Communications of the ACM
Human Creativity in the Age of Smart Machines
In the midst of predictive analytics and machine learning, with big data sweeping across sectors and industries, the importance of small data cannot be overstated.
Credit: Cristbal Schmal
The traditional method used by social workers to help the homeless is a conveyor belt model, which moves people methodically from street, to shelter, to permanent housing. Few service providers ever questioned this basic model. Yet any experienced social worker would concede that there is a so-called service-resistant population: homeless individuals who refuse shelters. Faced with this reality, in 2001 a nonprofit organization called Common Ground (now known as Breaking Ground) conducted an experiment: a winter count of the homeless individuals in New York City's Times Square. The Common Ground team went out to the field. They suspended judgment, postponed analysis, and drew conclusions based solely on up-close observations and careful listening.
This idea of a human-centric design — developing solutions through intensive observation and gathering of small data, those tiny clues of human behavior — is especially profound today. The rise of smart machines often leads observers to paint an apocalyptic outlook for the traditional workforce. At their most extreme, predictions foretell the majority of white-collar jobs being automated, leading to a jobless future. What often gets left out of this narrative is that even as artificial intelligence (AI) and other emerging technologies are transforming the way routine tasks are done, they are also freeing humans from a sort of white-collar drudgery. This in turn allows people to do what they are best at: creative problem solving.
In the midst of predictive analytics and machine learning, with big data sweeping across sectors and industries, the importance of small data cannot be overstated. Big data and machine learning concern themselves with correlation, not causation. Computers excel at precision, rigor, and consistency, but they are not designed to integrate social interactions across domains, or traverse data online and offline, or come up with a working hypothesis that explains human behaviors. In other words, AI will augment professionals, offering them expertise and assistance. But it still takes creativity to ask the right question, the question that guides one toward a desired outcome — whether it's improved corporate performance or sheltering society's most vulnerable on a cold winter night.
From Strategy+Business
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