Book Club: The Code Economy: The DNA of Business

“DNA builds products with a purpose. So do people.” –Auerswald, The Code Economy

McDonald’s is the world’s largest restaurant chain by revenue[7], serving over 69 million customers daily in over 100 countries[8] across approximately 36,900 outlets as of 2016.[9] … According to a BBC report published in 2012, McDonald’s is the world’s second-largest private employer (behind Walmart with 1.9 million employees), 1.5 million of whom work for franchises. …

There are currently a total of 5,669 company-owned locations and 31,230 franchised locations… Notably, McDonald’s has increased shareholder dividends for 25 consecutive years,[18] making it one of the S&P 500 Dividend Aristocrats.[19][20]

According to Fast Food Nation by Eric Schlosser (2001), nearly one in eight workers in the U.S. have at some time been employed by McDonald’s. … Fast Food Nation also states that McDonald’s is the largest private operator of playgrounds in the U.S., as well as the single largest purchaser of beef, pork, potatoes, and apples.  (Wikipedia)

How did a restaurant whose only decent products are french fries and milkshakes come to dominate the global corporate landscape?

IKEA is not only the world’s largest furniture store, but also among the globe’s top 10 retailers of anything and the 25th most beloved corporation. (Disney ranks number one.) Even I feel a strange, heartwarming emotion at the thought of IKEA, which somehow comes across as a sweet and kind multi-national behemoth.

In The Code Economy, Auerswald suggests that the secret to McDonald’s success isn’t (just) the french fries and milkshake machines:

Kroc opened his first McDonald’s restaurant in 1955 in Des Plaines, California. Within five years he had opened two hundred new franchises across the country. [!!!] He pushed his operators obsessively to adhere to a system that reinforced the company motto: “Quality, service, cleanliness, and value.”

h/t @simongerman600

Quoting Kroc’s1987 autobiography,

“It’s all interrelated–our development of the restaurant, the training, the marketing advice, the product development, the research that has gone into each element of the equipment package. Together with our national advertising and continuing supervisory assistance, it forms an invaluable support system. Individual operators pay 11.5 percent of their gross to the corporation for all of this…”

The process of operating a McDonald’s franchise was engineered to be as cognitively undemanding as possible. …

Kroc created a program that could be broken into subroutines…. Acting like the DNA of the organization, the manual allowed the Speedee Service System to function in a variety of environments without losing essential structure or function.

McDonald’s is big because it figured out how to reproduce.

source: Statista

I’m not sure why IKEA is so big (I don’t think it’s a franchise like McDonald’s,) but based on the information posted on their walls, it’s because of their approach to furniture design. First, think of a problem, eg, People Need Tables. Second, determine a price–IKEA makes some very cheap items and some pricier items, to suit different customers’ needs. Third, use Standard IKEA Wooden Pieces to design a nice-looking table. Fourth, draw the assembly instructions, so that anyone, anywhere, can assemble the furniture themselves–no translation needed.

IKEA furniture is kind of like Legos, in that much of it is made of very similar pieces of wood assembled in different ways. The wooden boards in my table aren’t that different in size and shape from the ones in my dresser nor the ones in my bookshelf, though the items themselves have pretty different dimensions. So on the production side, IKEA lowers costs by producing not actual furniture, but collections of boards. Boards are easy to make–sawmills produce tons of them.

Furniture is heavy, but mostly empty space. By contrast, piles of boards stack very neatly and compactly, saving space both in shipping and when buyers are loading the boxes into their cars. (I am certain that IKEA accounts for common car dimensions in designing and packing their furniture.)

And the assembly instruction allow the buyer to ultimately construct the furniture.

In other words, IKEA has hit upon a successful code that allows them to produce many different designs from a few basic boards and ship them efficiently–keeping costs low and allowing them to thrive.

From Anatomy of an IKEA product:

The company is also looking for ways to maximize warehouse efficiency.

“We have (only) two pallet sizes,” Marston said, referring to the wooden platforms on which goods are placed. “Our warehouses are dimensioned and designed to hold these two pallet sizes. It’s all about efficiencies because that helps keep the price of innovation down.”

In Europe, some IKEA warehouses utilize robots to “pick the goods,” a term of art for grabbing products off very high shelves.

These factories, Marston said, are dark, since no lighting is needed for the robots, and run 24 hours a day, picking and moving goods around.

“You (can) stand on a catwalk,” she said, “and you look out at this huge warehouse with 12 pallets (stacked on top of each other) and this robot’s running back and forth running on electronic eyebeams.”

IKEA’s code and McDonald’s code are very different, but both let the companies produce the core items they sell quickly, cheaply, and efficiently.

In The Code Economy, Chapter 8: Evolution, discusses the rise of Tollhouse Cookies, McDonald’s, the difference between natural and artificial objects, and the development of evolutionary theory from Darwin through Watson and Crick and through to Kauffman and Levine’s 1987 paper, “Toward a General Theory of Adaptive Walks on Rugged Landscapes.” (With a brief stop at Erwin Shrodinger along the way.)

The difficulty with evolution is that systems are complicated; successful mutations or even just combinations of existing genes must work synergistically with all of the other genes and systems already operating in the body. A mutation that increases IQ by tweaking neurons in a particular way might have the side effect of causing neurons outside the brain to malfunction horribly; a mutation that protects against sickle-cell anemia when you have one copy of it might just kill you itself if you have two copies.

Auerswald quotes Kauffman and Levin:

“Natural selection does not work as an engineer works… It works like a tinkereer–a tinkerer who does not know exactly what he is going to produce but uses… everything at his disposal to produce some kind of workable object.” This process is progressive, moving form simpler to more complex forms: “Evolution doe not produce novelties from scratch. It works on what already exists, either transforming a system to give it new functions or combining several systems to produce a more elaborate one [as] during the passage from unicellular to multicellular forms.”

Further:

The Kauffman and Levin model was as simple as it was powerful. Imagine a genetic code of length N, where each gene might occupy one of two possible “states”–for example, “o” and “i” in a binary computer. The difficulty of the evolutionary problem was tunable with the parameter K, which represented the average number of interactions among genes. The NK model, as it came to be called, was able to reproduce a number of measurable features of evolution in biological systems. Evolution could be represented as a genetic walk on a fitness landscape, in which increasing complexity was now a central parameter.

You may remember my previous post on Local Optima, Diversity, and Patchwork:

Local optima–or optimums, if you prefer–are an illusion created by distance. A man standing on the hilltop at (approximately) X=2 may see land sloping downward all around himself and think that he is at the highest point on the graph. But hand him a telescope, and he discovers that the fellow standing on the hilltop at X=4 is even higher than he is. And hand the fellow at X=4 a telescope, and he’ll discover that X=6 is even higher.

A global optimum is the best possible way of doing something; a local optimum can look like a global optimum because all of the other, similar ways of doing the same thing are worse.

Some notable examples of cultures that were stuck at local optima but were able, with exposure, to jump suddenly to a higher optima: The “opening of Japan” in the late 1800s resulted in breakneck industrialization and rising standards of living; the Cherokee invented their own alphabet (technically a syllabary) after glimpsing the Roman one, and achieved mass literacy within decades; European mathematics and engineering really took off after the introduction of Hindu-Arabic numerals and the base-ten system.

If we consider each culture its own “landscape” in which people (and corporations) are finding locally optimal solutions to problems, then it becomes immediately obvious that we need both a large number of distinct cultures working out their own solutions to problems and occasional communication and feedback between those cultures so results can transfer. If there is only one, global, culture, then we only get one set of solutions–and they will probably be sub-optimal. If we have many cultures but they don’t interact, we’ll get tons of solutions, and many of them will be sub-optimal. But many cultures developing their own solutions and periodically interacting can develop many solutions and discard sub-optimal ones for better ones.

On a related note, Gore Burnelli writes: How Nassim Taleb changed my mind about religion:

Life constantly makes us take decisions under conditions of uncertainty. We can’t simply compute every possible outcome, and decide with perfect accuracy what the path forward is. We have to use heuristics. Religion is seen as a record of heuristics that have worked in the past. …

But while every generation faces new circumstances, there are also some common problems that every living being is faced with: survival and reproduction, and these are the most important problems because everything else depends on them. Mess with these, and everything else becomes irrelevant.

This makes religion an evolutionary record of solutions which persisted long enough, by helping those who held them to persist.

This is not saying “All religions are perfect and good and we should follow them,” but it is suggesting, “Traditional religions (and cultures) have figured out ways to solve common problems and we should listen to their ideas.”

From Ray Kurzweil

Back in The Code Economy, Auerswald asks:

Might the same model, derived from evolutionary biology, explain the evolution of technology?

… technology may also be nothing else but the capacity for invariant reproduction. However, in order for more complex forms of technology to be viable over time, technology also must possess a capacity for learning and adaptation.

Evolutionary theory as applied to the advance of code is the focus of the next chapter. Kauffman and Levin’s NK model ends up providing a framework for studying the creation and evolution of code. Learning curves act as the link between biology and economics.

Will the machines become sentient? Or McDonald’s? And which should we worry about?

Which came first, the City or the Code? (book club Code Economy Ch 2)

The Code of Hammurabi

Writing, which is itself a form of code, enable humans to communicate code. Cities grow as code evolves. –Auerswald

Welcome to The Code Economy: A Forty-Thousand Year History, by Philip E. Auerswald. Chapter Two: Code looks at two epochal developments in human history: writing and cities.

One of the earliest pieces of writing we have uncovered is the Sumerian Hymn to Ninkasi, Goddess of Beer, which contains, yes, a recipe for making beer (translation by Miguel Civil):

Your father is Enki, Lord Nidimmud,
Your mother is Ninti, the queen of the sacred lake.
Ninkasi, your father is Enki, Lord Nidimmud,
Your mother is Ninti, the queen of the sacred lake.

You are the one who handles the dough [and] with a big shovel,
Mixing in a pit, the bappir with sweet aromatics,
Ninkasi, you are the one who handles the dough [and] with a big shovel,
Mixing in a pit, the bappir with [date] – honey,

You are the one who bakes the bappir in the big oven,
Puts in order the piles of hulled grains,
Ninkasi, you are the one who bakes the bappir in the big oven,
Puts in order the piles of hulled grains,

You are the one who waters the malt set on the ground,
The noble dogs keep away even the potentates,
Ninkasi, you are the one who waters the malt set on the ground,
The noble dogs keep away even the potentates,

You are the one who soaks the malt in a jar,
The waves rise, the waves fall.
Ninkasi, you are the one who soaks the malt in a jar,
The waves rise, the waves fall.

You are the one who spreads the cooked mash on large reed mats,
Coolness overcomes,
Ninkasi, you are the one who spreads the cooked mash on large reed mats,
Coolness overcomes,

You are the one who holds with both hands the great sweet wort,
Brewing [it] with honey [and] wine
(You the sweet wort to the vessel)
Ninkasi, (…)(You the sweet wort to the vessel)

The filtering vat, which makes a pleasant sound,
You place appropriately on a large collector vat.
Ninkasi, the filtering vat, which makes a pleasant sound,
You place appropriately on a large collector vat.

When you pour out the filtered beer of the collector vat,
It is [like] the onrush of Tigris and Euphrates.
Ninkasi, you are the one who pours out the filtered beer of the collector vat,
It is [like] the onrush of Tigris and Euphrates.

Sumerian tablet recording the allocation of beer

You guys requested beer or wine with your books, so here you go.

The hymn contains two layers of code–first, there is the code which allows each symbol or character to stand for a particular sound, which let the author write down the recipe and you, thousands of years later, decode and read the recipe; and second, there is the recipe itself, a code for producing beer.

The recipe’s code likely far predates the hymn itself, as humans had begun brewing beer at least a couple thousand years earlier.

Writing and cities go hand in hand; it is difficult to imagine managing the day-to-day need to import food (and water) for thousands of people without some ability to encode information. As cities grow larger, complexity grows: one man in the woods may relieve himself behind a tree; thousands of people packed into a square mile cannot.

Each solved problem, once routinized, becomes its own layer of code, building up as the city itself expands; a city of thousands or millions of people cannot solve each person’s problems anew each day.

Gobekli Tepe, Turkey

But which came first, the city or the alphabet? Did the growth of cities spur innovations that improved agricultural output, or did agricultural innovations spur the growth of cities?

For example, settlement and construction appear to have gotten underway at Jericho (one of the world’s oldest inhabited cities) around 9 or 10,000 BC and at the mysterious Gobekli Tepe site began around 7-9,000 BC, before agriculture emerged in the region.

Writing developed a fair bit later, developing from clay shapes to shapes impressed in clay between 8,000 and 4,000 BC.

Amphitheater, Norte Chico, Peru

Others of the world’s earliest civilizations had either no or very little writing. The Norte Chico civilization of Peru, for example; by the time the Spaniards arrived, the Inca had an accounting system based on the quipu, a kind of string abacus, but appear to have not yet developed a true writing system, despite their palaces, cities, roads, emperor, and tax collectors. (Here is my previous post on Norte Chico.)

The Great Bath of Mohenjo-daro

The extensive Indus Valley civilization had some form of symbolic encoding, but few of their inscriptions are longer than 4 or 5 characters–the longest inscription found so far is 26 symbols, spread over three different sides of an object. Not exactly an epic–but the Indus Valley Civilization was nevertheless quite large and impressive, supporting perhaps 5 million people. (Previous post on the Indus Valley.)

Auerswald documents some of the ways cities appear to drive innovation–and to “live”:

The Santa Fe team found that cities are like biological organisms when it comes to “metabolic” urban processes that are analogous to nutrient supply and waste removal–transportation, for example, ha a branching structure much like veins or bronchi–but that cities differ fundamentally from biological organisms when it comes to indicators reflecting the creation and transmission of code. measuring the size of cities based on population and on the urban “metabolism” using metrics such as wages, GDP, electric power and gasoline consumption, and total  road surface, the team found a systematic relationship between city size and indicators of the supply of “nutrients” and waste removal… However, while metabolic indicators do not keep pace with the size of cities as they grow, indicators relating to the creation and transmission of code increase at a greater rate than city size. … In short, the creation of ideas accelerates with city growth, whereas the cost of new infrastructure is minimized.

This intriguing macro-level departure from the inverse relationships that hold for organisms ends up risking more questions about the evolution of cities than it answers: What mechanism enables larger cities to produce disproportionately more innovation and wealth than smaller cities?

Data Economy has a fascinating article in a similar vein: Street Smarts: The Rise of the Learning City:

The city as a brain

An amalgam of terms that have been used for parallel conceptions of the Smart City among them cyberville, digital city, electronic communities, flexicity, information city, intelligent city, knowledge-based city, MESH city, telecity, teletopia, ubiquitous city, wired city.

However the one I would like to propose, with population movement in mind, is The Learning City.

The term is based on a combination of two theories The Ego City and The Flynn Effect.

In 2009 Neurobiologist Mark Changizi from the Rensselaer Polytechnic Institute released a paper entitled Ego City: Cities Are Organized Like Human Brain.

Changizi sees strikingly real similarities between the brain and a city.

The central idea being that they organise and evolve similarly due to the need for efficiency.

As brains grow more complex from one species to the next, they change in structure and organisation in order to achieve the right level of reciprocity.

This is analogous to the widening of streets in cities.

The research team found mutual “scaling laws” for brains and cities.

For example, as the surface area of a brain or city grows, the number of connectors (neurons or highways) increased at a similar rate for each.

Likewise, a bigger city needs more highway exits in the same proportion as a bigger brain needs more synapses connecting neurons.

“The brain is like a city.

Cities develop and grow bigger and may get problems with roads and infrastructure, which is similar to what happens to our brains when we get older”, notes Håkan Fischer, Professor of Biological Psychology at the Department of Psychology at Stockholm University.

 The learning city

This is curious when taken in the context of The Flynn Effect.

Intelligence Researcher James Flynn found that every decade without fail the human population scored higher on IQ tests.

An average increase of 3 points per decade.

His thesis suggests that the more information we as humans have to absorb and compute leads to an increase in IQ.

In this instance the increased information is data collected within the city.

As cities gain more data they adapt and in turn get smarter.

Human brains faced with a busier world filled with more information brings about an increase in IQ from generation to generation.

As people migrant to cities creating a more complex environment for the city it to must gather this data, learn and raise its Smart City IQ.

This is The Learning City.

On the other hand, the data Auerswald cites–from the “Santa Fe Team”–only looks at cities from the US, China, the EU, and Germany. How would this data look if it incorporated other megacities, like Manila, Philippines (the world’s densest city); Sao Paolo, Brazil; Bombay, India; Caracas, Venezuela; Karachi, Pakistan; or Jakarta, Indonesia? Of the world’s ten biggest cities, only two–Seoul, #1, and Tokyo, #10–are in the first world. (#9 Shanghai, is well on its way.)

#2 Sao Paolo might be more energy efficient than villages in the Brazilian hinterland (or it may not, as such towns may not even have electricity,) but does it produce more innovation than #11 New York City? (No American city made the top 10 by population.)

If cities are drivers of innovation, why are so many of the biggest in the third world? Perhaps third world countries offer their citizens so little that they experience a form of extreme brain drain, with everyone who can fleeing to the most productive regions. Or perhaps these cities are simply on their way–in a century, maybe Sao Paolo will be the world’s next Shanghai.

The city, by definition, is civilization–but does the city itself spur innovation? And are cities, themselves, living things?

Geoffrey West has some interesting things to say on this theme:

“How come it is very hard to kill a city? You can drop an atom bomb on a city, and 30 years later, it’s surviving.”

Here’s a transcript of the talk.

Hiroshima in 1945:

Hiroshima today:

Hiroshima montage

Detroit, 1905:

Belle Isle Park, Detroit, 1905–h/t Photos of Detroit’s Golden Age

Detroit today:

Detroit Book Depository

“Bombs don’t destroy cities; people destroy cities.”

Come read “The Code Economy: A 40,00 Year History” with us

I don’t think the publishers got their money’s worth on cover design

EvX’s Book Club is reading Philip Auerswald’s The Code Economy: A 40,000 Year History looks at how everything humans produce, from stone tools to cities to cryptocurrencies like bitcoin, requires the creation, transmission, and performance of “code,”  and explores the notion that human societies–and thus civilization–is built on a mountain of of encoded processes.

I loved this book and am re-reading it, so I would like to invite you to come read it, too.

Discussion of Chapter 1 Jobs: Divide and Coordinate, will begin on May 23 and last as long as we want it to.

Here’s Amazon’s blurb about the book:

What do Stone Age axes, Toll House cookies, and Burning Man have in common? They are all examples of code in action.

What is “code”? Code is the DNA of human civilization as it has evolved from Neolithic simplicity to modern complexity. It is the “how” of progress. It is how ideas become things, how ingredients become cookies. It is how cities are created and how industries develop.

In a sweeping narrative that takes readers from the invention of the alphabet to the advent of the Blockchain, Philip Auerswald argues that the advance of code is the key driver of human history. Over the span of centuries, each major stage in the advance of code has brought a shift in the structure of society that has challenged human beings to reinvent not only how we work but who we are.

We are in another of those stages now. The Code Economy explains how the advance of code is once again fundamentally altering the nature of work and the human experience. Auerswald provides a timely investigation of value creation in the contemporary economy-and an indispensable guide to our economic future.