A Quote by Douglas Rushkoff
Everyone knows, or should know, that everything we type on our computers or say into our cell phones is being disseminated throughout the datasphere. And most of it is recorded and parsed by big data servers. Why do you think Gmail and Facebook are free? You think they're corporate gifts? We pay with our data.
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In the developed world, we are surrounded by electronics - from the computers on our desks to the smart phones in our pockets to the thermostats in our homes to our data in the virtual cloud.
There is a saying that if you get something for free, you should know that you're the product. It was never more true than in the case of Facebook and Gmail and YouTube. You get free social-media services, and you get free funny cat videos. In exchange, you give up the most valuable asset you have, which is your personal data.
In my view, our approach to global warming exemplifies everything that is wrong with our approach to the environment. We are basing our decisions on speculation, not evidence. Proponents are pressing their views with more PR than scientific data. Indeed, we have allowed the whole issue to be politicized-red vs blue, Republican vs Democrat. This is in my view absurd. Data aren't political. Data are data. Politics leads you in the direction of a belief. Data, if you follow them, lead you to truth.
MapReduce has become the assembly language for big data processing, and SnapReduce employs sophisticated techniques to compile SnapLogic data integration pipelines into this new big data target language. Applying everything we know about the two worlds of integration and Hadoop, we built our technology to directly fit MapReduce, making the process of connectivity and large scale data integration seamless and simple.
People need to differentiate us from companies like Yahoo! and Facebook that collect your data and have it sitting on their servers. We want to know as little about our users as possible.
The cloud is still really just a bunch of servers, owned by someone or something, whose decisions and competence must be trusted. This applies to everything from Google Docs to Gmail: Putting our data out there really means putting it 'out there.'
People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.
Removed from 'Gmail' doesn't necessarily mean removed from all Google servers. In fact, your old emails are the data set from which Google models our behaviors - the real product it is offering its advertisers.
All of these technologies that we are putting together... our memory technology, our CPU, our graphics architecture, our GPUs - all that is being applied to where the data is. You can almost predict where Intel will be in the future. It will be where data resides.
As a digital technology writer, I have had more than one former student and colleague tell me about digital switchers they have serviced through which calls and data are diverted to government servers or the big data algorithms they've written to be used on our e-mails by intelligence agencies.
We should have companies required to get the consent of individuals before collecting their data, and we should have as individuals the right to know what's happening to our data and whether it's being transferred.
How can we be free when we are prisoners to social media, in a world without privacy? How can we be free when our every movement is tracked and every conversation is recorded and can easily be held against us? How exactly are we free if we are tethered to our cell phones?
Apple knows a lot of data. Facebook knows a lot of data. Amazon knows a lot of data. Microsoft used to, and still does with some people, but in the newer world, Microsoft knows less and less about me. Xbox still knows a lot about people who play games. But those are the big five, I guess.
We should always be suspicious when machine-learning systems are described as free from bias if it's been trained on human-generated data. Our biases are built into that training data.
Everything is changing now that we are in the cloud in terms of sharing our data, understanding our data using new techniques like machine learning.
There are a number of fascinating stories included in 'The Human Face of Big Data' that represent some of the most innovative applications of data that are shaping our future.
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