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Based on my own work with stochastic resonance and ADHD, and from earlier studies on noise and creativity, we know that some types of people require more noise in order to benefit from externally-driven neural stochastic resonance. In particular, individuals who score high on measures of originality, creativity, or divergent-thinking seem to perform better on tasks when exposed to higher noise levels.
This is likely related to dopamine function in key brain areas like the prefrontal cortex. Furthermore, it could be that extra noise is necessary in some individuals in order to help functional coherence in the default mode network. Amazingly, none of the psychological work on noise and creativity over the past thirty years has incorporated stochastic resonance. It is remarkable that almost all of these studies unintentionally find psychological or behavioral evidence of stochastic resonance. In other words, if we go back to these studies and model the results using the math of stochastic resonance, the consistent pattern is that a moderate amount of noise improves performance on many tasks. Idleness, then, could turn out to be a way to increase the brain's internal noise level, thus enabling what's called coherence resonance in the default mode network.
Noise that originates inside the system induces order and improves the brain's function, through the same mechanism of stochastic resonance. It could be that working all the time and being busy reduces internal noise to a sub-optimal level. While we still do not have a way to directly measure stochastic resonance inside a living brain, the techniques that Ward is using could be applied to the idle brain and the default mode network.
Let's return to Rilke pacing on the castle battlement by the sea that windy day in northern Italy. The years of patient idleness the poet went through allowed activity in his default mode network to percolate up to his awareness from time to time and so his consciousness was prepared to receive the messages. On that particular morning at Duino, the powerful wind blowing from the sea provided just the right addition of external noise his brain needed to give Rilke the inspiration for one of his life's great works. A highly original and creative person, he would likely have needed more external noise in order for his brain to benefit creatively from stochastic resonance.
Rilke's unconscious had been preparing this poem for him. The poem itself could be considered a weak signal, which as we saw earlier is undetectable without noise. As Rilke walked through the blustery wind that morning, it is possible that the same brain mechanism of noise-enhanced neural synchronization that Lawrence Ward has discovered allowed critical parts of Rilke's brain to synchronize.
This could have formed a functional network that transiently made this great work of poetry appear to Rilke. In the presence of the wind, the weak signal of the poem would then make its way through the network into Rilke's awareness. Furthermore, the strength of the signal would have been boosted over the critical threshold for it to enter into his consciousness. To Rilke, this would have seemed like a voice calling out to him in the wind saying:
And if I cried out, who would hear me up there among the angelic orders?
Lawrence Ward and other scientists are revealing the precise mechanisms by which noise actually helps our brains to achieve some of their most amazing feats of creativity. So rather than fighting noise, or seeing noise as something that distracts us from the truth, we might soon discover that our brains actually require noise to find truth. By embracing idleness, we embrace the noise of our own unconscious. The wind blows inside of us, enabling us to hear the truth in the wind that takes us by surprise, the wind we seek to hear ourselves.
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“Now I have to tell you something, and I mean this in the best and most inoffensive way possible: I don't believe in process. In fact, when I interview a potential employee and he or she says that âit's all about the process,' I see that as a bad sign ⦠The problem is that at a lot of big companies, process becomes a substitute for thinking. You're encouraged to behave like a little gear in a complex machine. Frankly, it allows you to keep people who aren't that smart, who aren't that creative.”
âElon Musk, founder of Space-X and Tesla Motors
If you have a job at any sizable company there is good chance you've been forced to endure Six Sigma training, or at least some watered-down derivative. Your instructor may have reminded you, as mine did, of a newly converted religious fanatic proselytizing his faith. Imagine a cross between a Scientologist and a Jehovah's Witness, tastefully attired in business casual.
Six Sigma devotees refer to their judo belts which denote mastery over the seemingly-infinite levels of the Six Sigma world. You start out as a “green belt” and proceed to a “black belt” if you are a true believer and you work really, really hard. There is also a “Master” level that seems almost unattainable to normal humans.
According to an official account, Six Sigma is an organized and systematic method for strategic process improvement, plus new product and service development, that relies on statistical methods and the scientific method to make dramatic reductions in customer-defined defect rates. Don't worry about trying to understand what that even means: it turns out that not even Ultimate Lean-Master Six Sigma Black Belts understand what it means. Six Sigma is neither statistical nor scientific. You can quite easily get through Six Sigma training by pretending to know what it means, so let's just pretend.
A paper on Six Sigma theory by R. G. Schroeder in the
Journal of Operations Management
from 2008 identifies several definitions: Six Sigma is “a high-performance, data-driven approach to analyzing the root causes of business problems and solving them.” Also it's a “business process that allows companies to drastically improve their bottom line by designing and monitoring every business activity in ways that minimize waste and resources while increasing customer satisfaction”; also it's “a disciplined and statistically based approach for improving product and process quality”; also it's “a management strategy that requires culture change in the organization.”
After going through a few weeks of Six Sigma training, I basically learned how to write my name on a piece of cardboard, how to draw on flipcharts, and how to pass pieces of paper to other members of my group. All while the instructor gave us questionable information about statistics. I learned too that questioning him about the statistics led to long digressions about his dog in Arizona.
Where did Six Sigma come from? Is it a secret government program gone awry? Legend has it that Six Sigma was developed at Motorola in the early 1980s to study and control defects in semiconductor chip manufacturingâand that's probably where it should have stayed. Unfortunately, like some contagious virus developed at a CDC lab, it escaped the factory. It has now become a horrifying corporate epidemic.
In the 1980s, Motorola wanted to produce perfect semiconductors as fast as possible, while at the same time saving billions of dollars. When you are making semiconductor chips, naturally you want to minimize defects. So once you've worked out the most efficient process to produce your chips, you want to codify the process and make it automatic. Every time a piece of machinery or factory worker does something during the production process, it should happen the exact same way. In other words, there should be no variation in the process. But what does sigma mean? And why is sigma preceded by the number six?
Sigma or “
Ï
” is the Greek letter used in statistics to represent the standard deviation from some mean (the mean is the middle point). Without going into too much detail, the standard deviation represents how much individual measurements differ on average from this mean.
A simple way to illustrate this is with how tall people are. For example, if we measure the height of one thousand male Americans, add up all the heights, and divide by the number of measurements (i.e., one thousand) the average might be around 5'10”. So roughly half of the people are shorter and half are taller than 5'10”. But we don't know if the average has been calculated because some people are ten feet tall and some two feet tall, or if most people measured hover very close to 5'10”.
The standard deviation tells us to what extent most people deviate from this average. Because the population is made up of mostly regular-sized people, height measurements have a small standard deviation of around three inches. Also, because height seems to come from what's called a “normal distribution,” also known as a bell curve, height can be studied using traditional statistics.
It's important to note that there are an infinite range of bell curvesânot just one distribution called “the bell curve.” But by determining both an average and also standard deviation, we can estimate what the heights of the tallest and shortest people are likely to be.
One sigma, or one standard deviation, from the mean with respect to height would cover perhaps sixty-five percent of the people. Since the sigma is three inches, this would refer to people who are either 5'7” on the low end or 6' on the high end. Two sigma from the mean would cover fewer people, perhaps only ten percent, as we move from out from the mean toward the tall and short sides of the spectrum: roughly 6'3” and 5'4.”
The farther out in standard deviations from the mean in a normal distribution, the more unusual you are. If you are “Six Sigma” (or six standard deviations) away from the average height you are extremely rare: 7'6.” Yao Ming territory. There are only a handful of people in the world who are this tall. The goal of Six Sigma is to make mistakes in business processes as rare as people like Yao Ming.
It's easy to see how this type of thinking can be applied to highly automated processes like manufacturing microchips or cars. You want to engineer your production system to produce faulty cars so rarely that they occur only at Six Sigma frequency. Basically, never.
By analyzing each step of the process and figuring out how to measure inputs and outputs, an average of the process can be taken, just like with measuring height. Then a standard deviation of the process can be worked out. If the standard deviation is very large it means there is too much variation in the process and it has to be changed to produce a smaller standard deviation. In other words, there should be as little variation in the process as possible. The underlying assumption is that variation leads to errors.
However, rather than just using it as a way to standardize production, companies began to apply the Six Sigma approach to every single business process, treating human beings as a series of inputs and outputs instead of sentient creatures. The single most important goal of the Six Sigma is to reduce variation in organizational processes by using disease vectors to spread throughout the company. These vectors are improvement specialists, a structured method, and performance metrics.
This is similar to what the underlying disease in epilepsy does to neurons. During a seizure, the variations in the neurons are reduced. Reducing variation in the brain is devastating. Applied to an entire company, the Six Sigma process is analogous to an organizational epileptic seizure.
Naturally, if you are making vaccines, aspirin, car parts, airplane engines, MRI scanners, or any other mass-produced thing that could potentially kill people, you want to prevent defects. In these types of highly automated manufacturing processes, Six Sigma makes sense. In fact, it makes sense to use robots to do most manufacturing. For repetitive automated tasks where very little decision-making is required, robots outperform human beings, no question.
Six Sigma wants to make human beings as efficient as possibleâpredictable, reliable, nearly fault free, and with minimal interference from outside thoughts. Since Jack Welch Six Sigma-ed GE, the approach has spread to many major companies in the industrial sector and beyond. Some of the corporations that are having Six Sigma seizures include Fiat, Honeywell, Dow Chemical, Cameron, Sony, Johnson & Johnson, Bank of America, and Whirlpool.
The human brain actually seeks out and thrives on its own variation. With each new experience we have, our brain is irreversibly changed. These changes become more profound and stable if we rest between new experiences. This allows our brain to consolidate what it has absorbed and integrate it into our own sense of self, therefore making meaning out of experience. The process is different for each experience and different for each person. Neuroscience is discovering that a crucial part of this process is allowing the brain's default mode network time to be active. A resting brain is necessary for this to happen.
Each of our brains has its own rhythm. For example, you can alter it by flying to Europe. After a period of jet lag you will have altered your circadian rhythm to a new time zone. However, once the jet lag has passed, you will have the same daily rhythm that you did in your old time zone. If you are a morning person in New York, you will be a morning person in Paris. This is likely because your brain is generating its own internal pattern, which may be largely inherited.
Our brain responds slightly differently to each situation depending on a great many factors: mood, your fatigue level, and motivation. Our ability to pay attention also has a natural rhythm that waxes and wanes throughout the day. As we've seen, the default mode network's activity likes to oscillate against the task-positive network. When these rhythms of the brain are not allowed to fluctuate naturally, the consequences can be severe for an individual. For example, pilot fatigue is one of the leading causes of airplane crashes.
The natural, nonlinear, fluctuating, and often-unpredictable aspects of human beings are troubling for corporations. CEOs crave certainty and predictability. Throughout the corporate hierarchy, each level must produce high levels of predictability and certainty. Over the last decade or so, the Six Sigma approach has come under intense criticism. Several large companies such as 3M noticed that when they religiously implemented Six Sigma, innovation slowed to a crawl. Michael Tushman, a professor at Harvard Business School, said, “These ⦠methodologies that are anchored on reducing variability are inversely associated with what we call exploratory innovation. Methodologies help incremental innovation.”
Within a decade, the percentage of 3M products that were new or less than five years old slipped from one-third to one-quarter. In other words, before Six Sigma, thirty percent of 3M's products were new, and after Six Sigma, that percentage fell to twenty-five percent. Rather than scrapping Six Sigma, the company stopped using that metric.
Motorola, where the Six Sigma outbreak started, used to enjoy a huge lead in the mobile phone market. Their dominant position in the market has evaporated. The mobile marketplace is one of the fastest moving and most innovative, and it seems like forcing your opponents to adopt Six Sigma tactics is a good way to cripple them.
Capitalist corporations must execute a strange balancing act between two poles on a spectrum that are paradoxical. On the one hand, they must work to the shareholders' immediate benefitâhence Six Sigma. On the other hand, they need ideas for innovative products. Both these contradictory elements are required for the elusive “competitive advantage.”
The only system we know of in the universe that can be innovative is the human brain. But the brain seems to need things like freedom, long periods of idleness, positive emotions, low stress, randomness, noise, and a group of friends with tea in the garden to be creative. The truth is that we can't have it both ways. Until we figure out how to give robots a “creative mode,” humans are going to be the only source of innovation for the foreseeable future. But the vast majority of business processes do not actually require human thought. Just as many time management strategies admonish you to get things out of your brain and into a physical organizer, Six Sigma would like to minimize human variation within the organization.
Epilepsy kills fifty thousand people a year in the United States alone. About fifty million people around the world have epilepsy, and thirty percent of these people have poorly controlled seizures despite taking the maximum medication dosage. There are many different causes of epilepsy, but the common symptom is having some type of seizure activity. Epilepsy can be inherited or it can be acquired from disease or head trauma. All those concussions you had as a teenager can come back to haunt you. The seizure activity can be very brief and mild like a subtle change in cognitive state.
The patient may not even notice he is having a seizure. You might just “check-out” for a few moments and then rejoin the world without realizing what happened. More serious forms of seizure can cause debilitating convulsions, and in the worst cases death.
Abnormal synchronous neural firing in one or several areas of the brain causes the epilepsy seizure. Recall that the way neurons in your brain communicate is through synchronizing their activity, so that information can flow back and forth between neurons, and between brain regions in the brain network. However, the normal neural synchronization that allows you to be conscious and function is very subtle and relies on groups of neurons that synchronize or desynchronize as necessary. Your everyday cognitive functioning depends on the variation in your neural activity.
Sometimes the synchronization is partial within a patch of brain. This complex interplay of neurons firing together or not together forms the basis of how parts of your brain talk to each other. The process is highly variable, nonlinear, context dependent, noisy, and displays many of the characteristics of complexity and self-organization we see in other complex networks.
