Big Data is Better Data (TED Talks)

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  1. What does the example of an apple pie prove?
  2. What does the presenter imply by saying that the data has gone from a stock to a flow, from something that is stationary and static to something that is fluid and dynamic?
  3. Does it worry you that “that somewhere, probably in a telecommunications carrier’s database, there is a spreadsheet or at least a database entry that records your information of where you’ve been at all times”? Do you feel devoid of privacy?
  4. What examples does the presenter give to prove that big data is a big deal? Can you think of your own examples?
  5. What feeling does the idea of computers capable of analyzing data and learning fast evoke in you?
  6. What are the dark sides of big data?
  7. How do you understand this: We may have algorithms that are likely to predict what we are about to do, and we may be held accountable before we’ve actually acted
  8. Do you agree with the presenter that many jobs will be eliminated?
  9. “This is a tool, but this is a tool that, unless we’re careful, will burn us.” – how do you understand this?
  10. To what extent do you agree with this? —

“If you’re active on Twitter or Facebook, share photos through Instagram, or blogging regularly, you’re already on your way to creating a Mindfile—a digital database of your thoughts, memories, feelings, and opinions that is essentially a back-up copy of your mind”



hype = advertisements and discussion on television, radio, etc. telling the public about a product and about how good or important it is

It is true that there is a lot of hype around the term, and that is very unfortunate, because big data is an extremely important tool by which society is going to advance.

render = cause someone or something to be something

Now, one reason why we have so much data in the world today is we are collecting things that we’ve always collected information on, but another reason why is we’re taking things that have always been informational but have never been rendered into a data format and we are putting it into data.

carjacker = the crime of forcing the driver of a car to take you somewhere or give you their car, using threats and violence

The idea is that the carjacker sits behind the wheel, tries to stream off, but the car recognizes that a non-approved driver is behind the wheel, and maybe the engine just stops, unless you type in a password into the dashboard to say, «Hey, I have authorization to drive.»

to aggregate = made up of several amounts that are added together to form a total number

telltale = showing that something exists or has happened

Maybe, if we aggregated the data, maybe we could identify telltale signs that best predict that a car accident is going to take place in the next five seconds.

fatigue = a feeling of being extremely tired, usually because of hard work or exercise

… then what we will have datafied is driver fatigue, and the service would be when the car senses that the person slumps into that position, automatically knows, hey, set an internal alarm that would vibrate the steering wheel, honk inside to say, «Hey, wake up, pay more attention to the road.»

to surpass = to do or be better than someone or something

Arthur Samuel has created a machine that surpasses his ability in a task that he taught it.

overt = done in an open way and not secretly

He changed the nature of the problem from one in which we tried to overtly and explicitly explain to the computer how to drive to one in which we say,»Here’s a lot of data around the vehicle. You figure it out.