This morning I boarded my flight from London to Houston. An hour before I checked my bag, and received my boarding pass. I walked onto the plane, took my seat. I am barely aware of the engines as they hum away at 35,000 feet. I switch on a movie, and settle in for the 9 hour journey.
So it seems that today was just like countless other ordinary days in my lifeâŠor was it? In fact, at each and every step there were millions of calculations going on around me, under my notice, making the morningâs events flow effortlessly one to another. It is a software-driven world to be sure, but software and information technology are just the delivery mechanisms. What actually made all of these sophisticated logistics, machine, and security functions happen?
In a word: rules.
A complex tapestry of rules encoded into the airlineâs reservation system delivered my boarding pass to me. The system recognized me as a frequent flier, and applied a whole different branch of rules to my reservation based on that status. I have no doubt that a dozen security cameras locked onto me as I walked through Heathrow, churning through a book of rules to determine my intentions. Once on-board, the flight attendants followed a well scripted set of rules from seating passengers to security announcements to closing the doors. The flight controllerâs rules took my weight into account and told the engine to provide just the right thrust to keep me and my fellow passengers aloft. Unseen, a sea of computations following prescribed rules that would fill hundreds of libraries worth of written pages surrounded me, enabling every mundane facet of my movements this morning. How extraordinary it would be to have âZ-Rayâ vision sufficient to see all of that code in real time coming together, as it moved me along!
Martin Ford in his book The Rise of the Robots paints a dramatic picture of the futureâone characterized by pervasive automation, including automation of creative and inherently human tasks like writing a novel or passing judgment in a legal case. Many other influential authors and thinkers have supported this view.
When an entire set of rules are encoded in technology, we refer to them as algorithms. Algorithms are not new, and in fact date back to ancient times. Ciphers, simple algorithms to substitute alphabet characters used in primitive cryptography so that armies could pass secret messages to one another were discussed in the 4th century BCE.
Therefore, if the hallmark of the future is automation, and algorithms form the âmoleculesâ of an automated system, one cannot escape the inevitable conclusion that those who participate in the design of algorithms will thrive in the coming economy. The new idea that I put forward in these pages is that algorithms are no longer the sole province of computer scientists and programmers. Ordinary people, most especially ordinary people involved in running a business or an organization of any stripe, can and should participate in the design of algorithms.
Algorithm design in the way that I will describe in this book will be one of the leading business skills of the coming decade, easily surpassing todayâs most popular analytical skill known as data science. I will begin by providing a historical context for algorithms, looking at âfamousâ algorithms across history, some created centuries before the invention of the computer. From there we will move on to understand the precise role algorithms will play in a highly automated commercial future, enabling smart business models and overturning certain industries. I will invite you to try your own hand at algorithm design, describing the means by which everyday people, not programmers (although programmers will enjoy this as well) can build, test, and validate their own algorithms. Since algorithms on paper may be beautiful to behold but donât do anything useful, we will address the important work of implementing algorithms within a technological system. Many knowledge workers in a company coming together to create algorithms to drive efficient operations or enhance new products suggest an almost factory-like nature to algorithm design for institutions. The factory metaphor is no accidentâwe must rethink the way corporations are stitched together to encourage greater capacity for algorithm design, notwithstanding their protection, archival, and monetization. Finally, I will offer some lessons as to where this newfound intelligence will take us, and what it means to stay competitive in an environment of ever-increasing technological sophistication.
I am delighted that youâve chosen to join me on these pages. I will reward you with a number of surprisesâthings you never knew about your own potential to participate in a lightning-fast economy. I promise to leave you with a set of enduring skills that you can apply right away. But most of all I want to pay forward the gift my mentors in life have given meâthe gift of keen insight, a way of thinking that you did not possess before; leading us to a new optimism about our collective future in a world where we will harness intelligence for good, yielding benefits beyond our imagination.
Welcome, friends, to the dawning of a new era in computation.
Letâs begin.
© The Author(s) 2019
George E. DannerThe Executive's How-To Guide to Automationhttps://doi.org/10.1007/978-3-319-99789-6_1 Begin Abstract1. Automation Is Here
George E. Danner1
(1)Business Laboratory LLC, The Woodlands, TX, USA
End AbstractThe first century A.D. was an exhilarating time in Alexandria, Egypt. The happy collision of engineering and mathematics of ancient Greece with the carefully curated knowledge of Egypt gave rise to an amazing number of sophisticated machines, even by todayâs standards. It was at this time that a prominent engineer and mathematician, Heron of Alexandria, created the very first vending machine.
Much of the income derived by the priests of the many temples around Alexandria came from the sale of religious elements to the temple-goers, such as parcels of holy water used to wash the face and hands. Priests were notably dismayed by certain visitors taking more water than they had paid for at the temple entrance. Heron devised a simple but ingenious device that allowed a coin to be inserted into a vessel. The coin fell upon a pan that was at one end of a balanced beam. The weight of the coin raised the opposite side which was attached to a valve that opened to allow the water to flow out of a tube at the bottom of the vessel. When the weight of the coin equalized with the weight of the water, the valve subsequently closed, giving the temple-goer a precise amount of water in accordance with what was paid [1].
Eighteen hundred years later (!) Percival Everett invented the first modern age coin-operated vending machine to dispense postcards, primarily at railway stations across London. Over the next two decades that followed, the products in the machines expanded to include gum, cigarettes, chocolate, and soap. Small, incremental improvements were made over the next seventy years until the advent of the microprocessor and communications networks, thus allowing vending machines to accept a much wider variety of payment forms outside of physical coins, as well as serving in two directions, both vending and receiving, as is the case with library books and DVD rentals.
At the one and only Amazon Go retail store in Seattle (as of this writing), a customer enters, picks up items, and leaves the store. The âcheckoutâ is fully automated using an army of unseen cameras and sensors, all meticulously coordinated under a concept known as sensor fusion . Amazon plans to roll out many more stores after learning from the initial opening [2]. Heron would be quite impressed.
A fascinating contrast of history with the modern age⊠but what does it mean? In all cases, we have a customer that wants something, and is willing to pay for it. We have suppliers willing to provide the items at an agreed price. The stories Iâve told here revolve around the mechanism for making the transaction which is designed for one purpose: to minimize the friction of the transaction. Friction can come in many formsâtheft in the temple, availability and cost of store clerks to sell gum, and long lines at grocery stores. Clever machinery (technology) gradually removed friction, solving the customerâs problem, whether they were conscious of a âproblemâ or not. Transactions now happen faster, cheaper, more accurately, and with greater optionality than before.
This is automation.
As you can see, it is not a new concept. What is new is our limitless ability to infuse automation into business models, not exclusively by an elite group of technologists, but by anyone with a systems mindset .
Two decades of technological advance in four specific vectors has placed us at a unique inflection point in the history of automation. First, sensors for everything from temperature to motion to image recognition are now lower in power consumption, cheaper to buy, and of a resolution and accuracy that allows computers to know in astonishing detail many aspects of the physical world around it. Computing has broken free from the bounds of âcomputersâ to run almost anywhere, and at a speed sufficient to do very sophisticated calculations, such as processing an image to find and identify human faces. Data is now universal, accurate, and ubiquitous, where once we had precious little. Moreover, we have well-proven sharing mechanisms that we can use to voluntarily distribute our specific data intentionally to trusted partners.
But perhaps the most important development giving rise to the automation boom is in the sophistication of the science of automation. In other words, we can harness computing to do the work that humans do, by mimicking the same processes that the brain uses to make decisions. Artificial intelligence is the cornerstone of this new, more comprehensive style of automation. There is no question that AI has enjoyed a renaissance in the 2010 decade, alongside a greater awareness (and less fear) of how the technology can be deployed to practical use.
History has taught us that real inflection points in technological advances come along when a suite of seemingly unrelated threads blend together in creative and ingenious ways [3]. When the printing press paralleled advances in naval architecture and design in Renaissance Europe, books could not only be printed but they could be put on vessels to carry that knowledge from one country to the next, unleashing an unprecedented wave of knowledge and invention. Today sensors, computing, data, and AI are in forms that are low cost and practical. It just so happens that these are the key ingredients in weaving automation into businesses to make them perform better, faster, and cheaper. Over the next decade we will witness an equally potent wave of automation, overturning commonly held beliefs of âoh we will never automate thatâ again and again.
Even today we have intelligent systems autonomously dispensing tax advice, diagnosing medical conditions, and optimizing farm yields where once we had humans holding forth with the aid of data and computers. Automation is upon us, but in hidden, out-of-the-way corners of the economy. The full wave is yet to start, but I see the 2020 decade as the staging ground for it. When it comes, intelligent systems will be the norm, the default expectation, rather than the amusing exception that exists today.
The decades of the 1970s and 1980s were filled with examples of physical automation. The automobile manufacturing industry dove head first into the concept of the âlights outâ factory with robots employed across the assembly line. Semiconductors and consumer goods followed suit. The coming wave will be distinctly differentânot focused on physical work, but rather on âwhite collarâ processes and functions that involve judgment and reasoning on knowingly incomplete data. In doing so we can set aside the complicated science of kinetics and kinematics needed in the physical world of work and focus exclusively on logic and data as a means for computers to make important decisions. Leading thinkers in business science have coalesced around a set of ideas collectively referred to as Industry 4.0 , suggesting that we are in a 4th wave of commercial power and enlightenment since the Industrial Revolution of the late 1700s.
The building block of new automation is the algorithm, a clear and precise ...