Data is the new oil

Economists have been claiming for a while that data is now a more valuable commodity than oil. I first heard this quote during a Netflix movie (The Great Hack) about the Cambridge Analytica role in the 2016 presidential elections. Regardless of what you think about the ethics of it all, it raised an interesting point about how valuable data has become. Not just our personal data but all forms of it.

As someone who has built data-driven startups (Infopia, Yovia, MEC Labs, Robauto) I can testify first-hand that data is an incredibly valuable commodity. Whether or not it’s more or less valuable than oil – I can’t really say. They don’t totally compare.

What I can say, however, is that data is the key to artificial intelligence. A common dialogue around the data discussion has to do with the privacy and tracking of consumers. Quickly, people start looking at companies like Google and Facebook, who seemingly track and create experiences for us based on our behavior. The answer is that they do 100% track our behavior and use it to optimize their revenues and provide a more tailored experience. Your like, share and search data trains their software to give you a better experience.

This is nothing new. Supermarkets have been tracking your behavior for years. Loyalty programs tie your in-store behavior to purchases to maximize profits. This isn’t some covert attempt to learn more about us – this is their job. A retail store’s goal is to make money and it’s really useful to look at data and adjust. Computers use data sets to try to pre-train themselves so more data is better. In the case of the Netflix show the premise was that it was a system of posts, social events, and even physical groups that were perpetrated by targeting a subset of the population that the algorithm had shown as being easily to influence.

The data is what drives machine learning. Without data, underlying algorithms don’t work. They need lots and lots of data. From robots to IoT devices to web advertising, data is what feeds the proverbial machines.

The example of Cambridge Analytica using data is extreme. In the Netflix documentary, they supposedly had a weapons-grade software algorithm that used questionably obtained Facebook user data to create more than 5,000 data points around every voter in America. They then used that data to figure out how to influence people who were undecided in the 2016 elections by sending them targeted candidate propaganda. I  personally find that a little invasive and not at all transparent but it’s not new, particularly in advertising.

We can argue whether or not it is ethical or if it is more or less valuable than something like oil, but the fact of the matter is this:

With a sample of less than 0.06% of the world’s Facebook data, Cambridge Analytica was able to help sway an election. That’s all it took for their algorithm to identify who to reach and what to say to them to influence their vote.

The show depicts their efforts coming into the public spotlight when the Trump campaign won in an upset and it was revealed that this organization had been swinging elections for years. It was their business, and they were good at it. Perhaps they went too far and I can’t really comment on the ethics of it other than I would never want to use technology for something so…? and I don’t know people who do. It seems like an unhelpful way to use data but it illustrates the point of its potential value.

Tesla is an example of a company using data. You can say what you want about their products or the company or the stock price, but Tesla has a huge advantage in that their underlying artificial intelligence – the self-driving software – has already been fed millions of miles of live driving data.

This gives the algorithm an advantage over someone who maybe has a great vehicle and software platform – but no data to train it.

Nobody really knows what the future holds for technology, but one thing for sure – your own personal data may become one of your most valuable assets. Ironically, your human input is what brings these technologies to life and for the most part, we all willingly feed it.

Remember Stats? Machine Learning is set to take over.