A Quote by Kate Crawford

When dealing with data, scientists have often struggled to account for the risks and harms using it might inflict. One primary concern has been privacy - the disclosure of sensitive data about individuals, either directly to the public or indirectly from anonymised data sets through computational processes of re-identification.
While many big-data providers do their best to de-identify individuals from human-subject data sets, the risk of re-identification is very real.
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.
I think philosophers can do things akin to theoretical scientists, in that, having read about empirical data, they too can think of what hypotheses and theories might account for that data. So there's a continuity between philosophy and science in that way.
Any time scientists disagree, it's because we have insufficient data. Then we can agree on what kind of data to get; we get the data; and the data solves the problem. Either I'm right, or you're right, or we're both wrong. And we move on. That kind of conflict resolution does not exist in politics or religion.
TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
Today, I think a CFO needs to be more of an operating CFO: someone who's using the financial data and the data of the company to help drive strategy, the allocation of capital, and the management of risks.
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.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
Data and data sets are not objective; they are creations of human design. We give numbers their voice, draw inferences from them, and define their meaning through our interpretations.
As individuals, we have very little say about how our data is being used. I'm not worried about the privacy implications of it so much. But it seems to me that, as an individual, if I'm the one generating the data, I should have some kind of say in how it's going to be used.
I will talk about two sets of things. One is how productivity and collaboration are reinventing the nature of work, and how this will be very important for the global economy. And two, data. In other words, the profound impact of digital technology that stems from data and the data feedback loop.
With too little data, you won't be able to make any conclusions that you trust. With loads of data you will find relationships that aren't real... Big data isn't about bits, it's about talent.
We tend to assume that data is either private or public, either owned by one person or shared by many. In fact there's more to it than that, above and beyond the upsetting reality that private data is now anything but.
I promoted Hyderabad to the world by saying that there was privacy in India and their data will be sage. Data is wealth.
The conjuror or con man is a very good provider of information. He supplies lots of data, by inference or direct statement, but it's false data. Scientists aren't used to that scenario. An electron or a galaxy is not capricious, nor deceptive; but a human can be either or both.
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