Steven Weber is a professor in the School of Information and Political Science department at UC Berkeley.
It's commonly said that most people overestimate the impact of technology in the short term, and underestimate its impact over the longer term.
Where is Big Data in 2013? Starting to get very real, in our view, and right on the cusp of underestimation in the long term. The short term hype cycle is (thankfully) burning itself out, and the profound changes that data science can and will bring to human life are just now coming into focus. It may be that Data Science is right now about where the Internet itself was in 1993 or so. That's roughly when it became clear that the World Wide Web was a wind that would blow across just about every sector of the modern economy while transforming foundational things we thought were locked in about human relationships, politics, and social change. It's becoming a reasonable bet that Data Science is set to do the same—again, and perhaps even more profoundly—over the next decade. Just possibly, more quickly than that.
There are important differences which have equally come into focus. Let's face it: Data Science is just plain hard to do, in a way that the Web was not. Data is technically harder, from a hardware and a software perspective. It's intellectually harder, because the expertise and disciplines needed to work with this kind of data span (at a minimum) computer science, statistics, mathematics, and—controversially—domain expertise in the area of application. And it will be harder to manage issues of ethics, privacy, and access, precisely because the data revolution is, well, really a revolution.
Can data, no matter how big, change the world for the better? It may be the case that in some fields of human endeavor and behavior, the scientific analysis of big data by itself will create such powerful insights that change will simply have to happen, that businesses will deftly re-organize, that health care will remake itself for efficiency and better outcomes, that people will adopt new behaviors that make them happier, healthier, more prosperous and peaceful. Maybe. But almost everything we know about technology and society across human history argues that it won't be so straightforward.
Data Science is becoming mature enough to grapple confidently and creatively with humans, with organizations, with the power of archaic conventions that societies are stuck following. The field is broadening to a place where data science is becoming as much a social scientific endeavor as a technical one. The next generation of world class data scientists will need the technical skills to work with huge amounts of data, the analytical skills to understand how it is embedded in business and society, and the design and storytelling skills to pull these insights together and use them to motivate change.
What skills, knowledge, and experience do you and your organization need to thrive in a data-intensive economy? Come join senior industry and academic leaders at DataEDGE at UC Berkeley on May 30-31 to engage in what will be a lively and important conversation aimed at answering today's questions about the data science revolution—and formulating tomorrow's.
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