Random finds (2016, week 23) — On lean, mean, learning machines, our bias for action, and the shortcomings of artificial intelligence
Every Friday, I run through my tweets to select a few observations and insights that have kept me thinking over the last week.
Lean, mean, learning machines
According to Aaron Dignan, founder at The Ready and the former CEO of Undercurrent, today’s fastest growing, most profoundly impactful companies are using a completely different operating model.
“Tesla, the fastest-growing stock in the automotive industry, is run by a software engineer. Amazon has a market cap three times bigger than Target, even though it operates at a loss. Instagram, a company with only thirteen employees at the time, was acquired for a billion dollars just three months after Kodak filed for bankruptcy. These are technology companies doing extraordinary things. But there is a larger pattern here. The dominant players in video, music, retail, recruiting, and direct marketing are also companies that operate like tech startups. This phenomenon is spreading, and soon enough every category on the planet will be shaken up.”
Most big corporations experience a rising pressure to innovate. But legacy processes that were built for another era, continue to enforce bureaucracy, command-and-control structures, waterfall development, and risk management; processes turn out to be great liabilities in the fight against unencumbered and fast-growing startups.
“They engineered a system so robust, that it’s still with us today, continually producing identical people for a machine that no longer exists.” — Sugata Mitra in his 2013 TED Prize acceptance speech.
These fast-growing companies are lean, mean, learning machines. “They have an intense bias to action and a tolerance for risk, expressed through frequent experimentation and relentless product iteration,” Dignan writes. “They hack together products and services, test them, and improve them, while their legacy competition edits PowerPoint. They are obsessed with company culture and top tier talent, with an emphasis on employees that can imagine, build, and test their own ideas. They are maniacally focused on customers. They are hypersensitive to friction — in their daily operations and their user experience. They are open, connected, and build with and for their community of users and co-conspirators. They are comfortable with the unknown — business models and customer value are revealed over time. They are driven by a purpose greater than profit; each has its own aspirational ‘dent in the universe.’” These are the first generation of truly responsive organizations.
Non-responsive organizations try to plan their way around uncertainty. Responsive organizations test their way through it.
It’s easy to assume that this new approach is limited to software companies only, but according to Dignan, the reality is more complicated. “As software ‘eats’ new categories and verticals, the winners (and the categories themselves) start to look more like technology platforms (think: Uber vs. car services, Twitter vs. the news media, Amazon vs. the department store, or Airbnb vs. hotels). The physical world that we used to value so much — the devices, cars, real estate, and other infrastructure — are merely inventory for something bigger. The value, it seems, is in the data, the tools, and the optimization of markets.”
Dignan has found that the shift these new organizations represent can best be understood through these five nested domains, which he describes in more detail in The Operating Model That Is Eating The World:
Purpose: from growth as a commercial agenda to growth as a visionary agenda.
Process: from process as quality assurance to process as learning mechanism.
People: from people as managers of competitive advantage to people as makers of competitive advantage.
Product: from product built to last to product built to evolve.
Platform: from a platform the company builds upon to a platform the world builds on.
Although powerful on their own, the real magic occurs when these domains interact with each other: “A living, breathing organization experiences constant interplay between them — a tension that can drag it down or take it to new heights. New People may balk at old Processes and institute new ones that spread.” Together they form a new Operating System, a Responsive OS, that can be applied at any level within an organization: an individual, a team, a department, or a division. “In fact, in our experience,” Dignan concludes, “a rogue unit operating using a Responsive OS is often the best method for insurgent transformation of the enterprise. Like the original Skunk Works that paved the way, this method of doing business needs space to breathe and mature, before it spreads like wildfire.”
Further reading (and watching)
The Future of Organizations is Responsive. How to Unlock Your Organization’s Potential to Change the World, Mike Arauz’ talk, including slides, during the Telstra Retail Innovation Summit, Sydney, February 2016. Mike Arauz is a Founding Member at August, and, before that, partner at Undercurrent.
In big companies, doing still trumps thinking
“Many executives in big companies attained their positions by excelling at getting things done. Unfortunately, a bias for doing rather than thinking can leave these executives ill-equipped for their new roles,” Duncan Simester writes in The Lost Art of Thinking in Large Organizations.
While approaching a strategic business problem, the focus quickly narrows to proposing solutions. When asked why, many executives respond that they don’t have time to think. Apparently, they don’t seem to recognize that thinking is part of their job. The reason, according to Simester, can be found in the relentless focus on execution in many large companies. “A company becomes big by finding a successful business model — and then scaling it massively,” he writes. “This necessitates building a finely tuned system with highly standardized processes. To get promoted in such an environment requires an almost singular focus on execution. In other words, it requires action more than thinking.” But the very skills that led to their promotion make many of these executives ill-equipped for their new roles.
Many executives don’t seem to recognize that thinking is part of their job.
Simester believes delegation is the key to finding time to think. Delegation, no doubt, frees up time, but it still leaves me with another question: ‘how’ will they think? What is the quality of their thinking? Time, I feel, is not the only issue at hand.
From a very early age on, we have all been trained and educated to be rational people — a notion that can be traced back to Aristotle, whose continuous struggle for finding a ‘better’ truth has left us suspicious of contradictions. We have come to believe that the more we know, the better we can predict. That if you want large outcomes, you have to put large amounts of effort or resources into it. That finding answers, preferably theanswer, is better than raising questions. Most of us analyze our way through a problem onto a single solution.
That’s fine as long as the world acts accordingly. As long as the world is linear and predictable. But it isn’t, not anymore. (Has it ever been?) Yet, many executives, but not only them of course, try to solve today’s complex challenges with 2 by 2’s and yesterday’s logic. As a consequence, their organizations miss out on great opportunities for new growth and innovation. While at the same time, run the risk of being disrupted.
This paradigm shift from linearity to complexity — from independent predictable systems to interdependent adaptive and even emergent systems — requires more than ‘time to think.’ It requires different, non-linear ways of thinking, and of looking at the world.
A bit more …
Adrienne Lafrance, a staff writer at The Atlantic, where she covers technology, tried if she could give ‘Robot Adrienne’ a crash course in journalism by having it learn from a trove of her past writings, and then publish whatever it came up with.
Lafrance isn’t exactly overwhelmed by her robotic alter ego’s writings. No wonder, because, even as the field of machine learning blossoms, language generation hasn’t fundamentally changed in recent decades. According to Jaime Carbonell, the director of the Language Technologies Institute at Carnegie Mellon University, machines, so far, haven’t been able to acquire general intelligence. “There are things like writing fiction or writing poetry,” Carbonell says, “where it’s not clear what it means for a computer to be able to do it, since the machine can not directly experience the emotions you’re trying to convey. It’s difficult to fathom how you could generate genuine creative writing in that sense. There are categories of activities in which it doesn’t really make sense to train the computer to do it. You would just get some ersatz version of a human.”
“Enabling a computer to teach itself to write, even once the machine gets the hang of it, actually is human work — even if human jobs are made obsolete as a result,” Lafrance writes in A Computer Tried (and Failed) to Write This Article. “So far, the ersatz version of me has quite a bit to learn.”
Read on The Atlantic: http://www.theatlantic.com/technology/archive/2016/06/story-by-a-human/485984/?utm_source=atltw.
More ‘Man versus Machine’ in The Guardian, where Leo Benedictus puts AI to the test. Can it paint a portrait? Can it plan a meal as well as Yotam Ottolenghi? Is technology still artificially intelligent — or is it starting to be intelligent, for real? His verdict on the cooking test: “Watson hides the weirdness of the ingredients, but Ottolenghi makes them sing.”
Read on The Guardian: https://www.theguardian.com/technology/2016/jun/04/man-v-machine-robots-artificial-intelligence-cook-write.
Deepak Chopra writes on the perils of artificial intelligence on Huffington Post. According to Chopra “AI has taken us to the verge of an Orwellian dilemma, because the spectacular advantages offered by computers weigh so heavily and create such enormous optimism, it’s easy to overlook one flaw: AI isn’t based on the truth. Computers process information at lightning speed and their abilities improve as the algorithms that are programmed into them become more sophisticated. Yet, without question, life isn’t algorithmic, which means that no computer can ever truly be alive. Computers cannot and will never have minds.”
Artificial intelligence isn’t based on the truth.
“When Picasso invented Cubism, when Tolstoy imagined Anna Karenina jumping in front of the train, when Keats wrote the final draft of ‘Ode to a Nightingale’ in a few frenzied minutes, turning a promising poem into a masterpiece, creativity made leaps that were not based on mixing and matching the ingredients of what came before. Logic didn’t come into it.”
“Of all the weird contradictions that plague modern life, the strangest is the collapse of philosophy with the triumph of science,” Chopra continues. ‘Aesthetics, morals, love, transcendence, idealism — all of these fields of thought, having persisted for thousands of years, in the East and in the West, mean nothing in scientific terms because they cannot be reduced to data, measurements and experimentation. AI attempts to defy such an obvious truth by its belief that absolutely everything is reducible to data.”
What we need is a wholesale commitment to a meaningful life, placing our best hopes there, not in logic machines and their parody of having a mind.
Chopra nevertheless believes great benefits can come out of AI. Technology shows no sign of slowing down and promises endless improvements. But while that’s going on, human beings live their lives according to those banished, discredited things: aesthetics, morals, love, transcendence and ideals. They are the way to make life meaningful and fulfilled.
Read on Huffington Post: http://www.huffingtonpost.com/deepak-chopra/artificial-intelligence-human_b_10240122.html.
Southern Californian and especially Los Angeles provided a promising environment for many of the formidable European minds who came to America around the Second World War, including writers like Aldous Huxley, composers like Arnold Schoenberg, and philosophers like Theodor Adorno. Architects, such as the earlier arrival Richard Neutra, thrived in the young city’s vast space and under its bright sun, giving shape to a new kind of twentieth-century house, one influenced by the rigorously clean aesthetics of the Bauhaus movement but adapted to a much friendlier climate, both in terms of the weather and the freedom from strict tradition.
Even if you don’t know much about architecture, you immediately recognize these houses, also known as ‘Case Study’ houses, from their countless appearances in movies, television, and print over the past seventy years. Sooner or later, everyone sees an image of Neutra’s Stuart Bailey House, Charles and Ray Eames’ Eames House, or Pierre Koenig’s Stahl House. The decades have turned these and other houses from the peak of midcentury modernism into priceless architectural treasures — or at least extremely high-priced architectural treasures. Some open themselves to tours now and again, but very few of us will ever have a chance to experience these houses as not quasi-museums but actual livable spaces.
Now we have the next best thing in the form of the University of Southern California’s Architectural Teaching Slide Collection, which collects about 1,300 rarely seen photographs of midcentury modern houses shot all over the western United States from the 1940s to the 1960s by Koenig himself, along with his colleague Fritz Block. The archive also offers images of models, blueprints, and other such technical materials.
Browse through the collection on UCS Digital Library: http://digitallibrary.usc.edu/cdm/landingpage/collection/p15799coll42.
Read on Hyperallergic: http://hyperallergic.com/287131/1300-intimate-images-of-midcentury-modernist-structures-go-online.
Watch the documentary film Coast Modern (available in iTunes): https://itunes.apple.com/movie/coast-modern/id655413445.
Some striking examples of brutalist architecture in The Guardian, including New York’s TWA Terminal, by the Finnish American architect and industrial designer Eero Saarinen
Saarinen was commissioned to design a terminal at JFK airport that would ‘capture the spirit of flight.’ Construction started in 1956 and was completed in 1962, a year after Saarinen’s death. Named a New York City landmark in 1994, it has been unused since 2001 as it couldn’t handle larger aircraft. Last year it was announced the building would be redeveloped as a hotel.
See on The Guardian: https://www.theguardian.com/cities/gallery/2016/jun/07/brutalist-world-architecture-peter-chadwick-in-pictures?CMP=share_btn_tw.
“We need novels to see the world through the eyes of others.” — Orham Pamuk