Marcus Sakey Quotes

I say I write extrapolations. I look at data points and ask what the world could look like.

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.

Data is a tool for enhancing intuition.

The big mystery of Big Data is causation versus correlation.

Well, we'll look at the hundred thousand type A personalities, and then we'll have a look at the corresponding data points that we have on those hundred thousand people. We'll have a look at what attributes they have in common and then we'll build a model based on that.

To learn something from your data, the forming of a hypothesis lies with the human being, which turns into a query, which becomes a result. The problem is that there are too many queries to make, too many questions to ask.

I don't really know what I want, other than good sequences, whatever that means. What I find is always a matter of chance, judgment, and luck.

But the indeterminate future is somehow one in which probability and statistics are the dominant modality for making sense of the world. Bell curves and random walks define what the future is going to look like. The standard pedagogical argument is that high schools should get rid of calculus and replace it with statistics, which is really important and actually useful. There has been a powerful shift toward the idea that statistical ways of thinking are going to drive the future.

Of course, having information to use is one thing. Knowing what it means and how to use it is a different story.

Statistics were magic like this: they could tell you with near-certainty that a thing would occur, without a hint of when or where.

We were required to predict a soldier's performance in officer training and in combat, but we did so by evaluating his behavior over one hour in an artificial situation. This was a perfect instance of a general rule that I call WYSIATI, "What you see is all there is." We had made up a story from the little we knew but had no way to allow for what we did not know about the individual's future, which was almost everything that would actually matter. When you know as little as we did, you should not make extreme predictions like "He will be a star."

Unobstructed access to facts can produce unlimited good only if it is matched by the desire and ability to find out what they mean and where they lead.

Till facts are grouped & called there can be no prediction. The only advantage of discovering laws is to foretell what will happen & to see bearing of scattered facts.

Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.

If you have all the research, all the ground rules, all the directives, all the data - it doesn't mean the ad is written. Then you've got to close the door and write something - that is the moment of truth which we all try to postpone as long as possible.

Finding patterns is easy in any kind of data-rich environment; that's what mediocre gamblers do. The key is in determining whether the patterns represent signal or noise

And knowing what happens on average is a good place to start. By so doing, we insulate ourselves from the tendency to build our thinking - our daily decisions, our laws, our governance - on exceptions and anomalies rather than on reality

Science values static patterns.

Being in charge of your work life doesn't mean you always move with assurance and sublime self-confidence; it means you keep moving, continuing on your own path, even when you feel shaky and uncertain.

The next darwin is more likely to be a data wonk than a naturalist wandering through an exotic landscape.

People are storytelling creatures. We like stories that go somewhere, and therefore we like trends - because trends are things that either get better or get worse, so we can either rejoice or lament. But we mistakenly depict many things as trends moving in some direction. We take the "full house" of variation in a system and try to represent it as a single number, when in fact what we should be doing is studying the variation as it expands and contracts. If you look at the history of the variation in all its complexity, then you see there's no trend.

[Sherlock Holmes:] The temptation to form premature theories upon insufficient data is the bane of our profession.

Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge: the serenity to accept the things we cannot predict, the courage to predict the things we can, and the wisdom to know the difference.

The same past data can confirm a theory and its exact opposite! If you survive until tomorrow, it could mean that either a) you are more likely to be immortal or b) that you are closer to death.

Because you have seen something doesn't mean you can explain it. Differing interpretations will always abound, even when good minds come to bear. The kernel of indisputable information is a dot in space; interpretations grow out of the desire to make this point a line, to give it direction. The directions in which it can be sent, the uses to which it can be put by a culturally, professionally, and geographically diverse society are almost without limit. The possibilities make good scientists chary.