Where should we draw the line with data analytics, asks Aditi Udayabhaskar
We know all too well the spiral of a YouTube spree – just one video, you think, until you find yourself watching advertisements on Brennan’s bread some two hours later thinking, how did I get here? Yep, we can all relate. Whilst this is a great way to procrastinate, it also is a subtle way for someone out there to create a digital profile of who you are – but more importantly, what you like.
You might think watching Sherlock on Netflix or adding Barry’s tea to your Tesco cart are completely random things you do, as they should be. But could these innocent actions actually be translated into something more?
Big data – that’s where your binge-watching and shopping preferences land up. Everyone’s talking about it; the media, politicians, Silicon Valley giants, everybody. People have given the term different names: artificial intelligence, data analytics, even machine learning. Whilst these don’t technically mean the same things, these words allow for a simplified and more accessible terminology that the common man can easily understand. Where was big data earlier? With processing power having increased multifold in recent years, companies can now run through larger amounts of data quicker than ever before. This finally allowed companies to actually harness the terabytes of data they store today. But what is so ‘big’ about big data, you may ask? And what exactly is it?
All of our online activity generates data, which each company stores in a data warehouse.
Instead of having this data just sit around and do nothing, companies are turning to algorithms that can find patterns in the data and help predict attributes or features about their users, to enable higher profits and increase efficiency.
This is best explained at Google – your searches online, the newsletters you’ve signed up for on Gmail, your subscribed channels on YouTube and usage of Maps to help you navigate – this information gives techies at Google plenty to get started on your virtual footprint.
Think about it: they already know where you live (thanks to Maps), they know what you like (thanks to Gmail) and also what you are interested in (thanks to the search engine). While for you Google is just a service that helps you get things done efficiently and for free, your information is a goldmine for a company that can use this data to target specific adverts, companies or videos at you. And if they get this right, it could mean millions of dollars in commission fees from marketing agencies, multinationals or simply anyone who wants to sell their product on Google.
Of course, big data is also a blessing – we mustn’t be too quick to forget the many benefits of analytics either. Be it reading your beautifully personalised news magazine on Flipboard sipping your morning coffee or getting sent vouchers you can actually redeem at Tesco through your Clubcard, the effect data mining has had on our personal lives may be small, yet significant.
Medical startups that use machine learning algorithms to predict whether patients have cancerous tumours are on the rise, and with improved technology and accessibility, this could mean more affordable healthcare for the masses.
Airbnb is another good one – using user preferences to find you an affordable home in a city of your choice – and enhance your travel experience. The possibilities are quite frankly limitless, and there is plenty of potential to use analytics to make the world a truly better place.
All the same, ideas that begin with a very simple premise can unintentionally lead to undesirable consequences. What do I mean? Where Uber is making our commute easier, it’s leaving our jolly-good traditional taxi drivers out of a job. As Enlitic keeps tweaking its algorithm to ensure it outdoes doctors to identify and treat cancer, we may see a decline in people wishing to join the healthcare profession. If Elon Musk and Co. succeed in making self-driving cars a reality, we may seriously need to ask the question: is nothing sacred?
Sure, automated driving may seem utopic and straight out of a sci-fi movie, but how much is too much? With analytics taking the world by storm and nothing seeming to be too big of a challenge, are we as a human race on the verge of decapitating our own society? If we let artificial intelligence take over everything from healthcare to driving, humanity will be left out of a job – and humanity will be responsible for it. We must maximise the glorious, and limit the disastrous. The key is striking the right balance – with the increasingly blurring boundaries between the two, this is easier said than done.
Today, the road forks into two paths – the first, a possible utopia; the other, a self-destructive society. Big data can be both. Which do you choose? The answer to that will write the destiny of the human race.