What Technology Wants
In the Plex: How Google Thinks, Works, and Shapes Our Lives
(Simon & Schuster, 2011)
Final Jeopardy: Man vs. Machine and the Quest to Know Everything (Houghton Mifflin Harcourt, 2011)
To understand the future of innovation and entrepreneurship, listen to the technology. Don’t talk. Listen. Carefully.
“Listen to the technology” is Carver Mead’s mantra. The eccentrically brilliant Caltech engineer is an apostle of and evangelist for Moore’s Law, which states that chip circuit density reliably doubles every one to two years. Mead thinks that Moore’s Law is more about belief systems than technology. “When people believe in something,” he observes, “they’ll put energy behind it to make it come to pass.”
Belief systems that inspire great faith and even greater investment are powerful. Technologies and technical challenges that evoke such passion and commitment deserve to have their stories told. This year’s best technology books are well-crafted tales of what happens when people really listen to technology and believe what they hear.
At their core, these books describe how people and technology successfully coevolve to compete. The heroes here aren’t technologies, technologists, or entrepreneurs; they’re the innovation ecosystems that create transformative value and growth.
That’s why Kevin Kelly’s What Technology Wants, in which Mead is featured, reads like technology’s The Origin of Species. This sprawling compendium of argument and analysis asserts that technology is best understood not as materialized tools or actionable artifacts but as what he calls a technium — an ever-evolving system driven by the interaction of technology and people. By contrast, In the Plex: How Google Thinks, Works, and Shapes Our Lives is Steven Levy’s superb, surprisingly comprehensive Baedeker of what makes Google Google. Levy captures the accelerating evolution of a global innovation juggernaut and quirky collective of entrepreneurial talent. And Stephen Baker’s Final Jeopardy: Man vs. Machine and the Quest to Know Everything updates the behind-the-scenes sensibility of Tracy Kidder’s classic The Soul of a New Machine (Little, Brown, 1981) by observing how and why IBM committed itself to creating an artificial intelligence that could win on Jeopardy. The resulting computer, named Watson, dispassionately but definitively defeated humans and Ken Jennings, who had won US$2.52 million in 74 consecutive appearances on the show.
With eyes and ears wide open for detail, the authors of these three books are exceptional reporters. They artfully balance their insight into innovative people with their insight into innovative technologies. Their books position technology as pop culture and pop culture as technology.
Just as important, the books benefit from their living-in-the-moment narrative; they avoid the “Neugebauer dilemma” that plagues most high-tech histories. “The common belief that we gain ‘historical perspective’ with increasing distance seems to me to utterly misrepresent the actual situation,” observed the historian of mathematics and science Otto Neugebauer. “What we gain is merely confidence in generalization that we would never dare to make if we had access to the real wealth of contemporary evidence.”
These contemporaneous accounts of technical transformation possess that wealth. In these books, telling details don’t defer to facile “big think” generalizations. Executive readers desiring the big picture with meaningful technical detail will find these works useful.
For Kelly, What Technology Wants amplifies and expands upon Out of Control: The Rise of Neo-Biological Civilization (Perseus, 1994), his exploration of emergent behavior and complex systems. A complexity junkie, Kelly is a cofounder and former executive editor of Wired magazine. He is always on the rhetorical prowl for underappreciated systems interrelationships. He listens diligently to people and technology alike.
What Technology Wants, this year’s best technology book, fully commits to Kelly’s conceit that humans and their technologies coevolve. One is practically meaningless — or inert — without the other. Like the bacterial flora and fauna digesting food in our gut, he says, technology is a life force. The book is studded with biological metaphors and analogies. The suspension of disbelief that Kelly asks of his readership is the willingness to see technologies as living things.
With no apologies to Darwin, Kelly’s take on technology is more rooted in ecology than biology. Darwin’s great epiphany was that the Galapagos Islands mattered as much as the finch’s beak. Similarly, Kelly says that it’s intellectually and economically misleading to appreciate a technology outside its (un)natural habitat.
Trying to grasp technology by studying its underlying physics, chemistry, and engineering design is too reductionist, Kelly argues. Real understanding demands insight into the web of user beliefs — tacit and explicit — around the fitness and perceived evolvability of tools and processes. In other words, what can the technology become? What does it want?
Kelly’s imperative goes beyond evolutionary biologist Richard Dawkins’s vivid metaphor of the “selfish gene” to his lesser-known but comparably influential notion of the extended phenotype. Dawkins’s crucial insight is that successful birds are successful technologists. Nests, like the eggs they shelter, are essential to how birds perpetuate themselves. Poorly placed or shoddily constructed nests reduce the chances for reproductive success. Conversely, well-built nests dramatically improve the evolutionary odds. “Nest tech” — the twigs, leaves, hair strands, and so on — inarguably shapes both individual and species fitness. Divorcing bird biology from nest technology (and vice versa) fundamentally misrepresents bird reality. Technology is an extended phenotype, something external and transcendent that transforms the bio- and ecosystems of living things.
No species on earth better extends its phenotype than human beings. Human habitats and personal relationships are mediated and managed by all manner of evolving technologies. This has been true for millennia. In What Technology Wants, Kelly maintains that it’s becoming ever more crucial.
We are, he insists, committed to coevolve with the living artifacts of our creation: “Technology is simply the further evolution of evolution. The technium is a continuation of a four-billion-year-old force that pursues more ability to evolve. The technium has discovered entirely new forms in the universe, such as ball bearings, radios, and lasers that organic evolution could never invent. Likewise, the technium has discovered entirely new ways to evolve, methods that were unreachable by biology. And just as evolution did with life, technological evolution uses its fecundity to evolve more widely and faster. The ‘selfish’ technium generates millions of species of gadgets, techniques, products, and contraptions in order to give it sufficient material and room to keep evolving its power to evolve.”
That relentless and remorseless coevolution spawns a theme and thesis inhabiting the entire book: “the evolvability of evolvability.” In other words, how does evolution itself evolve?
“As evolution rises, ‘choicefulness’ increases,” Kelly writes. “A mind, of course, is a choice factory....”Different technologies appeal to different minds. Choices change as technologies evolve. Technologies evolve — and mutate — as those choices shift. But human minds won’t be the only “choice factories” in this emerging ecosystem.
Kelly’s technology wants choicefulness. Technologies are becoming smarter; they’re evolving with silicon and software-enabled situational awareness. They’ll be inventing, and evolving, new ways to choose, not just in cooperation with people, but also in competition with them. Does anyone doubt that tomorrow’s smartphone will recommend what pictures to take or phone calls to make? Whose choicefulness will exert greater influence over a typical day: the growing menagerie of your evolving devices or your mind, which (supposedly) tells them what to do?
The upshot is that almost everything people think they understand about intelligence, innovation, and choice needs to evolve as technology evolves. What Technology Wants is explicit acknowledgment that, now and tomorrow, trying to understand these three things distinct from our coevolving technologies is not merely self-deceptive but a denial of human potential.
Google’s Hive Mind
Arguably no company on earth better embodies Kelly’s thesis than Google. With its global reach, driverless automobiles, plethora of digital platforms, dizzying arrays of real-time algorithms, and density of computational expertise and server farms — not to mention its great and growing wealth — Google is a coevolving innovation ecosystem par excellence.
Google cofounders Larry Page and Sergey Brin do more than just listen to the technology; they’ve turned their company into a most fluent translator of its every hiccup, whisper, and utterance. Even bats must envy their flair for echolocation. They’ll hire the world’s best specialists, deploy microphones anywhere and everywhere, and do whatever it takes to ensure maximum technological intelligibility. But the genius of Page and Brin lies not in their own acuity, but with their ability to evoke it in others. They hunger for techno talent that listens even better than they do.
In the Plex flawlessly describes Google’s unique culture, which is dedicated to getting the world’s greatest technologists to innovate beyond disciplinary boundaries. Although Steven Levy does not quite offer — or create — fully rounded views of the many Googlers mentioned in his pages, his descriptions of their design sensibilities and innovation ethos are without peer. This is the best book about Google yet written, because Levy gets the “push the envelope until it rips” intellectual extremism that defines Google’s most effective intrapreneurs. Sure, they’re very smart. But their drive and ambition have to get Page and Brin hot and bothered, or they will not have much impact.
“Page once said that anyone hired at Google should be capable of engaging him in a fascinating discussion should he be stuck at an airport with the employee on a business trip,” Levy writes. “The implication was that every Googler should converse at the level of Jared Diamond or the ghost of Alan Turing. The idea was to create a charged intellectual atmosphere that makes people want to come to work. It was something that Joe Kraus [a top-tier Google hire] realized six months after he arrived, when he took a mental survey and couldn’t name a single dumb person he’d met at Google. ‘There were no bozos,’ he says. ‘In a company this size? That was awesome.’”
Serious readers will come away from In the Plex knowing in their heart of hearts that their own organizations aren’t as passionately committed to technology, technologists, and their creative coevolution as Google. Recruiting the very best quants and software jocks was simply the most obvious element in the coevolutionary equation. What really made the difference was the founders’ relentless emphasis on creating the fastest possible and best user experience. Milliseconds mattered. The fastest search had to be the best; the best search had to be the fastest. That is an innovation imperative requiring exquisite skills in listening to technology.
But Google’s founders — intuitively, analytically, or alchemically — thoroughly grasped that they had launched not a company but a global innovation ecosystem that technologically transformed value creation. The company’s culture evolved around the interaction of brilliant people with brilliant technology. It wasn’t just that smart Googlers made innovative technology; innovative technology made Googlers smarter. Google was as much a hive mind as an innovation ecosystem.
In the words of publisher and digital entrepreneur Tim O’Reilly, Google was the first real Web 2.0 enterprise: “The real heart of Web 2.0 is harnessing collective intelligence.” This was Google’s transcendental essence. Google understood and exploited the innovation ecosystem of network effects faster, better, and cheaper than anyone else. Virtually every successful investment the company made was based on the belief that the economics of network effects ensured that great innovation would be great business.
This proved true. From Page’s PageRank (pun intended) algorithm that made links the center of search to Google’s expropriation of rival GoTo’s auction business model for keyword search, Levy observes, everything was engineered around exponential expectations.
To succeed, Google would ultimately have to manage billions of queries and petabytes of data. To sustain success and growth, Google would inherently need to think not just big but huge. The firm would need to listen for and exploit network effects wherever it could find or create them. As Levy documents with relish, from Android mobile phones to Gmail to YouTube videos, Google literally and figuratively enjoyed an embarrassment of digitized riches.
What a fantastic innovation environment. Network effects meant that the innovation paradigm could shift away from linear research and development to more iterative experimentation and scale. Business experimentation soon converged and coevolved with technical and computational experimentation. Google’s ecosystem became an economy. So the company hired innovative Berkeley professor Hal Varian as its chief economist; Varian has proved adept at designing market mechanisms for monetization and using Google searches as forecasting tools for the global economy. (See “To Hal Varian, the Price Is Always Right,” by Michael Schrage, s+b, First Quarter, 2000.)
Levy holistically captures Google as a global business; a data-driven, experimentation-oriented innovation culture; a cutting-edge technologist; a pop culture icon; and the living extension of its founders’ vision. He strikes these balances remarkably well, although he is, perhaps, a little too generous to a company that clearly offered terrific access.
That said, Levy doesn’t flinch in describing Google’s difficult moments, such as the souring of relations with Apple’s late CEO Steve Jobs, who felt betrayed by the top management at Google when that company introduced the Android phone. Indeed, Levy’s earlier books on Apple — The Perfect Thing: How the iPod Shuffles Commerce, Culture, and Coolness (Simon & Schuster, 2006) and Insanely Great: The Life and Times of Macintosh, the Computer That Changed Everything (Viking, 1994) — give him great insight into and context for writing about idiosyncratic technical geniuses worth billions of dollars.
Levy also points to the struggle of retaining exceptionally talented people who invariably chafe at the technical and business conflicts that emerge in every fast-growing global enterprise. As dominant and influential as Google may be now (wasn’t that true of Microsoft barely a decade ago?), Schumpeterian reality suggests that today’s Googlers may be the firm’s most serious rivals tomorrow. To its credit, Google recognizes this. It knows that some of its best people may listen to the technology in a different way — and choose to do their translating elsewhere.
What Is “Watson”?
That “listen different” sensibility reverberates throughout Final Jeopardy. This book is more an hors d’oeuvre than a gourmet banquet. But it serves a tasty slice of the larger themes addressed by What Technology Wants and In the Plex. Sometimes the technology simply says, “What the heck.” Sometimes the seemingly trivial provokes serendipitous and significant leaps of innovation.
The sheer quixotic nature of the quest is silly but irresistible. Could IBM build a machine that could do for Jeopardy what Deep Blue did for chess? Could Ken Jennings — the ubergeek who captured the hearts, minds, and Nielsen ratings of America’s longest-lived TV game show as its most dominant champion — be turned into a 21st-century Gary Kasparov, the world’s top chess player who was defeated by IBM’s Deep Blue in 1997? Could creating a Jeopardy machine generate publicity for IBM even as it pushed the boundaries of real-time artificial intelligence research? As a successful Jeopardy contestant would answer, “What is yes, Alex?”
Although his prose is more serviceable than sparkling, Stephen Baker chronicles what happens when IBM’s serious researchers confront a high-risk/high-stakes challenge at the intersection of humiliation and breakthrough. Given the immature mix of artificial intelligence techniques and technologies, the Jeopardy challenge was far more difficult than that presented by chess.
After all, chess — the royal game — had been the lab rat of artificial intelligence research for decades. Jeopardy — the game show of the upper middlebrow — sometimes involved more competitive, interpretive, and open-ended interplay than chess. The task of recognizing, evaluating, and processing puns, pop culture references, and subtle wordplay in less than two seconds is a nightmarish programming proposition.
But David Ferrucci, the stressed-out researcher tasked with bringing Watson to life and Baker’s chosen hero, is fully committed. Money plays only a minimal role in this narrative. IBM supported the Jeopardy challenge both as a publicity stunt and as a forcing mechanism to integrate nonaligned strands of its artificial intelligence and analytics research efforts.
I’m comfortable arguing, as Baker is not, that a decade hence, Watson’s triumph in Jeopardy will be regarded as a far more technically and economically significant event in computing history than Deep Blue’s victory. Why? Because the way people interact with machines around seemingly simple questions and answers represents a profound shift in the coevolution of technology. It’s not an accident that one of IBM’s most important prototyping tools in Watson development was Google.
Just observing how IBM modeled, simulated, and evaluated what it takes to win at Jeopardy is an anecdotal treat. Knowledge is not the same as understanding. “This led to an early conclusion about a Jeopardy machine,” Baker writes. “It didn’t need to know books, plays, symphonies, or TV sitcoms in great depth. It only needed to know about them.... Ken Jennings, Ferrucci’s team learned, didn’t prepare for Jeopardy by plowing through books. In Brainiac [Jennings’s pop autobiography], he described endless practice with flash cards. The conclusion was clear: The IBM team didn’t need a genius. They had to build the world’s most impressive dilettante.”
Designing for dilettantism across the breadth and range of Jeopardy categories was enormously difficult. But Google- and Wikipedia-type technologies — combined with computationally intensive statistical learning algorithms — ultimately gave Watson the power to win.
When Ken Jennings lost to Watson, he noted on his (correct) final Jeopardy answer the mock ironic line from a famous Simpsons cartoon: “I for one welcome our new computer overlords.” This was a passing of the pop trivia torch from the most successful human player to his silicon successor. When Jennings completed his run of Jeopardy wins in 2004, no one in computer science — including the Googlers —would have predicted a Watson-like triumph within a decade.
Francis Bacon, the founding philosopher of science to whom the famous phrase “Knowledge is power” is attributed, also observed in 1620 that “we cannot command nature except by obeying her.” In this later observation, he anticipated Carver Mead’s aphorism by roughly 375 years. The essential truth of that prescient insight hasn’t changed a bit. But the technologies have evolved, in every meaning of the word. Their ongoing evolution, these three books agree, is also our own.
- Michael Schrage is a contributing editor to strategy+business and holds appointments at MIT’s Sloan School of Management and London’s Imperial College. He was previously a Washington Post reporter and a columnist for Fortune and the Los Angeles Times.