The Glass Cage: Automation and Us (12 page)

Google acknowledges that it has even seen a dumbing-down effect among the general public as it has made its search engine more responsive and solicitous, better able to predict what people are looking for. Google does more than correct our typos; it suggests search terms as we type, untangles semantic ambiguities in our requests, and anticipates our needs based on where we are and how we’ve behaved in the past. We might assume that as Google gets better at helping us refine our searching, we would learn from its example. We would become more sophisticated in formulating keywords and otherwise honing our online explorations. But according to the company’s top search engineer, Amit Singhal, the opposite is the case. In 2013, a reporter from the
Observer
newspaper in London interviewed Singhal about the many improvements that have been made to Google’s search engine over the years. “Presumably,” the journalist remarked, “we have got more precise in our search terms the more we have used Google.” Singhal sighed and, “somewhat wearily,” corrected the reporter: “ ‘Actually, it works the other way. The more accurate the machine gets, the lazier the questions become.’ ”
²³

More than our ability to compose sophisticated queries may be compromised by the ease of search engines. A series of experiments reported in
Science
in 2011 indicates that the ready availability of information online weakens our memory for facts. In one of the experiments, test subjects read a few-dozen simple, true statements—“an ostrich’s eye is bigger than its brain,” for instance—and then typed them into a computer. Half the subjects were told the computer would save what they typed; the other half were told that the statements would be erased. Afterward, the participants were asked to write down all the statements they could recall. People who believed the information had been stored in the computer remembered significantly fewer of the facts than did those who assumed the statements had not been saved. Just knowing that information will be available in a database appears to reduce the likelihood that our brains will make the effort required to form memories. “Since search engines are continually available to us, we may often be in a state of not feeling we need to encode the information internally,” the researchers concluded. “When we need it, we will look it up.”
²⁴

For millennia, people have supplemented their biological memory with storage technologies, from scrolls and books to microfiche and magnetic tape. Tools for recording and distributing information underpin civilization. But external storage and biological memory are not the same thing. Knowledge involves more than looking stuff up; it requires the encoding of facts and experiences in personal memory. To truly know something, you have to weave it into your neural circuitry, and then you have to repeatedly retrieve it from memory and put it to fresh use. With search engines and other online resources, we’ve automated information storage and retrieval to a degree far beyond anything seen before. The brain’s seemingly innate tendency to offload, or externalize, the work of remembering makes us more efficient thinkers in some ways. We can quickly call up facts that have slipped our mind. But that same tendency can become pathological when the automation of mental labor makes it too easy to avoid the work of remembering and understanding.

Google and other software companies are, of course, in the business of making our lives easier. That’s what we ask them to do, and it’s why we’re devoted to them. But as their programs become adept at doing our thinking for us, we naturally come to rely more on the software and less on our own smarts. We’re less likely to push our minds to do the work of generation. When that happens, we end up learning less and knowing less. We also become less capable. As the University of Texas computer scientist Mihai Nadin has observed, in regard to modern software, “The more the interface replaces human effort, the lower the adaptivity of the user to new situations.”
²⁵
In place of the generation effect, computer automation gives us the reverse: a degeneration effect.

B
EAR WITH
me while I draw your attention back to that ill-fated, slicker-yellow Subaru with the manual transmission. As you’ll recall, I went from hapless gear-grinder to reasonably accomplished stick-handler with just a few weeks’ practice. The arm and leg movements my dad had taught me, cursorily, now seemed instinctive. I was hardly an expert, but shifting was no longer a struggle. I could do it without thinking. It had become, well, automatic.

My experience provides a model for the way humans gain complicated skills. We often start off with some basic instruction, received directly from a teacher or mentor or indirectly from a book or manual or YouTube video, which transfers to our conscious mind explicit knowledge about how a task is performed: do this, then this, then this. That’s what my father did when he showed me the location of the gears and explained when to step on the clutch. As I quickly discovered, explicit knowledge goes only so far, particularly when the task has a psychomotor component as well as a cognitive one. To achieve mastery, you need to develop tacit knowledge, and that comes only through real experience—by rehearsing a skill, over and over again. The more you practice, the less you have to think about what you’re doing. Responsibility for the work shifts from your conscious mind, which tends to be slow and halting, to your unconscious mind, which is quick and fluid. As that happens, you free your conscious mind to focus on the more subtle aspects of the skill, and when those, too, become automatic, you proceed up to the next level. Keep going, keep pushing yourself, and ultimately, assuming you have some native aptitude for the task, you’re rewarded with expertise.

This skill-building process, through which talent comes to be exercised without conscious thought, goes by the ungainly name
automatization
, or the even more ungainly name
proceduralization
. Automatization involves deep and widespread adaptations in the brain. Certain brain cells, or neurons, become fine-tuned for the task at hand, and they work in concert through the electrochemical connections provided by synapses. The New York University cognitive psychologist Gary Marcus offers a more detailed explanation: “At the neural level, proceduralization consists of a wide array of carefully coordinated processes, including changes to both gray matter (neural cell bodies) and white matter (axons and dendrites that connect between neurons). Existing neural connections (synapses) must be made more efficient, new dendritic spines may be formed, and proteins must be synthesized.”
²⁶
Through the neural modifications of automatization, the brain develops
automaticity
, a capacity for rapid, unconscious perception, interpretation, and action that allows mind and body to recognize patterns and respond to changing circumstances instantaneously.

All of us experienced automatization and achieved automaticity when we learned to read. Watch a young child in the early stages of reading instruction, and you’ll witness a taxing mental struggle. The child has to identify each letter by studying its shape. She has to sound out how a set of letters combine to form a syllable and how a series of syllables combine to form a word. If she’s not already familiar with the word, she has to figure out or be told its meaning. And then, word by word, she has to interpret the meaning of a sentence, often resolving the ambiguities inherent to language. It’s a slow, painstaking process, and it requires the full attention of the conscious mind. Eventually, though, letters and then words get encoded in the neurons of the visual cortex—the part of the brain that processes sight—and the young reader begins to recognize them without conscious thought. Through a symphony of brain changes, reading becomes effortless. The greater the automaticity the child achieves, the more fluent and accomplished a reader she becomes.
²⁷

Whether it’s Wiley Post in a cockpit, Serena Williams on a tennis court, or Magnus Carlsen at a chessboard, the otherworldly talent of the virtuoso springs from automaticity. What looks like instinct is hard-won skill. Those changes in the brain don’t happen through passive observation. They’re generated through repeated confrontations with the unexpected. They require what the philosopher of mind Hubert Dreyfus terms “experience in a variety of situations, all seen from the same perspective but requiring different tactical decisions.”
²⁸
Without lots of practice, lots of repetition and rehearsal of a skill in different circumstances, you and your brain will never get really good at anything, at least not anything complicated. And without continuing practice, any talent you do achieve will get rusty.

It’s popular now to suggest that practice is all you need. Work at a skill for ten thousand hours or so, and you’ll be blessed with expertise—you’ll become the next great pastry chef or power forward. That, unhappily, is an exaggeration. Genetic traits, both physical and intellectual, do play an important role in the development of talent, particularly at the highest levels of achievement. Nature matters. Even our desire and aptitude for practice has, as Marcus points out, a genetic component: “How we respond to experience, and even what type of experience we seek, are themselves in part functions of the genes we are born with.”
²⁹
But if genes establish, at least roughly, the upper bounds of individual talent, it’s only through practice that a person will ever reach those limits and fulfill his or her potential. While innate abilities make a big difference, write psychology professors David Hambrick and Elizabeth Meinz, “research has left no doubt that one of the largest sources of individual differences in performance on complex tasks is simply what and how much people know: declarative, procedural, and strategic knowledge acquired through years of training and practice in a domain.”
³⁰

Automaticity, as its name makes clear, can be thought of as a kind of internalized automation. It’s the body’s way of making difficult but repetitive work routine. Physical movements and procedures get programmed into muscle memory; interpretations and judgments are made through the instant recognition of environmental patterns apprehended by the senses. The conscious mind, scientists discovered long ago, is surprisingly cramped, its capacity for taking in and processing information limited. Without automaticity, our consciousness would be perpetually overloaded. Even very simple acts, such as reading a sentence in a book or cutting a piece of steak with a knife and fork, would strain our cognitive capabilities. Automaticity gives us more headroom. It increases, to put a different spin on Alfred North Whitehead’s observation, “the number of important operations which we can perform without thinking about them.”

Tools and other technologies, at their best, do something similar, as Whitehead appreciated. The brain’s capacity for automaticity has limits of its own. Our unconscious mind can perform a lot of functions quickly and efficiently, but it can’t do everything. You might be able to memorize the times table up to twelve or even twenty, but you would probably have trouble memorizing it much beyond that. Even if your brain didn’t run out of memory, it would probably run out of patience. With a simple pocket calculator, though, you can automate even very complicated mathematical procedures, ones that would tax your unaided brain, and free up your conscious mind to consider what all that math adds up to. But that only works if you’ve already mastered basic arithmetic through study and practice. If you use the calculator to bypass learning, to carry out procedures that you haven’t learned and don’t understand, the tool will not open up new horizons. It won’t help you gain new mathematical knowledge and skills. It will simply be a black box, a mysterious number-producing mechanism. It will be a barrier to higher thought rather than a spur to it.

That’s what computer automation often does today, and it’s why Whitehead’s observation has become misleading as a guide to technology’s consequences. Rather than extending the brain’s innate capacity for automaticity, automation too often becomes an impediment to automatization. In relieving us of repetitive mental exercise, it also relieves us of deep learning. Both complacency and bias are symptoms of a mind that is not being challenged, that is not fully engaged in the kind of real-world practice that generates knowledge, enriches memory, and builds skill. The problem is compounded by the way computer systems distance us from direct and immediate feedback about our actions. As the psychologist K. Anders Ericsson, an expert on talent development, points out, regular feedback is essential to skill building. It’s what lets us learn from our mistakes and our successes. “In the absence of adequate feedback,” Ericsson explains, “efficient learning is impossible and improvement only minimal even for highly motivated subjects.”
³¹

Automaticity, generation, flow: these mental phenomena are diverse, they’re complicated, and their biological underpinnings are understood only fuzzily. But they are all related, and they tell us something important about ourselves. The kinds of effort that give rise to talent—characterized by challenging tasks, clear goals, and direct feedback—are very similar to those that provide us with a sense of flow. They’re immersive experiences. They also describe the kinds of work that force us to actively generate knowledge rather than passively take in information. Honing our skills, enlarging our understanding, and achieving personal satisfaction and fulfillment are all of a piece. And they all require tight connections, physical and mental, between the individual and the world. They all require, to quote the American philosopher Robert Talisse, “getting your hands dirty with the world and letting the world kick back in a certain way.”
³²
Automaticity is the inscription the world leaves on the active mind and the active self. Know-how is the evidence of the richness of that inscription.