In Big Data: A Revolution That Will Transform How We Live, Work, and Think, you’ll learn about how information is changing, how that impacts how we understand ourselves and go about our day-to-day lives, and the implications for our privacy and ethics now and in the near future.
“As recently as 2000, only a quarter of the stored information in the world was digital. The other three-quarters were on paper, film, vinyl LP records, magnetic cassette tapes, and the like…in 2013 the amount of stored information in the world is estimated to be around 1,200 exabytes, of which less than 2 percent is non-digital.”
“Big Data” doesn’t only mean the amount of available information, although volume is a component. The main difference between traditional uses of information and big data analysis is that big data uses ALL of the information and looks at it in innovative ways to find new connections and teach us new things.
For example, the CDC uses information traditionally to figure out what is happening every winter with the flu. But since they have to wait for reports from doctors and hospitals, and they only use a sample size of the data they get, their results are delayed by several weeks behind where the outbreaks occur. Google, on the other hand, used it’s huge amount of data to figure out what searches people do online when they have the flu, and was able to track and predict the course of the flu in near real time.
This does highlight one difference between traditional uses of information and big data: big data doesn’t show causality, just correlation. That is, it tells us what but not why. Although we sacrifice some detail and specificity, we gain broader insights and can make connections never possible before.
A downside is that anonymity is virtually impossible with big data. No matter how you try to anonymize it, by it’s comprehensive nature, big data means crossing information and gives the ability to drill down into characteristics that makes privacy a huge concern. Even now, half of all US states use big data to assess a person’s fitness for parole, and credit rating companies are looking into how your Facebook friends can predict your credit worthiness. Since big data comes from sources you wouldn’t expect, even seemingly innocuous things like your electricity use, it can reveal a lot of personal information about your daily behavior, health conditions, and activities that could be used against you. You might not be worried about coming up for parole, but presumably using information in a predictive fashion to impact things like whether or not you get a job, insurance, or the best interest rates would impact most people.
I thought the book did a good job addressing the ethical implications of big data, although more in a “here is a potential issue” than a “here is a potential solution” way. It seems like I’ve been running into a lot of books that raise the issues of ethics and morality in a rapidly changing world, but very few that actually advance concrete suggestions for how to move forward. I wonder if any philosophers are working on this, or if they are all still sort of caught up in the problems of the past decades.
Don’t let the technical-sounding title of Big Data deter you – the book is highly readable and has implications for how all of us will live and interact in the very near future. These issues bear thinking about before they become acute problems, and I’d recommend Big Data as a good start.
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