Artificial Intelligence Is Likely Affecting Your Life, Daily

            The use of big data to analyze media ratings and profitable markets is nothing new, but the terms of how that information is retrieved has not seemed to evolve much in recent memory.  However, with an already nearly immeasurable amount of devices capable of streaming and downloading media content, the ratings for a TV show cannot be limited any more to simply the amount of televisions that are watching a broadcast at any one time.  The amount of people streaming a show, downloading it for later viewing or mentioning it on a social media site is a vastly more complex and largely scaled data set to sift through than traditional TV ratings as we have seen up until this point.  This is where Artificial Intelligence comes in, to make sense of all this data.  According to http://recode.net/2015/12/16/bbc-uses-artificial-intelligence-to-track-down-new-audiences-for-sherlock/, the company which the BBC has hired to analyze viewer data for its show Sherlock, Parrot Analytics, has reported that the amount of data required to go over is on the order of several petabytes for this one show.              

Image credited to recode.net; specifically this article 

To better examine how large a petabyte (PB) is, it is the equivalent of 1,000,000 gigabytes, or 1,000 terabytes of information.  And this is just for one show, on one network.  The “big four” tech giants in the world, Google, Amazon, Microsoft and Facebook, are estimated to hold 1,200 PBs of information altogether, across every service they offer, according to http://www.sciencefocus.com/qa/how-many-terabytes-data-are-internet.  When we start talking about the amount of data to sift through in regards to media ratings, we start talking about data sets that are large to the point that a human, or team of well-trained statisticians, may never be able to comb through them all, much less actually boil them down into useful information for an average reader to make sense of.  Parrot Analytics, however, employs artificially intelligent agents to comb through all of this information, and low and behold, a viable, useful set of data is produced as a result.

In the article, Parrot is described as calculating what it calls a “demand rating,” which is a measurement of the interest in a specific media broadcast in a specific area of the world.  It is the result of analyzing the total social media mention that a show has, in a sense.

Truthfully, this is where the analysis of data has to go, into the hands of an artificially intelligent program to be able to make sense of it all.  In Probability and Statistics, a course taught in the Math department (MATH 315), one of the first lessons you are taught is that a list of data that is even as small as 20 statistics will look different to you when viewed in a list versus when it is made into a graph.  Students and teachers alike are only able to identify patterns on data sets when those sets are made into a visual representation.  However, when that same data is presented in a list, such as

1                     1.00015

2                     1.00016

3                     1.00099

4                     1.00127

5                     1.00019

6                     1.00018

7                     1.00017

8                     1.00003

9                     1.00019

10                 1.00053

11                 1.00137

People will be less likely to identify patterns in that data (here, the pattern is that it starts out low, then increases, then lowers back to its original state, then increases again).  The end result is that these thousands of terabytes of information result in the discovery of new markets for TV shows.  In the case of Sherlock, the unlikely market of Seoul, South Korea, proved to hold a very large number of fans for its show.  After analytics from Parrot tipped them off that they may have a large fan base in that part of the world, the BBC included the city in a promotional world tour, according to the news article this writing is based on.  The tour involved being able to get a selfie in front of a Tardis replica and being able to buy tickets to meet Benedict Cumberbatch, the actor who plays Sherlock Holmes in the series.  There were 4,000 possible tickets that could be sold, and 50,000 people physically left their homes and lined up for them in a few minutes.

To me, this confirms the suspicion that Artificial Intelligence will be not just an important tool to have in the years to come, but indispensable in terms of analyzing trends.  These kinds of numbers, 2-3 PB of information for one television show, are the result of multiple different outlets for people to express interest in a given form of media, and as time has shown us, the available outlets to express interest tend to increase exponentially.  An article from 2014 in the Wall Street Journal, http://www.wsj.com/articles/SB10001424052702303640604579296580892973264, records technology giant Cisco as saying “the number of devices connected to the Internet will swell from about 10 billion today [in 2014] to 50 billion by 2020, as wireless links spread beyond smartphones and PCs to many other kinds of devices.”  This is known as the Internet of Things, or IoT.  The data sets which we use to analyze television shows are growing, and the data which we can collect about cities and governments is increasing exponentially as well.  In this article, http://mic.com/articles/130132/this-high-tech-city-is-showing-the-rest-of-the-world-what-the-future-looks-like#.4EjQngQLF, the city of Glasgow, Scotland, is mentioned to now have sensors placed under the pavement of its streets to detect when traffic is coming, so to better time traffic lights, for example, or to allow users of a mobile app to report potholes in their neighborhood.  Crime is now tracked using technology, data is collected as to where more electricity is spent, and citizens of the city can now be given notice when it might be faster to ride a bicycle to work than drive their car.  The result of all of this information is a data set that is orders of magnitude larger than any set of information gathered in history, and it is growing rapidly.  Search algorithms set to find a proper time to go and fix a pothole, or agents designed to find a good market for a TV show are now, or soon going to be, required to analyze data sets that may soon become too large for most humans to comprehend.  A more intelligent world demands more intelligent tools to work with it, and for that, artificially intelligent programs are not only valuable, but indispensable in terms of what kind of big data sets they can look at, and just how they can affect our lives as a result.