putting a new stress on nurturing human expertise and craftsmanship, reports Bloomberg:
“We need to become more solid and get back to basics, to sharpen our manual skills and further develop them,” said [Mitsuru] Kawai, a half century-long company veteran tapped by President Akio Toyoda to promote craftsmanship at Toyota’s plants. “When I was a novice, experienced masters used to be called gods, and they could make anything.” These gods, or Kami-sama in Japanese, are making a comeback at Toyota, the company that long set the pace for manufacturing prowess in the auto industry and beyond. Toyota’s next step forward is counter-intuitive in an age of automation: Humans are taking the place of machines in plants across Japan so workers can develop new skills and figure out ways to improve production lines and the car-building process.
The trend in manufacturing is to turn workers into robot tenders who feed parts into automated machines and watch for breakdowns. The shift of core manufacturing tasks from people to robots may boost productivity in the short run. But the cost is a decay in human know-how and a loss of the unexpected insights that come with that know-how. Robots, for all their speed and precision, lack perspective and understanding. They can monitor and optimize measurable aspects of production processes, but they can’t view those processes from different angles, and they have no feel for the goods being produced. So-called “smart factories” are actually pretty stupid.
Recognizing the dangers in allowing craftsmanship to decay, Toyota is giving pink slips to some of its robots, returning their jobs to people in order to promote the development of deep know-how:
Learning how to make car parts from scratch gives younger workers insights they otherwise wouldn’t get from picking parts from bins and conveyor belts, or pressing buttons on machines. At about 100 manual-intensive workspaces introduced over the last three years across Toyota’s factories in Japan, these lessons can then be applied to reprogram machines to cut down on waste and improve processes, Kawai said. In an area Kawai directly supervises at the forging division of Toyota’s Honsha plant, workers twist, turn and hammer metal into crankshafts instead of using the typically automated process. Experiences there have led to innovations in reducing levels of scrap and shortening the production line 96 percent from its length three years ago.
Much of the current thinking about the future of automation adopts the viewpoint of the robot. It overstates the importance of the things computers are good at (things that tend to be easily measured) and understates the importance of the things that people are good at (things that often are not easily measured). The flaw in that view manifests itself only over the long run, after masters have begun to lose their mastery and companies have begun to lose the intangible benefits mastery brings. Just because a robot can take over a job doesn’t mean it should.
Photo: Wikipedia.
“Ultimately, it’s a virtuous cycle,” declares economics reporter Annie Lowrey in a Times Magazine piece on the job-displacing effects of automation technologies, “because it frees humans up to work on higher-value tasks.” The challenge today, she writes, a few paragraphs later, “is for humans to allow software, algorithms, robots and the like to propel them into higher-and-higher-value work.” The idea is an old one. Aristotle compared tools to slaves: both provide their masters with time for more refined activities. Thinkers as various as Marx, Keynes, and Oscar Wilde said similar things during the industrial revolution. It remains a common refrain today, as automatons and software take over more of the work people used to get paid to do. “We need to let robots take over,” wrote Kevin Kelly last year. “They will help us discover new jobs for ourselves, new tasks that expand who we are. They will let us focus on becoming more human than we were.”
There’s something deeply comforting about the notion that labor-saving technology inevitably pushes workers to higher pursuits. It salves our anxieties about job losses and wage declines — everything will work out fine, “ultimately” — while playing to our unbounded sense of self-importance. The ladder of human occupation goes forever upward; no matter how high our machines climb, there will always be another rung for workers to clamber to. But like many of the comforting things we tell ourselves, it’s no more than a half-truth. And when trotted out as a pat response to contemporary unemployment and underemployment problems, it becomes a dangerous fallacy. By promoting a reassuring fantasy about the future, it relieves us from grappling with the possibility that new, structural problems are opening up in the economy.
The problem with the endless-ladder myth begins with the fuzziness of its claims. What exactly is a “higher-value task”? Are we talking about value for the employer, or value for the employee? Are we measuring value in terms of productivity and profit, or in terms of worker skill and satisfaction? Not only are those two things different; they’re often in conflict. One way that a machine can improve labor productivity is by reducing the number of workers required to produce something. Another way is by reducing the skill requirements of the worker’s job and hence reducing the worker’s pay. As analyses of the employment impacts of industrial machinery show, the use of technology to automate a job tends at first to enhance the skills of a worker, making the job more challenging and interesting, but as the machine becomes more sophisticated, as more job skills are built into its workings, a deskilling trend takes hold. The highly skilled craftsman turns into a moderately skilled or unskilled machine operator. Even Adam Smith understood that machinery, in enhancing labor productivity, would often end up narrowing jobs, transforming skilled work into routine work. At worst, he wrote, the factory worker would become “as stupid and ignorant as it is possible for a human creature to become.”
That’s not the whole picture, of course. In evaluating the long-term effects of automation, we have to look beyond particular job categories. Even as automation reduces the skill requirements of an established occupation, it may contribute to the creation of large new categories of interesting and well-paid work. That’s what happened, as the endless-ladder mythologists will eagerly tell you, during the latter stages of the industrial revolution. The efficiencies of assembly lines and other mechanized forms of production pushed down the prices of all sorts of goods, which drove up demand for those goods, which led manufacturers to hire not only lots of blue-collar workers to operate and repair the machines but also lots of white-collar workers to manage the factories, design new products, market and sell the products, keep the books, and so forth. The resulting expansion of a consumption-minded, experience-seeking middle class ratcheted up demand for all sorts of other workers, from retail clerks to doctors and nurses to teachers to architects to pilots to journalists to government bureaucrats to etc. A virtuous cycle it most definitely was. What it wasn’t was the manifestation of some universal virtuous cycle, some inevitable dynamic in the economy. It was a virtuous cycle very much contingent on its time, and one of the most important of the contingencies was the limited capacity of industrial machinery to take over human work. Even a highly mechanized factory needed lots of people to tend the machines, and most professional and other white-collar jobs lay well beyond the reach of technology.
Times are different now. Machines are different, too. Robots and software programs are still a long way from taking over all human work, but they can take over a lot more of it than factory machines could. It seems pretty clear now that that’s one of the main reasons we’re seeing persistently depressed demand for workers in many sectors of the economy. What’s perhaps less well acknowledged is the spread of the deskilling phenomenon into so-called knowledge work. As computers become more capable of sensing the environment, performing analyses, and making judgments, they can be programmed to take over more white-collar skills. Professionals and office workers start to look more and more like computer operators, tenders of machines.
There will always be opportunities for individuals to design cool new products, make new scientific discoveries, create new works of art, and think new thoughts. But that says little about the prospects for the labor market in general. There’s no guarantee that the deployment of computers is going to open up vast new swathes of interesting, well-paid jobs the way the deployment of factory machines did. Recent experience suggests that computers may have very different consequences. What they seem to be particularly good at is concentrating wealth rather than spreading it, narrowing the work that people do rather than broadening it.
The language that the purveyors of the endless-ladder myth use is revealing. They attribute to technology a beneficent volition. It “frees us” for higher-value tasks and “propels us” into more fulfilling work and “helps us” to expand ourselves. We just need to “allow” the technology to aid us. Much is obscured by such verbs. Technology doesn’t free us or propel us or help us. Technology doesn’t give a rat’s ass about us. It couldn’t care less whether we have a great job, a crappy job, or no job at all. It’s people who have volition. And the people who design and deploy technologies of production are rarely motivated by a desire to create jobs or make jobs more interesting or expand human potential. They’re motivated, as Adam Smith also pointed out, by a desire to make money. Jobs have always been a byproduct of the market’s invisible hand, not its aim.
The biggest beneficiaries of the endless-ladder myth are those who have gained enormous wealth through the profit-concentrating effects of commercial computers. The myth helps them feel good about themselves. They, after all, are the ones who are setting in motion the virtuous cycle that, in the fullness of time, will bring us all to the nirvana of “higher-and-higher-value work.” It suits their business interests, too, by conflating those interests with society’s interests. Software and algorithms and robots will solve our problems, if we allow them to.
I’m not saying that it’s impossible that we’ll soon be blessed with all sorts of great new jobs. The world’s complicated; the economy’s complicated; no one knows what the future’s going to bring. I’m saying that we can’t take it as a given that that’s going to happen, and we certainly shouldn’t assume that machines have the best interests of workers at heart. Ultimately, it’s a virtuous cycle — except when it’s a vicious one.
Image of ladder-climbing robot: DARPA.
One of the pleasures of writing The Glass Cage was discovering the works of the American pragmatic philosopher John Dewey, particularly the 1934 book Art as Experience. In “Self-Reliance,” Emerson wrote, “In every work of genius we recognize our own rejected thoughts: they come back to us with a certain alienated majesty.” I had that feeling often while reading Dewey. There was this passage, for instance:
An environment that was always and everywhere congenial to the straightaway execution of our impulsions would set a term to growth as surely as one always hostile would irritate and destroy. Impulsion forever boosted on its forward way would run its course thoughtless, and dead to emotion. For it would not have to give an account of itself in terms of the things it encounters, and hence they would not become significant objects. The only way it can become aware of its nature and its goal is by obstacles surmounted and means employed; means which are only means from the very beginning are too much one with an impulsion, on a way smoothed and oiled in advance, to permit of consciousness of them. Nor without resistance from surroundings would the self become aware of itself; it would have neither feeling nor interest, neither fear nor hope, neither disappointment nor elation. Mere opposition that completely thwarts, creates irritation and rage. But resistance that calls out thought generates curiosity and solicitous care, and, when it is overcome and utilized, eventuates in elation.
Among other things, Dewey here provides us with a powerful way of examining and interrogating technologies. A tool that simply smooths and oils our way, that speeds us to the execution of an impulsion, has a deadening effect. It removes us from the world and hence from the struggle with the world and its objects that gives definition to the self. The best tools are the ones that expand and extend our contact with the world, that give us more not fewer frictional surfaces.
Dewey’s teaching runs directly counter to our assumption that we should seek out the technologies that offer us the greatest convenience and ease. Imagine, for instance, if software developers, and users, embraced Dewey’s philosophy. The entire software industry would evaporate in an instant, and along with it many fortunes, and a new industry would emerge in an entirely different form.
Tim Wu sketches an intriguing scenario:
A well-educated time traveller from 1914 enters a room divided in half by a curtain. A scientist tells him that his task is to ascertain the intelligence of whoever is on the other side of the curtain by asking whatever questions he pleases.
The traveller’s queries are answered by a voice with an accent that he does not recognize (twenty-first-century American English). The woman on the other side of the curtain has an extraordinary memory. She can, without much delay, recite any passage from the Bible or Shakespeare. Her arithmetic skills are astonishing—difficult problems are solved in seconds. She is also able to speak many foreign languages, though her pronunciation is odd. Most impressive, perhaps, is her ability to describe almost any part of the Earth in great detail, as though she is viewing it from the sky. She is also proficient at connecting seemingly random concepts, and when the traveller asks her a question like “How can God be both good and omnipotent?” she can provide complex theoretical answers.
Based on this modified Turing test, our time traveller would conclude that, in the past century, the human race achieved a new level of superintelligence.
What the time traveller doesn’t see, of course, is that the woman behind the curtain is equipped with a smartphone. Her extraordinary memory is a parlor trick, a ruse.
Mechanical Turk, the chess-playing automaton, amazed eighteenth century audiences with his prowess at the game of kings — until it was revealed that a small-statured human chess master, hidden inside the automaton, was actually making the moves. And so now the roles are reversed: the superintelligent human hides a small-statured, question-answering automaton! Knowledge seems such a drab thing beside the fireworks of its simulation. Baudrillard: “Everywhere we see a paradoxical logic: the idea is destroyed by its own realization, by its own excess.”
Well played, Mr. Turk.
My next book, as previously announced in these pages, is called The Glass Cage. It’s still in the works, but here’s a preliminary cast of characters:
Wiley Post
William Carlos Williams
Norbert Wiener
John Marston
Peter Thiel
Adam Smith
Harry Braverman
Oscar Wilde
Maurice Merleau-Ponty
Kate Crawford
Robert M. Yerkes
Ned Ludlam
John F. Kennedy
Marc Andreesen
Hannah Arendt
Charlie Watts
Katherine Hayles
David Brooks
May-Britt Moser
William Wordsworth
Frank Gehry
George W. Bush
Paul Proteus
Andy Clark
Aristotle
Vinod Khosla
Pierre-Cédric Bonin
Bifo Berardi
Richard Poirier
Benedict de Spinoza
Alfred Korzybski
Robert Frost
Amit Singhal
Serena Williams
Evgeny Morozov
Donna Haraway
Sam Peckinpah
Now that’s a shindig.
Image from Rockstar Games.
