This reading was divided into two parts: the collection of data and the pitfalls of Big Data. It provided a great many examples to illustrate its points, which was helpful. I felt that it was informative without being overwhelmingly so.

In the first part of the reading, the collection of data, a few things stood out to me: this history of big data, the amount of data collected, and the type of data collected.

I found the story of Matthew Fontaine Maury interesting, because he collected vast amounts of data, and from unusual sources. The datafication of journals was a brilliant idea. His work was not unlike research projects done in some classes (just on a much bigger scale). Maury’s case shows that solid research methods are important in data collection.

The sheer volume of collected data never ceases to amaze me. It’s pulled from so many different sources, and it just feels like privacy doesn’t really exist anymore, unless someone decides to completely unplug from their online existence, and even then, that person may have stopped new data from being collected, but the already-collected information is still out there.

I was boggled by what qualifies as data. Books and words? I’m a linguist: I suppose that I’ve looked at language as data for quite some time. That Facebook’s social graph involves over one billion people is astonishing.

It’s just… I’ve never thought about what parts of myself I’m surrendering by being online.

Granted, not all uses of this data are troubling, but enough are, which is what chapter eight is about.

Informed consent strikes me as important. In an ideal world, we would be able to give it, but I’m not sure we can. As data is collected and research on that data evolves, the reasons for data collection will change. This especially matters because the precautions taken to anonymize the data just simply don’t seem to work.
Does this mean that companies like Facebook should have to ask every six months or so? Or, perhaps, when a new data mining project is initiated? I don’t know. I do think the whole “Let’s just click on this privacy notice once” thing doesn’t seem to be adequate.

People are fallible, so they may decide to focus on the wrong data or analyze the data improperly.

Standardized tests in school struck a chord with me because I used to teach SAT test taking skills: I know those tests can be played. Specific techniques have been developed to raise student scores, and those techniques aren’t about information learned in schools, but, rather, information about how to approach the questions. For instance, in the math sections, “the answer cannot be determined by the information given” is almost never correct.

As a result, I don’t think we can trust the data standardized tests can provide, yet, we still see many people holding them up as proof of learning.

The potential for abuse and misuse of data is great, and we have to watch out for it. I’m not sure how. I mean, I know enough about history to know that trusting the corporations to police themselves is a huge mistake, but I don’t know how we can manage it.

This reading raised some troubling questions for me.