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Big Data: the future face of information

Data has exploded in recent years, but can we use it wisely?

Big Data: the future face of information

Are machines better than us at making decisions? It has been argued that, as the amount of data goes up, the importance of human judgment will go down.

Over the past two decades, we have seen massive advances in artificial intelligence and machine learning, from Deep Blue beating Garry Kasparov at chess in 1997 to IBM’s Watson supercomputer winning the US game show Jeopardy. We’ve even heard Stephen Hawking say that "AI could spell the end of the human race".

You only have to watch the Hollywood movie Ex Machina to get an idea of what that looks like as the machines go rogue, utilising big data to render an unpleasant judgment on humanity.

So what is big data? Well it’s big, there is lots of it and it’s highly individualised, unstructured and often available in real time. For instance, every minute in 2014 humans sent 240m emails, made 4m search queries, posted 2.5m pieces of content on Facebook and uploaded 72 hours of content on YouTube. Google’s Eric Schmidt said: "There were five exabytes of information created between the dawn of civilisation through 2003. That much information is now created every two days."

With that explosion in data, we have seen the increasing power of predictive analytics, which has helped elect presidents, discover new energy sources, score consumer credit, detect fraud, target prospective buyers and even tell you which movie you’re likely to watch next.

With Moore’s law driving exponential advances in processing power, we can see the use of predictive analytics being more creative and efficient than ever before.

But big data is not everything. It gives us context and correlations for understanding human behaviours, but it rarely tells us why people behave this way. There’s also the problem of interpretation. As MIT’s Kate Crawford said: "Biases and blind spots exist in big data as much as they do in individual perceptions and experiences."

Take the case of Google’s Flu Trends, which demonstrably failed to predict flu trends and spurred Google to warn of "big-data hubris" in which companies give too much weight to analyses whose flaws only come to light through experience.

Meaning vs machine

At Mindshare we believe that the future communications agency will have a data culture, and the core competency will be analytics. It will be a place where human expertise and AI converge to make sense of data in the marketing world. A place where machines don’t replace humans but rather rely on them to translate patterns and behaviours into information that can change the world for the better. A place where we use insights generated from the data to create valuable and meaningful connections between people and brands.

To quote the American statistician Nate Silver: "The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning. Before we demand more of data, we need to demand more of ourselves."

So when it comes to human versus machine, we believe big data is fantastic but its potential can only be realised by people. Humans are still making most of the important decisions in marketing.

David Walsh is chief business officer at Mindshare

Main photo by r2hox, under a Creative Commons Attribution-ShareAlike 2.0 Generic license

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