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University Lectures

Former Amazon chief scientist to speak Tuesday for lecture series, discusses future applications of social data

Andreas Weigend, big data expert and former chief scientist at Amazon, will be giving the first University Lecture of the spring semester Tuesday at 7:30 p.m. Weigend is the founder of the Social Data Lab, an organization that enables companies to make better use of social data and to enable the consumer to make better decisions. In his lecture, Weigend will talk to students about using data to benefit themselves and others.

The Daily Orange: You spoke at MasterCard’s International Advisory Board meeting that was titled, “The Untapped Power of Data: Refining the New Oil.” What makes data the new oil?

Andreas Weigend: Let me give you an example of a data refinery: Google. Google takes all the data however they can get to it. Then, you enter the search term in a given situation, with a given history of search terms. In my case, Google knows 50,000 search types. So they know quite a bit about you. And then they refine. They crank in the background to find the answer. They find and they give me a product that helps me make a better decision.

The D.O.: What are some practical applications of data that are often used in the businesses that you have worked with?

A.W.: Since I was the chief scientist at Amazon, let’s start with electronic retail. I think all of your readers are familiar with the feature “people who bought X, also bought Y.” My personal favorite is “people who looked at X eventually bought Y.” Why is that a personal favorite of mine? Because it helps people even more in the decision making process. As you are clicking on an item, you thought about a search term, now you harvest the collective intelligence of hundreds of millions of users. How they were thinking when they were clicking on that item and what they got out of that item or by another item.



The D.O.: What do you want Syracuse University students to know about data?

A.W.: In the past, data was used to optimize. An Amtrak train would try to be optimized using data. The schedules of students to minimize overlap would be optimized. There, the quality is different from what is going on with data now. Data has become the product. Let’s take Facebook. Facebook is not about optimizing our behavior. Facebook is taking data by the people, of the people and making data for the people.

The D.O.: Is there a method to data mining? How do you sift through so much information?

A.W.: Don’t start with data. Start with the questions. It is a circle. You start with the questions. You find your data. You refine your questions. So that is the approach. When we get all of this data, what should we do with it? If you can’t formulate the questions, then you won’t get anything out of it.

The D.O.: What is next for big data?

A.W.: I think data is a centrally important thing for government to think about. And when we talked about the balance of power earlier, I forgot to tell you about the balance of power between citizen and government. Those are where the shifts are. I think how those shifts happen, that is our concern. In the spirit of the audience at the University Lecture, people need to understand what the trade-offs are.

The D.O.: What kinds of trade-offs are there?

A.W.: If (citizens) are not sharing their data, then science cannot provide them with services. I expect them to not be naïve and want to have anonymity, but then not to have anonymity when something could be retrieved. All my hope really is that people think deeply about what they can get and what the implications are. I am fully supportive of whatever decision they make.





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