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Big Data and the Philosophy of Knowledge

Big Data and the Philosophy of Knowledge

We live in an era in which "big data" is supposed to solve lots of problems for businesses.  By looking at the buying patterns of a large number of individuals, retailers can get insights into how to sell to customers more effectively.  Credit card companies can detect fraud by exploring purchase patterns that have signaled bad transactions in the past.  Companies can learn about the types of employees who are likely to be effective by exploring characteristics that have been good indicators of success in those roles before.  Websites like  http://www.fivethirtyeight.comfivethirtyeight.com use data from a variety of sources like polls to help make predictions about events like polls.

This approach signals a shift in which companies are taking an empirical approach to answering questions.  The idea is that data from the past can be used to determine what might be true in the future.

I am a fan of big data and (as a scientist) I am also happy to see people interested in answering questions by looking at sources of data in the world.

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At the same time, I think it is important for people to be clear about the kinds of questions that data can and cannot answer.  That means that it is valuable to take a peek at the philosophical field of epistemology, which studies knowledge.

A key question in epistemology is how we can know whether something is true and whether a particular opinion is worth believing.  Data is often a good source of belief, but it is not useful for answering every question.

Data is most valuable for helping to settle matters of fact.  Science advances by using data to distinguish between theories that explain how aspects of the world works.  Different theories make different predictions about what we are likely to observe in a particular situation.  When the data support one theory over another, that increases our confidence that a particular theory is correct.  Of course, no theory can ever be proven definitively.  New data may always come along that contradict a strongly-held theory. But, many theories (like the theory of evolution in biology) have enough support that it would be hard to supplant them.

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There are many things that businesses need to know that are matters of fact of this type.  Drug companies, for example, can use the scientific method to explore whether a particular drug is effective at treating a disease.

 



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