Big Data and Trayvon Martin

Few things have divided this nation to the extent that the Trayvon Martin case has. While some believe racial profiling was the root cause of Trayvon’s death, others believe that race was not the reason Trayvon Martin caught George Zimmerman’s attention on the night of February 26, 2012. Despite these different viewpoints, there are some things we can all agree on. George Zimmerman, after observing some unknown set of characteristics about Trayvon Martin, made at two key decisions about Trayvon. George Zimmerman decided:

1. Who Trayvon was (a person who belongs vs. a person who doesn’t, youth with in hoodie, etc)
2. What Trayvon might do (passing through vs up to no good)

This set of characteristics was likely based on George’s past knowledge and experience with other people with similar characteristics (be they race-based or not). This set of characteristics probably included an analysis of Trayvon’s visible behavior at the time – how he walked, what he was looking at, etc. All of this data, both directly and indirectly tied to Trayvon, played a part in George Zimmerman’s decision to follow him. As we all know, Zimmerman’s decision was a key factor in the end result, which was Trayvon Martin’s death.

What does all of this have to do with Big Data?

We are in the early stages of Big Data – the mass storage and analysis of huge amounts of data for the purpose of correlating human behavior. Beyond simply using data to understand what people have done, statistical analysis of Big Data is being used to predict future behavior. We see evidence of this in things as simple as product recommendations on sites like Amazon.com, and movie recommendations from Netflix. Examples of predictive algorithms also exist in the physical world. Superstore retailer Target uses online customer identifiers and cash register information to link consumers web habits with what they buy in store. That information is used to determine what sales promotions and mailings each customer receives. To get a better idea of Target’s Big Data analytics abilities, read the NY Times article on “The Target Baby” (link). From online giants like Facebook & Google, down to brick and mortar bureaucracies like the NYC Housing authority, major companies and governments are collecting and analyzing large amounts of behavior data about all of us for the sake determine when, where, how, and to whom certain products and resources should (or shouldn’t) be offered. From their perspective, the more data they can collect, the more accurate their algorithms will be.

While the fact that these algorithms drive efficiency and productivity has been well documented, there is another outcome that is less obvious. All of us – each and every one of us, are increasingly being evaluated and judged by a set of behavioral characteristics.

Just like Trayvon Martin.

And in the eyes those looking at us, the data collected is complete enough to accurately sum up who we are.

While the output of these Big Data algorithms may not determine whether we get shot or not, their impact may be equally as life threatening. Algorithms will increasingly determine what services are available to us, what jobs we are considered for, and how we live in both the online and physical worlds.

There are already start-ups that use a person’s Facebook social graph to predict that person’s credit score.

The key question is does that split second decision – whether it’s coming from a person watching us walk down the street, or a complex algorithmic formula – accurately sum up who we are?

And what is the happens if I choose to believe these decisions made about me?

If, from our past choices and decisions, it is possible to predict and make decisions about what we will do, what does that mean about man’s ability to change?

If the (big) data tells me there is little chance for me to change, what is the likelihood that I will believe I can change?

If I believe what Big Data tells me I am (and what I will be), is there room in my life for the redeeming power of Christ?

Lots of questions – share your thoughts in the comments!!!

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