A Quote by Kate Crawford
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.
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Knowledge about limitations of your data collection process affects what inferences you can draw from the data.
Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.
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.
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.
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'm repledging myself to human-scale values. As a fiction writer, the best data comes through the senses and is then processed through many revisions. We have to learn to be intelligent assessors of the data coming in to us and what it's doing to our mental process.
Data will always bear the marks of its history. That is human history held in those data sets.
What's going on in the game today... it's data vs. art - that's what it comes down to for me. Art being the human heartbeat, data being numbers, the math, etc. I believe there's a balance to be struck right there.
Watson augments human decision-making because it isn't governed by human boundaries. It draws together all this information and forms hypotheses, millions of them, and then tests them with all the data it can find. It learns over time what data is reliable, and that's part of its learning process.
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.
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.
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.
Design has a powerful impact on the viewer. It has authority, and data also has the same air of authenticity and detail. It can be hard to argue with a graph, and it's hard to argue with data. So to combine data with a strong visual impact creates a powerful message.
Listening to the data is important... but so is experience and intuition. After all, what is intuition at its best but large amounts of data of all kinds filtered through a human brain rather than a math model?
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.
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