How can a company that combines AI with consumers respect your privacy?
Big Data
Today’s world is an increasingly messy clutter of information. The sheer mass of data that every connected person on the planet uses and creates what tech experts and industry leaders have labelled Big Data. Though the term’s meaning is fuzzy and still debated, it typically refers to a mass sum of data.
Everything you do online leaves a data trail, from chatting on Facebook Messenger to using a debit card (to buy that fourth pair of shoes that I totally needed). Much of that data ends up in databases in cloud storage or local servers controlled by e-commerce or search engine sites.
The Data Pool
Imagine Big Data as a giant swimming pool, and every water molecule is a piece of data. Every organization has their own swimming pool with their own data. In the last 30 years, Big Data as a term and a measure of data has exploded. To put that into perspective, Walmart conducts more than 1 million customer transactions every hour, and the data taken from those is estimated to be around 2,560 terabytes — the equivalent of 167 times the total information of the Library of Congress.
Since people are more connected than ever, and the popular switch from local server storage to cloud storage, Big Data is more important than ever.
Here’s why.
Predicting Patterns
Companies are constantly developing new ways to use this unwieldy mass of data.
The term Big Data is associated with the predictive analytics used by companies like Facebook and Google, and government organizations like the IRS. Predictive analytics uses coding and statistical algorithms and models to make business decisions.
Using Data Passively
Sometimes a company’s data is solely observed. By tracking how often a single user buys and searches on a site like Amazon, the company is able to measure the level of retention they have with their customers, allowing them to make business and marketing decisions.
Actively Using Data
Other times a company’s data is used more directly. The IRS takes the mass data they receive and uses predictive analytics to sift through tax returns and find tax fraud.
Facebook Chief Executive Mark Zuckerberg has been in hot water recently because Facebook’s user data wound up in the hands of voter profiling agency Cambridge Analytica. During the 2016 presidential campaign, Facebook allowed (possibly unknowingly) the data of 87 million users to be used to create and promote targeted political advertisements. While the outcome of the election may or may not have been affected significantly by Cambridge Analytica, it is an example of the power Big Data puts in the hands of corporations — as well as the dangers it could pose when used unethically.
Big Data and AI
Big Data is also helping tech innovators develop artificial intelligence (AI). AI and the software behind it is useless without a huge amount of data. An autonomous car uses cameras to view surroundings, which is turned into data that is used to dictate the movements of the car. This AI can become predictive and answer questions based on statistics and probability, like the IBM Watson machine.
(AI is a really complex topic. This article does a great job of explaining it in a simple way.)
Additionally, Big Data strategies often leverage interactions between devices to transfer data and learn from larger samples of user data. Tesla does this with their current vehicles — collecting data from their entire fleet and analyzing it to predict mechanical and software issues and preemptively update their customer cars’ operating systems.
Predictions like this are only possible with very large amounts of data — hence the seemingly endless drive towards a more connected world — with a lot more data being transferred from isolated devices to large databases.
Originally Published at medium.com
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