If we are to believe the evidence from clinical trials there are many effective pharmacological and psychological treatments for mental illness. Epidemiological data, on the other hand, says otherwise.
It's not just that there is a cooperative spirit of investigation there, where we all recognise that we are engaged in a common project of inquiry. It's also that the philosophers are well-versed in the relevant empirical data, and the scientists are well-versed in the more abstract issues which are typically the central focus of philosophical work.
The use of neuroscientific data to help resolve phenomenological questions is proving a common theme in much contemporary thinking about the mind. How rich are the contents of visual perception? Does vision only tell us about shapes and colours, or does it also represent higher categories like lemon or umbrella?
Remember, in the heyday of vitalism, people said that when all the data are in about cells and how they work, we will still know nothing about the life force - about the basic difference between being alive and not being alive.
So as soon as you want something to happen you begin skewing the data to support it. Our stuff is invaluable to decision-makers precisely because we have no ax to grind.
Technology and the Internet have created a new set of relationships. It's changed the social fabric of promotion: advertising, dating. Part of art world judgment, part of it, is based on people's statistics; their measure of financial value: of likes, of popularity. Data and technology are invading the traditional and classic set of criteria.
I believe that the data will set you free. At the end of the day, it’s about how do you turn those pieces of information into insights that will improve business.
The changes are coming so quickly it's been difficult for workers to retrain themselves and for entrepreneurs to figure out where the next opportunities may be. The catalyst is something called computer learning or artificial intelligence - the ability to feed massive amounts of data into supercomputers and program them to teach themselves and improve their performance.
The art is in preparing the content for optimal human consumption. The data doesn't just talk back to you. You collect, you analyze, you tell stories.
We have 25 or so years invested in the work. Why should I make the data available to you, when your aim is to try to find something wrong with it.
With portable cameras and affordable data and non-linear digital editing, I think this is a golden age of documentary filmmaking. These new technologies mean we can make complicated, beautifully crafted and cinematic films about real-life stories.
The key to good decision making is evaluating the available information - the data - and combining it with your own estimates of pluses and minuses. As an economist, I do this every day.
We should teach the students, as well as executives, how to conduct experiments, how to examine data, and how to use these tools to make better decisions.
If you entrust your data to others, they can let you down or outright betray you.
Perhaps... some day the precision of the data will be brought so far that the mathematician will be able to calculate at his desk the outcome of any chemical combination, in the same way, so to speak, as he calculates the motions of celestial bodies.
The whole enterprise of teaching managers is steeped in the ethic of data-driven analytical support. The problem is, the data is only available about the past. So the way weve taught managers to make decisions and consultants to analyze problems condemns them to taking action when its too late.
We have the data to prove to men that gender equality is not a zero-sum game, but a win-win.
Thought, without the data on which to structure that thought, leads nowhere.
Think of your existing power as the exponent in an equation that determines the value of information. The more power you have, the more additional power you derive from the new data.
Some of the best theorizing comes after collecting data because then you become aware of another reality.
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.
A hacker doesnt deliberately destroy data or profit from his activities.
Cloud computing offers individuals access to data and applications from nearly any point of access to the Internet, offers businesses a whole new way to cut costs for technical infrastructure, and offers big computer companies a potentially giant market for hardware and services.
Big data will replace the need for 80% of all doctors
Engineering, I think you can pick up. [A data scientist's] curiosity is built-in
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