A Quote by Max Richter

'Sleep' is a project I've been thinking about for many years. It just seems like society has been moving more and more in a direction where we needed it. Our psychological space is being increasingly populated by data. And we expend an enormous amount of energy curating 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.
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.
Data is the new soil, because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments.
There are two ways to be rich: to have more or need less. It's estimated that we squander about 30 percent of our energy leaving the lights on, the refrigerator door open, and so on. Then there is the enormous amount of food that we expend huge amounts of energy to raise and then throw away.
Disruptive technology is a theory. It says this will happen and this is why; it's a statement of cause and effect. In our teaching we have so exalted the virtues of data-driven decision making that in many ways we condemn managers only to be able to take action after the data is clear and the game is over. In many ways a good theory is more accurate than data. It allows you to see into the future more clearly.
The big thing that's happened is, in the time since the Affordable Care Act has been going on, our medical science has been advancing. We have now genomic data. We have the power of big data about what your living patterns are, what's happening in your body. Even your smartphone can collect data about your walking or your pulse or other things that could be incredibly meaningful in being able to predict whether you have disease coming in the future and help avert those problems.
I'm going to say something rather controversial. Big data, as people understand it today, is just a bigger version of small data. Fundamentally, what we're doing with data has not changed; there's just more of it.
There's enormous energy required to carry grudges - enormous energy! And I'm getting too old to expend my energy that way, cause I think every person has a limited amount of energy. So I have given up all grudges.
Trying to analyze a situation without enough data was like looking at a photograph of a ball in flight and trying to gauge its direction. Is it going up, down, sideways? Is it about to collide with a baseball bat? Is it moving at all, or is something on the blind side holding it in place? A single frame didn't mean a thing. Patterns were based on data. With enough datapoints, you could predict just about anything.
The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.
Government and businesses cannot function without enormous amounts of data, and many people have to have access to that data.
I still love coming into work everyday after so many years working as an actress. I've been working more or less continuously and I find I have to really want to do the project to make it work because you have to put such an enormous amount of effort into it.
As we become so visible in the digital world and leave an endless trail of data behind us, exactly who has our data and what they do with it becomes increasingly important.
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.
We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.
If we gather more and more data and establish more and more associations, however, we will not finally find that we know something. We will simply end up having more and more data and larger sets of correlations.
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