As we begin a new year, perhaps the most certain prediction for the insights industry is that Artificial Intelligence will command a great deal of attention and cause a great deal of anxiety. Nearly every move today’s connected consumers make is being tracked and recorded by computers, creating data trails of incredible scale and complexity. Artificial Intelligence sorts and sifts through it all at speeds far beyond the reach of mere human intelligence.
To get a grasp on the power of Artificial Intelligence to assimilate masses of data and make predictions about human behaviors, consider what happened when AI took on the reigning human champions in the ancient Chinese game of Go.
In 2016, an AI program called AlphaGo played five games each against the world champion, Lee Sedol, and the European champion, Fan Hui. The score was nine wins for AlphaGo, and one for the humans, with Lee notching the lone victory. AlphaGo, which was created by Google’s DeepMind division, had mastered the game by assimilating a mass of data representing a specific human behavior — it had delved into an archive that housed records of all the moves made in thousands of games of Go played by humans.
But AlphaGo’s victory gave it no satisfaction. Algorithms don’t feel. Lee, on the other hand, expressed some surprising emotions in defeat: “I have questioned at some points in my life whether I truly enjoy the game of Go, but I admit that I enjoyed all five games against AlphaGo.”
Artificial Intelligence never stands still, and In 2017, AlphaGo had its comeuppance. It faced off in a 100-game match against AlphaGo Zero, a new Go-playing algorithm designed by Google. The new, improved algorithm won every game, and the online publication Gizmodo cited the shellacking as one of the most significant technological achievements of 2017. That’s because, except for being fed the rules of Go, AlphaGo Zero had received zero input from human beings. In three days, it had deduced from the rules alone how the game could best be played. It hadn’t needed to crunch a single move made by any other Go player, human or computer.
Do AI’s encounters with Go have implications for how we can understand and predict consumer behavior? Artificial Intelligence already can suggest products of interest based on shoppers’ past purchases and searches. Could it some day make the very act of shopping obsolete by becoming so expert at interpreting consumers’ preferences that they’ll simply hand over their purchasing decisions to algorithms they trust to produce more satisfactory outcomes than they could achieve themselves?
Or are the uniquely human capacities for emotion and intuition too fundamental to human satisfaction, including satisfaction with shopping and buying, for a machine to decide rather than merely suggest? It’s significant, and offers a spark of hope for those who value human agency and will, that Lee, the human world champion, had enjoyed playing AlphaGo even though he lost. AlphaGo could not say the same. Nor were the subsequent matches between AlphaGo and AlphaGo Zero anything but technological experiments. Those games were devoid of exhilaration and tension and fun for anyone but the algorithms’ designers. The loser felt no frustration, the winner felt no pride, and neither took the slightest bit of pleasure from the experience. Artificial Intelligence can dominate a game of Go, but it fails to comprehend the intrinsic qualities that have engaged the game’s human players for more than 3,000 years.
The human quirk of being able to enjoy even a losing experience illustrates the complexity of our emotions. Our true humanity lies in our unpredictability, our need for newness and surprise in some things, and for reliability and constancy in others. It’s the role of the insights professional to delve into how these slippery qualities drive consumer behavior. Can Artificial Intelligence model human emotions well enough to provide insights that inform business decisions better than surveys that ask real consumers about their motivations and how they felt about an experience? Will market research remain a job for people who can interpret people? Or is it primed for a complete takeover by extremely intelligent and fast-acting machines?
Perhaps we’ll know more by the end of 2018. Meanwhile, start your year with a productive conversation with a real human being about how mobile GeoLocation technology can put you in touch with real consumers at the moment they’re shopping or just after they’ve left a store. You’ll get the most vivid data possible at the Point of Emotion® where buying decisions are made. Artificial Intelligence tracks data that’s recorded after-the-fact. Data from surveys fielded through a mobile app gives you a window on what a consumer experience was like in-the-moment. Why did a shopper go to that particular store? What motivated the decision to buy or not to buy? What do shoppers say they feel about their experiences, when asked while those feelings are freshest in their hearts and minds? For answers on how to understand the consumer experience all along the path to purchase, and beyond, just get in touch by clicking here.