Data Sets Quotes

In the future, I think movies are going to be more of data sets that viewers have a hand in controlling - where the narrative originates and what happens to the content.

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.

Big data is mostly about taking numbers and using those numbers to make predictions about the future. The bigger the data set you have, the more accurate the predictions about the future will be.

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.

Data will always bear the marks of its history. That is human history held in those data sets.

Big data sets are never complete.

What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units - the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging - free-form labeling, without regard to categorical constraints - seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.

I might take from the current political chaos a desire to somehow reflect its essential qualities in a story - the blatant lies that get accepted with repetition; the way mass media seems to be agitating people en masse; the way, particularly, that a relatively lucky and affluent and privileged population can be undone by a certain spoiled quality; that feeling when two decent people violently disagree, because they are arguing from two non-intersecting data sets - well, the list goes on.

Artificial intelligence is just a new tool, one that can be used for good and for bad purposes and one that comes with new dangers and downsides as well. We know already that although machine learning has huge potential, data sets with ingrained biases will produce biased results - garbage in, garbage out.

While massive datasets may feel very abstract, they are intricately linked to physical place and human culture. And places, like people, have their own individual character and grain.

Every day we have teams looking for new data sets.

As we get more transparent with data sets about infrastructure and systems management, I have a feeling we'll see big changes in how we think about complexity and our relationship to our actions.

AIs are only as good as the data they are trained on.