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Samuel Arbesman: There Are Limits To Big Data—And To Our Knowledge, Too
Science | February 25, 2013

Samuel Arbesman: There Are Limits To Big Data—And To Our Knowledge, Too

Just because we know that something is true today doesn't mean that it will always be true—or that we should give up researching something when we think we have the right answer. In a new article in Slate, Samuel Arbesman, science speaker and author of The Half-Life of Facts, explains that our world is in "draft form." He refers to this idea as "pessimistic meta-induction", that despite thinking we have a firm understanding of the world today, previous generations once thought the same thing and they too were proven wrong. That's not necessarily a bad thing, though. The Senior Scholar at the Ewing Marion Kauffman Foundation says that we're "improving our view of the world and reducing error in our understanding." And, with the aid of machines, we may even be improving our world view to the point that we can no longer comprehend what we've learned.

"Does such a hint of non-understandable pieces of reasoning and thought mean that eventually there will be answers to the riddle of the universe that are going to be too complicated for us to understand, answers that machines can spit out but we cannot grasp?" Arbesman asks in the article. His response? "Quite possibly." Computers have already made developments that we know are true—even if we can't entirely understand them. Don't stress too much though, because he also says that: "Just because something is true, doesn’t mean that we can’t continue to explore it, even if we don’t understand every aspect." Just as there are potentially limits to what we can comprehend, Arbesman says there are also limits to what we can learn using big data—the newest craze.

The problem with this kind of data, Arbesman says, is that it only measures a snapshot in time. You cannot measure long-term trends using big data and we can sometimes lose sight of what we were seeking to understand in the first place. Not only that, but we sometimes get caught up in measuring what is easy and convenient instead of what we actually want to learn. That's not to say that we should cast out the benefits of big data. He tells MPR News that "big data is a powerful lens—some would even argue a liberating one—for looking at our world. Despite its limitations and requirements, crunching big numbers can help us learn a lot about ourselves." In his book and his keynotes, Arbesman uncovers the limitations to fully understanding our world—and why we shouldn't ever stop exploring despite them.
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