As chat and conversation continue to emerge, along with a sensor explosion due to the Internet of Things, I find myself wondering what sorts of side effects we’ll see in business, at play, how we shop and how we interact with each other. We tend to think a lot about this stuff while working on cashbot.ai
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 out predicted large groups of experts who rely on non swarm 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 crowd sourcing, 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 conversation & chat?
If the Internet is the largest decentralized network of interaction among humans, then the chat and conversational services will become the largest decentralized network of interactions among bots & humans. More fascinating still is the thought that humans will ultimately control many of these bots, actively or passively. We can expect to see elements of emergence in how developers design conversations to interact at scale, what to listen to, in real time, what the swarm is doing. With the infusion of outside data sources— weather data comes to mind—developers 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 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.
I love to think about the implications on product development, inventory rationalization, personalization, prediction and market research. Indeed, think about the effects on digital commerce.
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 conversational systems change dramatically. If we can observe, predict and react to user needs based on emergence, then we will need to rethink how conversational systems function at scale.
That’s what’s happening at cashbot.ai – we’re working on methods to listen, infer and interact at massive scale, with many diverse conversational end points. Of course this is all happening simultaneously.
Emergence is something that interests me quite a bit, I suspect as the conversational ecosystem matures and as cashbot.ai matures, it’s something we’ll have to investigate quite a bit more.
That’s it. I love you all – Peace out!