A Quote by Hilary Mason

Data science requires having that cultural space to experiment and work on things that might fail. — © Hilary Mason
Data science requires having that cultural space to experiment and work on things that might fail.
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.
As long as there is cash, and the economy is running, all is well. But as a bank, we'll have to test, experiment, try a hundred different things. A few may work, a few may fail, but we have to experiment and try.
Science is based on experiment, on a willingness to challenge old dogma, on an openness to see the universe as it really is. Accordingly, science sometimes requires courage - at the very least the courage to question the conventional wisdom.
Science is like society and trade, in resting at bottom upon a basis of faith. There are some things here, too, that we can not prove, otherwise there would be nothing we can prove. Science is busy with the hither-end of things, not the thither-end. It is a mistake to contrast religion and science in this respect, and to think of religion as taking everything for granted, and science as doing only clean work, and having all the loose ends gathered up and tucked in. We never reach the roots of things in science more than in religion.
It is a failure of imagination and methodology to claim that it is necessary to experiment on millions of people without their consent in order to produce good data science.
Scientific knowledge is, by its nature, provisional. This is due to the fact that as time goes on, with the invention of better instruments, more data and better data hone our understanding further. Social, cultural, economic, and political context are relevant to our understanding of how science works.
If you have a lot of data and you want to create value from that data, one of the things you might consider is building up an AI team.
I don't think that you can invent on behalf of customers unless you're willing to think long-term, because a lot of invention doesn't work. If you're going to invent, it means you're going to experiment, and if you're going to experiment, you're going to fail, and if you're going to fail, you have to think long term.
When you say what is the difference between me and my stage name the idea is that as a musician you always think of yourself as inhabiting a certain cultural space in the kind of a cultural landscape, so when I say cultural space what I mean to imply there is that you exist within certain parameters of how people think of culture.
The scientist-community guy may get a $500,000 grant, and if his equipment works or doesn't work, he still gets a gold star for doing the science experiment. For me, there is no merit in anything for doing an experiment; I have to go home with pictures.
I think context, location matters a lot. Because location obviously in my situation, it's the space in which the work is going to be exhibited. And since some of the work I do is created onsite, it requires a different type of space, versus the smaller drawings or more subject-oriented work. So that the context becomes important.
In the spirit of science, there really is no such thing as a 'failed experiment.' Any test that yields valid data is a valid test.
Science has only two things to contribute to religion: an analysis of the evolutionary, cultural, and psychological basis for believing things that aren't true, and a scientific disproof of some of faith's claims (e.g., Adam and Eve, the Great Flood). Religion has nothing to contribute to science, and science is best off staying as far away from faith as possible. The "constructive dialogue" between science and faith is, in reality, a destructive monologue, with science making all the good points, tearing down religion in the process.
There are two sources of error: Either you lack sufficient data, or you fail to take advantage of the data that you have.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
Sometimes you can fail in an experiment. But if you fail, you still don't stop observing that thing, looking for a better way.
This site uses cookies to ensure you get the best experience. More info...
Got it!