This article is essentially an overview of one of the directions that math is going in today's world. It focuses on how applied math is becoming increasingly valuable in the world of computer sciences and virtual analysis. Today, those programmers who can write the best algorithms or mine the most crucial data from the internet and its vast quantity of 'unstructured data,' are becoming increasingly valuable. Programs that sift through thousands of blogs, articles, advertisements, etc., and can quantify their results in a way that can create profit are not only becoming more numerous but also more accurate and because of that, more valuable. Because there is such a host of information on the web, the algorithms that are able to pick out useful patterns and tendencies are becoming the new '.com's' of our world. And the people who are math savvy are being increasingly rewarded both monetarily and with power and position.
Beyond that, there was a huge emphasis on humans being transformed into points on a graph. Our behavior, race, achievements, socioeconomic status, and anything else that can be seen as an essential character brick, are being transformed into a statistic on a chart.
“The clearest example of math's disruptive power is in advertising. There Google and other search companies built on math are turning an industry that grew on ideas, hunches, and personal relationships into a series of calculations...Rising flows of data give companies the intelligence to home in on the individual customer. Internet marketers are the natural leaders, but traditional businesses are following suit. Gary W. Loveman, CEO of casino giant Harrah's Entertainment Inc. () and a former Harvard B-school professor, has led the company to build individual profiles of millions of Harrah's customers. The models include gamblers' ages, gender, and Zip codes, as well as the amount of time they spent gambling and how much they won or lost. These data enable Harrah's to study gambling through a host of variables and to target individuals with offers, from getaway weekends to gourmet dining, calculated to maximize returns. In the last five years, Harrah's has averaged 22% annual growth, and its stock has nearly tripled...[Another company scans the web for articles and blogs and] breaks down English messages into the smallest components -- words, phrases, grammar, even emotions -- and turns them into math.” (3-4)
Essentially, that which has been reserved for the qualitative side of analysis is now being analyzed quantitatively.
When I first read this, I was somewhat disturbed. "What right does some algorithm have to turn me into math?! What a gross violation of my humanity!," I thought. But then I realized that if these companies are finding ways to successfully analyze things that have so long been considered subjective, then maybe this isn't a case of the proverbial David getting squashed by Goliath. It's not as if these programmers are making things up about me, they are doing nothing other than analyzing what is already there. And what's so horrible about that? Well, this is where I'm split.
Mystery has always been an essential part of the human experience. Not knowing everything about the present and future has allowed for creativity to flourish and exploration thrive. But, if said mystery is reduced to a margin of triviality, then maybe the exploratory drive that has propelled humanity through the ages will be replaced by a sequential system with the sole goal of profit, eliminating many creative freedoms we now enjoy today. But, on the other hand, maybe they won't be. Maybe computer programs will never be able to map the impetuousness of human nature, and will simply allow us to explore more efficiently, with a more defined direction and with greater success.
But as of now, I'm torn, which will it be?
Quotes cited:
http://www.math.uiuc.edu/MSS/2006-Spring/MathWillRockYourWorld.pdf
Posts
Once again your alter ego, dammitimgood, has won over here. This is a nice post. I enjoyed your leading questions at the end. Normally I find leading questions as a annoying and sly way to get out of a real conclusion, leaving readers back to square one. This is not the case for your post. You have a stated conclusion and keep the reader thinking even after the conclusion of your post. My only other comment is that a few sentences at the beggining are rather long and wordy. Yet, I too have a tendency to do the same. Overall a greatly written post.
ReplyDeletemc Casper
Dammitimmad,
ReplyDeleteYou make some interesting points in this post. I was particularly interested by your thoughts on the move towards quantitative analysis. You write that "But then I realized that if these companies are finding ways to successfully analyze things that have so long been considered subjective". As a graduate student learning to conduct educational research in math education, I think a lot about the values of quantitative vs. qualitative analyses. I think it is easy to view quantitative methods as objective, but I'm learning that it is often not the case. How we decide to "measure" something and turn it into numbers in itself is a subjective process that involves the biases of the researchers.
Do you think that human beings can truly be quantified? For example, I can use a student's math SAT score as a measure of his or her mathematics knowledge, but is that a true measure of his or ability to do math? I don't believe so. I don't think it captures a student's ability to problem solve, communicate about mathematics, and work collaboratively.
I guess what I'm learning is that the best research uses both quantitative and qualitative methods to develop a richer description.
Thanks for your thoughts!
SKS
Great point Sarah. I hadn't considered that quantitative analysis comes from a qualitative standpoint. Very interesting. I think I am going to have to take the middle ground here.
ReplyDeleteFor example, I do not think that there is anything wrong with quantifying students based on their SAT scores, as long as it is perfectly clear that the you are not summing up the student's entire math skill set, and that it is just one (uber lame) test that you are looking at.
I guess what I'm going for is that regardless of the quantitative analysis, it must always be clear the reference and data being analyzed, and that they are just a collection of specific facts pointing to a possible application in the real world.
Thanks!