The Internet of Things and the wisdom of crowds
As the Internet of Things (IoT) continues its explosive expansion, I find myself wondering how side effects of the Internet of Things will weave their way into our everyday lives.
Emergence, says Wikipedia, is “a process whereby larger entities, patterns, and regularities arise through interactions among smaller or simpler entities that themselves do not exhibit such properties”—as I was reminded when I listened to a Radio Lab podcast on just that topic. In it, the host spoke of Sir Francis Galton, a Victorian statistician, sociologist and psychologist who pioneered the application of statistical methods to the study of human differences and inheritance of intelligence.
At a country fair, runs the story, Galton asked bystanders to guess the weight of an ox. To his surprise, averaging the guesses produced a figure only a pound away from the actual weight of the ox, suggesting to him the idea of the wisdom of crowds. Though many of Galton’s ideas were later debunked, his contributions—the concept of emergence among them—enabled advances in many of the disciplines he studied.
Today, when we speak of the wisdom of crowds, we talk in particular of human swarming, an approach that uses real-time feedback loops from groups of users to arrive at accurate insights. Indeed, swarming has sometimes outpredicted large groups of experts who rely on nonswarm methodology.
Take, for example, the work of researchers working with Unanimous AI, who asked groups of people to take part in various intellectual tasks. Among other things, members of participant groups attempted to predict the winners of the NFL playoffs, the Super Bowl, the Golden Globes, the Oscars, the NBA finals and the Stanley Cup. In every case, the swarm outperformed not only individuals within the swarm, but also the experts within the swarm. Perhaps, then, human swarms reveal the “wisdom of the crowd,” unlocking the collective intelligence of populations.
We see emergence in the Internet as well—a large, decentralized system of human interaction capable of displaying emergent characteristics, having no formal organizing principle but only links pointing to one another, enabling traffic between them. Such a network can be described as an emergent system, as Google is well aware. Indeed, Google’s entire search model is based on the notion of emergence. Crawling the web and evaluating the relevance of pages based on traffic between them is Google’s way, so to speak, of guessing the weight of the ox. And that’s just the beginning. Take crowdsourcing, for example—yet another instance in which bits of information can create an aggregate structure of information.
Create opportunities for emergence
What does this have to do with the Internet of Things?
If the Internet is the largest decentralized network of interaction among humans, then the Internet of Things is the largest decentralized network of interaction among things. More fascinating still is the thought that humans will ultimately control many of these things. We can expect to see elements of emergence in how manufacturers use IoT devices and products to monitor, in real time, what the swarm is doing. With the infusion of outside data sources—Weather Company data comes to mind—manufacturers may begin to understand not just what the swarm is doing, but why.
For more on this, check out what Enterprisetech.com had to say about emergence—and notice the new IoT term “sensory swarm”:
“In the near future, we are going to have a sensory swarm, a great deal, a great variety of all kinds of heterogeneous sensors that are going to interface the cyber world, the computing world, with the physical world,” according to Alberto Sangiovanni-Vincentelli, an electronic design automation expert at the University of California at Berkeley.
Only think of the implications for product development, inventory rationalization, personalization, prediction and market research. Indeed, think about the effects on cloud computing!
Rethink your supply chain
As we continue to heighten connectivity and adopt analytical models that capture emergent properties, we may well see core business processes and IT systems change dramatically. If we can predict customer needs based on emergence, then we will need to rethink supply chain optimization and supplier rationalization. Even the places where we store our manufactured products may change—after all, why keep a widget in Texas if only people in the northwest will need it next year?
That brings us to the idea of product market fit. Suppose you build a product that is so well fit for its purpose that your clients begin recommending it at every chance. You see second and third sales happen; renewals are at 100 percent. This is every company’s ideal, but how often does it actually happen? Yet, if companies can identify emergent trends, will this become the norm? I hope so. Indeed—for this and many other reasons—the Internet of Things gets more interesting by the day.
Are you trying to take advantage of emergence in your organization? Join the conversation in the comments, or connect with me on Twitter @peter_ryans.