- Safi Bahcall – Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform (St. Martin’s Press, 2019)
- Kartik Hosanagar – A Human’s Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control (Viking, 2019)
- Clive Thompson – Coders: The Making of a New Tribe and the Remaking of the World (Penguin Press, 2019)
This is an odd moment in the history of technology and innovation. Technology companies have never been more powerful or influential. The five most valuable corporations in the world are all American tech giants, and the products they make and the services they provide continue to colonise an ever-larger chunk of our daily lives. Yet that very power has occasioned a serious anti-tech backlash, driven in part by a sense that these companies have too often exercised their might in a cavalier and careless fashion, and in part by anxieties about how their dominance may be hindering innovation.
So it’s only fitting that this year’s best business books on technology and innovation grapple with the fundamental challenges facing the tech world today — how to continue to drive radical innovation, how to manage the rise of ubiquitous machine intelligence, and how to make software that’s socially useful and beneficial as well as lucrative.
Silicon Valley has always prided itself on offering innovation. And yet in recent years there’s been a nagging concern that for all the money being poured into startups and all the money invested by the tech giants themselves, the payoff has been disappointing.
Safi Bahcall’s Loonshots,selected by strategy+business as one of the year’s best business books in technology and innovation, offers both an implicit explanation for this phenomenon and a recipe for how even big, established companies can nurture the kind of crazy ideas that ultimately turn into world-changing innovations. What Bahcall terms a loonshot is an attempt to take on a problem that is, as Polaroid founder Edwin Land put it, “manifestly important and nearly impossible” to achieve. These are the kinds of problems that we want companies to go after. But they’re also the kinds of problems that are difficult for companies, particularly established ones, to go after, because the risks are high and the payoffs are hard to measure.
How can a company become what Bahcall, the founder of a successful biotech company, calls a “loonshot nursery”? The models he points to were spearheaded by leaders who gave innovators — Bahcall calls them “artists” — the time and space they needed to develop ideas. They recognised that the task of coming up with new innovations is different from the task of turning innovations into concrete products and services, so they created separate groups for each function. At the same time, they didn’t denigrate the work of the “soldiers” whose job it was to execute the artists’ ideas. Healthy, successful organisations need both functions to thrive, and a dynamic equilibrium between the two.
Crucially, a company’s leader cannot act as the ultimate creator leading the organisation, like Moses, to the promised land. Instead, they must act like gardeners, creating processes that allow ideas to move from the nursery to the field, and useful feedback to come from the field to the nursery. Because they are not personally invested in any one idea, they lower the risk that they would bet too heavily on an ultimately doomed concept.
Coming up with groundbreaking innovations may be enormously challenging. So can being held responsible for managing the consequences of innovation. And in no field is that more true than artificial intelligence (AI), or what Wharton School professor Kartik Hosanagar more accurately calls “machine intelligence,” in his extraordinarily lucid A Human’s Guide to Machine Intelligence, next on s+b‘s list of best business books in technology and innovation.
Hosanagar has developed and deployed his own algorithms at a number of companies, and has spent many years studying the impact of algorithms on human behaviour. Written for laypeople, this book is as much about human behaviour and psychology as it is about technology, because it’s human behaviour that AI algorithms seek to alter, and human psychology that determines how we respond not only to what algorithms do, but also to the broader concerns they provoke.
Those concerns typically focus either on machines taking all our jobs or, more apocalyptically, on machines becoming self-aware — à la Terminator’s Skynet — and then destroying (or trying to destroy) humans. But although Hosanagar touches on these issues, his real focus is on the way algorithms are already having a profound influence on our choices and decisions, remaking us in ways that we oftentimes don’t even notice.
Hosanagar is a firm believer in the long-term benefits of machine learning, which has dramatically improved the diagnosis of disease and the management of money. But he is also keenly aware of the costs and the dangers that may arise as machine learning becomes more ubiquitous. It’s essential, he argues, to pay attention to the negative effects of algorithmic decision making, because if we don’t, they “will become deep-seated and harder to resolve.” And if we don’t engage with how humans respond to algorithms, we risk a backlash against machine learning in particular that could chill innovation in the field.
Hosanagar suggests that what we need is an algorithmic bill of rights. The basic idea is that we need some measure of transparency and control, and that those devising algorithms need to acknowledge the way they can create unintended and perverse consequences. But as journalist Clive Thompson shows to great effect in his rigorous and fascinating Coders, strategy+business’ pick of the best business book of the year on technology and innovation, the challenge is that the kind of people who write and devise the algorithms that are coming to govern so much of our lives are not, at the moment, necessarily the kind of people who care all that much about their negative effects.
Understanding coders has never been more important. One of the distinctive developments of the past 20 years is that coders are now the people running companies, the people in charge of making really important decisions that shape our politics, our economy, and much of our everyday lives. Those decisions have been enormously lucrative, but have also led to an enormous amount of skepticism about the value of the work that coders do. Although there are surely people in Silicon Valley who still see technology as the way to a brighter, freer, more connected future, the double-edged nature of technology, and of the internet specifically, should be obvious.
Thus the importance of Thompson’s book is that it helps us understand, in a deep sense, the world coders inhabit. It’s a world in which efficiency is often seen as a paramount goal. And it’s a world in which the issues that matter most have been practical ones — did these lines of code accomplish the task they’re supposed to accomplish? It’s also a relatively homogeneous world: predominantly male, predominantly young, and overwhelmingly white and Asian. And Coders does an excellent job of illuminating how that homogeneity shapes the choices the group makes, and the innovations they produce.
Coding, as Thompson describes it, can encourage a certain narrowness of vision, a limited perspective on how the world works and what matters. And what Silicon Valley needs now is a wider range of perspectives that can inform the decisions about what it chooses to build and, just as important, what it chooses not to build. In the absence of real government action, companies need to think much harder about those questions than they have before, because the ubiquity and influence of social media and the rise of machine learning mean that the stakes are incredibly high.
About the Contributor: James Surowiecki is the author of The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations.