On Big Data and The Internet of Things


Analytics Algorithms are all around us. A multitude of methodologies is used to record what you do both online and off. These algorithms, more often controlled by big companies or the government, work constantly to track your information, contextualize data, and weave correlations. Amidst the flow of ceaseless internet streaming and social media, a 24-hour surveillance conglomerate can be discerned. Thousands of networks tune in to our engagements, a transaction where we are the informant, reporting on our activities.

Our Orwellian world today requires a concurrence to forfeit our privacy and be monitored. Your search engine results, likes, browser history, and cookies, they’re all free game for the NSA and data brokers to make use of (yes, even your choices in porn send off alerts). The main driving force at play here is undoubtedly economic. Our digital footprints leave behind them an assembled trail of imagery, one that has become indispensable to the stability of our economy.

We choose every day to inhabit an interstitial space where money means little when we are the ultimate product. “The single mother”, “the avid traveler”, “the craft beer drinker”; mathematical processes continue in a prodigious interchange of Big Data to discern significant connections. Advertisers thrive on these connections. Our momentous change toward wanting free content has revolutionized digital marketing strategies. In an age where we would rather not pay for the latest games, apps, and streaming services; this has allowed websites to sell and invent means of exploiting our data.

Surely, you’ve been awed by what Netflix has suggested for your wish list. Or, by what song follows next on Spotify. Algorithmic methods are remarkably blueprinted to forecast our online conduct. These predictions aren’t always accurate, but a few misses matter little in comparison to the gainful interactions made in the agglomeration of data collected from user engagement.

The shroud of secrecy involved in these operations is enclosed in controversy. Out of the millions of consumer profiles retained and examined without consent by information brokers, a seemingly ferocious cycle of targeting vulnerable demographics has been observed. These algorithms have become so precise as to well surpass traditional means of consumer data mining (census, public, and motor vehicle records) and are more than capable of predicting someone’s race, economic class, and social status.

Despite the increasing awareness Americans have of this surveillance, the vast majority of our population does little to counter it and utilize helpful tools for privatizing their information. Whether out of fear or apathetic tendencies, few are not concerned enough to learn tactics such as using safer search engines or coming up with more intricate passwords. When it comes to taking even bigger steps, like finding the right system to encrypt your emails with, these options are hardly publicized. Also, uninformed to us, are software with which to access and surf the internet (Tor, being an example).

In the next five years, billions of people from developing countries are projected to enter the Internet of Things. By then, the amount of accumulated data stored online will have risen dramatically. The need for a more secure and private internet-centered world will become pivotal.

There is opportune hope for reform. Many consumers find security software difficult to implement. Companies need to strive to find ways to design digital solutions that are easier to use. On the search engine front, sites such as Duck Duck Go have enacted an emphasis on protecting user search results. In order to maintain and protect the internet, one of the most profound inventions of the 20th century, we must learn to adopt a new social contract, one which emphasizes the importance of privacy on the internet.

Photo courtesy of ALAMY.


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