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You are searching the internet for a new archery bow. You find the perfect one, but it’s too expensive. With reluctance you close the tab and return to Facebook. Your newsfeed refreshes. “No, it can’t be!” you think, astounded. The very bow you were just looking at has appeared in the advert column to the right of your page. “Is this a sign?” you ponder. You feel something strange on your head. You look in the mirror. It’s a candy red apple and you realise, “This is not a sign, this is data fuelled marketing and I’ve just become the target.”

Every time you Google an image, shop online, log into your email or click an advertisement you create something; that something is data. On its own the 2.5 quintillion bytes worth of data created daily seems like an overwhelming ocean of useless information that you are sure to drown in. However, thanks to Dan Steinberg, an entrepreneurial scientist who provided the bow that is machine learning, this informational data is now analysed and used to predict the wants of individuals. Machines learning from data unleashes the power of these two singularly harmless resources, combining them to create a high velocity marketing weapon. A weapon that according to Siegel (2013) “... uncovers what drives people and the actions they take” to predict which customer will buy/buy into their product or service and henceforth provide them with some form of corporate gain. To most, data seems like a drab result of our time spent on the internet, however, each click is identifying information about ourselves, creating a virtual version to be ridiculed and exploited by the machine learning process.

Perhaps this colourless interpretation of the process is due to the nature in which our ‘digitally native’ society has been influenced to accept the way it has no control over the arrows they produce and who becomes targeted.

Along with the evolution of this machine learning process that enables targeted marketing, is the evolution of the number of platforms this data is allowing us be targeted on. Society is now encouraged by one platform to utilise another in order to achieve something. For example, whilst watching television you may be encouraged to tweet your opinion on Twitter for the opportunity to see your Tweet on screen as is the case with Big Brother Australia. The amount of Tweets selected to be on-screen are few, though Big Brother is essentially harnessing the power of the crowd to advertise for them at virtually no cost other than the data they have already bought that tells them exactly how to inspire you to do so. This vicious circle only continues as the data you create by participating tells them information regarding your age, gender and location and how successful they are at swindling you.

Data is created by you and everyday internet users who have little (if any) access to and no control over the way the fruits of their labour is used. Maybe this doesn’t seem like such a bad occurrence, perhaps this is society’s way of paying the pied piper for the use of his services, right? That may have been the case if equal access were provided to the population of the product the crowd has created. However, the commercial hierarchy behind 72% of websites have lucrative privacy policies that allow third parties (the highest bidders) to track internet activity which, in an efficiency driven society, few would spend the time to read (The Economist, 2012). This means efforts of the crowd is being exploited and furthermore, forced to relinquish both privacy and control over what they see when browsing. Corporate entities aren’t just targeting you with un-nocked bows, they are using your own arrows to do it; encouraging a new media consumerism of content.

Ultimately, the rich get richer and you get duped into standing under the apple.

Shayla Girdler ( http://shaylagirdkcb206.tumblr.com/ )

References

Siegel, Eric, (2013). Introduction : The Prediction Effect. In Siegel, Eric, Predictive analytics : the power to predict who will click, buy, lie, or die, (pp.1 - 16). Hoboken, NJ: Wiley.

You are searching the internet for a new archery bow. You find the perfect one, but it’s too expensive. With reluctance you close the tab and return to Facebook. Your newsfeed refreshes. “No, it can’t be!” you think, astounded. The very bow you were just looking at has appeared in the advert column to the right of your page. “Is this a sign?” you ponder. You feel something strange on your head. You look in the mirror. It’s a candy red apple and you realise, “This is not a sign, this is data fuelled marketing and I’ve just become the target.”

Every time you Google an image, shop online, log into your email or click an advertisement you create something; that something is data. On its own the 2.5 quintillion bytes worth of data created daily seems like an overwhelming ocean of useless information that you are sure to drown in. However, thanks to Dan Steinberg, an entrepreneurial scientist who provided the bow that is machine learning, this informational data is now analysed and used to predict the wants of individuals. Machines learning from data unleashes the power of these two singularly harmless resources, combining them to create a high velocity marketing weapon. A weapon that according to Siegel (2013) “... uncovers what drives people and the actions they take” to predict which customer will buy/buy into their product or service and henceforth provide them with some form of corporate gain. To most, data seems like a drab result of our time spent on the internet, however, each click is identifying information about ourselves, creating a virtual version to be ridiculed and exploited by the machine learning process.

Perhaps this colourless interpretation of the process is due to the nature in which our ‘digitally native’ society has been influenced to accept the way it has no control over the arrows they produce and who becomes targeted.

Along with the evolution of this machine learning process that enables targeted marketing, is the evolution of the number of platforms this data is allowing us be targeted on. Society is now encouraged by one platform to utilise another in order to achieve something. For example, whilst watching television you may be encouraged to tweet your opinion on Twitter for the opportunity to see your Tweet on screen as is the case with Big Brother Australia. The amount of Tweets selected to be on-screen are few, though Big Brother is essentially harnessing the power of the crowd to advertise for them at virtually no cost other than the data they have already bought that tells them exactly how to inspire you to do so. This vicious circle only continues as the data you create by participating tells them information regarding your age, gender and location and how successful they are at swindling you.

Data is created by you and everyday internet users who have little (if any) access to and no control over the way the fruits of their labour is used. Maybe this doesn’t seem like such a bad occurrence, perhaps this is society’s way of paying the pied piper for the use of his services, right? That may have been the case if equal access were provided to the population of the product the crowd has created. However, the commercial hierarchy behind 72% of websites have lucrative privacy policies that allow third parties (the highest bidders) to track internet activity which, in an efficiency driven society, few would spend the time to read (The Economist, 2012). This means efforts of the crowd is being exploited and furthermore, forced to relinquish both privacy and control over what they see when browsing. Corporate entities aren’t just targeting you with un-nocked bows, they are using your own arrows to do it; encouraging a new media consumerism of content.

Ultimately, the rich get richer and you get duped into standing under the apple.

Shayla Girdler ( http://shaylagirdkcb206.tumblr.com/ )

References

Siegel, Eric, (2013). Introduction : The Prediction Effect. In Siegel, Eric, Predictive analytics : the power to predict who will click, buy, lie, or die, (pp.1 - 16). Hoboken, NJ: Wiley.

You’re walking resolutely through the city on a busy pathway filled with others just like you. You all have somewhere do be; you all have a goal. You’ve got your headphones in listening to music. Momentarily the music cuts out, replaced by a ‘ding!’; a text message. You focus on your phone screen as you continue walking with the flow of other pedestrians. “HOLY! Sooooo much drama went down last nite *distressed emoticon face*. BTW me and Jason r ova. TTYL xx”. While reading this message, you have become almost completely immersed in technology and have failed to realise the person in front of you has slowed their pace to a complete halt. They pull out their mobile phone, intent on taking the perfect picture of a building; you bump straight into them. You don't feel apologetic for the disruption to the other person, no body stops in the middle of a busy pathway; it isn’t the social normality.

Communication has evolved with new media technology to fit into our ‘time equals money’ society where efficiency in achieving our goals are paramount. We naturally find the simplest and fastest way to achieve our goals. For example, you want to send a message to your friend to make plans for the evening. You wouldn’t stop everything you’re doing, sit down, hand write a letter, make an envelope, walk to the nearest post-office, get a stamp, mail it, then wait around at home all day, unsure if your friend has even received the mail, let alone replied. You would send a text-message or make a phone call on your five minute lunch-break and have it arranged by the time you go back to work. So just like the people in the city scenario above, everyone has a goal they want to achieve and our techno-social society makes the ‘pathway’ simpler and more efficient to navigate. The technologies that allow us to do so provide us with tools such as ‘auto-correct’, ‘spell-check’ and the ability to communicate with more people, in more locations with more efficiency than ever. However such tools are allowing us to invest less time in constructing our messages and therefore, we are in a sense sacrificing grammatical knowledge and its importance, for efficiency. For example, your friend has misspelled ‘nite’ and ‘ova’, and stated ‘Me and Jason’, rather than ‘Jason and I’, yet you are technologically proficient, and still understand the message, so what does it matter right?

In symmetry with technologies evolution, is a language evolution which again, makes the communication pathway more efficient. Society has created a ‘short-hand’ writing style that quickens the process still; emphasising our techno-social reliance. This language evolution comes in the form of abbreviations, paralinguistic tools, fragmented words/sentences, symbols and emoticons as read in the city scenario. These linguistic tools affect the way our messages are perceived as they portray intonation, and emotion in the place of body language which would be present in face-to-face communication, though efficiently.

However, while the majority of people walk on the left side of the path and move to the side when they need to pause, some aren’t as proficient and barriers do exist. Some people misinterpret things like sarcasm, intonation and the emotion behind the message; though it says one thing, they read it to say another. People say ‘haha’ but aren’t actually laughing, misspell words for particular effect and use exclamation points when they aren't yelling. If you are not proficient with this evolved language, chances are you are in for a very inefficient conversation with your mum to explain LOL does not mean lot’s of love, and she needs to resend the message to the family about grandma’s passing.

You have a calm exterior. You text your friend back, “OMG SO ANNOYED. Stoopid tourist n their blimey photo’s. Like learn to navigate the pathway haha. BTW, soz bout you and J, TTYL bout it *kiss emoticon face* xoxo.”

Written By: Shayla Girdler (http://shaylagirdkcb206.tumblr.com/)

Reference List