Privacy vs Profits: Navigating data, ethics & the age of AI

We’ve all heard it at some point: data is the new oil. Every internet user is a node in a gigantic network designed to collect, process, analyse, and monetise data. Artificial intelligence is the culmination of this project to understand people and how we use the web: an unimaginably complex statistical calculator, fed with our data to help and understand us.

On the upside, this data – and the AI created with it – helps us complete tasks at work, and helps businesses operate more efficiently (although we’ll probably still need plenty of people with a masters in financial planning). On the other hand, it requires mass collection of information about our online behaviour and characteristics and might have serious impacts on the structure of the economy. The ethical implications are vast and complex, but one thing is for sure – the times, they are a-changin’.

Every time you click a link, every purchase you make, and every time you interact on social media, you leave behind a digital footprint. Small and almost meaningless in isolation, but together with millions like it, it’s a meaningful signal that can help inform the behaviour of corporations and governments. Whether it’s an algorithm collecting data on you individually to pick which ads to show you, a political candidate figuring out whether or not you’re a potential voter, or artificial intelligence learning to understand human behaviour, someone, somewhere can derive value from just about anything you do online…as part of a larger data set, of course.

For this information to be useful, it has to be collected en masse. This creates serious ethical concerns for all parties involved. As internet users, we should have a right to know what kind of data these companies are collecting on us. We provide consent for this data collection every time we use a free service powered by ads, or whenever we click “accept cookies” when we visit a website – we should all be aware of our participation in the data economy. But these “micro-agreements” add up to something that isn’t always easy to comprehend when all we see are complicated user agreements and buttons for accepting cookies.

This broader amalgamation of data – about us as individuals and as part of every calculable demographic we might belong to – and what it has the potential to be used for is not necessarily obvious, even to a particularly fastidious individual who bothers to read user agreements and website terms and conditions. Public education on this subject by governments, media, and companies employing these techniques is vital for this business model to function without corporations acquiring an undesirable amount of power – knowledge is power, and today, data is knowledge.

The ethical dilemmas don’t end with consumer privacy. Big Data and AI are using resources at an unprecedented clip, and have the potential to massively remake our economy in ways that won’t necessarily benefit everyone. This presents corporate executives with difficult decisions that could affect the future of society or even that of our planet.

Collecting data isn’t free, either in terms of money or the resources required to perform all of the complex computational calculations and operations required to collect such massive amounts of data. Datacenters worldwide consume as much as 340TWh, or up to 1% of global electricity demand. It doesn’t sound like much, but when we need to cut carbon emissions by 45% within the next 6 years to meet Paris Accord targets, things like personalised product ads and political campaigns start sounding like great candidates for the chopping block. AI is projected to increase that number by up to half% by 2027.

But it’s not just energy we’re losing – jobs are set to suffer, too. As much as 5% of all jobs and 20% of all work currently done by humans can currently be automated, and that number will only increase as AI advances improve the quality of automation and increase the types of tasks that can be done by machines. Nearly every white-collar job will be disrupted by AI in some way, and many blue-collar jobs, including truck drivers, can be replaced outright.

As ominous as this all sounds, more people higher up the food chain would probably have grown a conscience and started calling for serious regulations if this apparent ethical dilemma didn’t have real, practical benefits. Sure, we get free services like YouTube and Facebook in exchange for our data, but if it was all just a ruse to distract us while our corporate overlords gradually accrued enough data and computing power to create an omniscient AI that enslaved us all, someone at Google would probably blow the whistle.

So what’s the real deal? What do we get out of this aside from cat pics and video chats with grandma?

The reality is, data is incredibly valuable – not just for accruing power and training hypothetically sentient superbeings, but also for much more practical, mundane purposes. Understanding viewing and buying habits helps corporations make decisions about what to invest in, which products to design and produce, and how to plan for the future. After all, every penny wasted on a product that nobody wanted can be saved if the companies building these products can know what we, as consumers, really want before they make it – and that means saving the resources that money would have been spent to procure.

It’s not just about pinching pennies: the broader benefits for communities and the environment are incalculable. Every year, Australians throw away 7.6 million tonnes of food. This isn’t just people leaving a loaf of bread on the counter for a week – grocery stores throw away massive amounts of expired produce and packaged food every day. With better data, grocery chains and their distributors can more accurately predict the demands of their customers, allowing them to better allocate food stocks and reduce production when necessary. That means not only less food wasted but also less petrol processing and transporting that food. And this is just one example.

Perhaps the most promising application of big data is the one we’ve been hearing so much about lately: AI. AGI, or artificial general intelligence, is often defined as an AI that equals or surpasses human intelligence in its capacity to think abstractly and generate unique solutions to complex problems. With the surge in progress in more advanced AI systems that’s been made public in recent years, it’s no surprise that the industry is attracting a substantial amount of attention and investment.

We’ve all become very accustomed to what AI researchers and scientists might call “narrow AI” – computer programs designed to solve specific sets of problems. One could call something as mundane as Google Search a narrow AI – it’s just a computer program that is good at one specific thing: searching the internet for the things you ask it for.

A true AGI is considered by many to be the holy grail of computer science: the ultimate tool that will make everybody more intelligent, productive, and satisfied with life. After all, if we had unlimited intelligence at our fingertips, is there anything we couldn’t do? If we could solve high-level problems like nuclear fusion, mass production of graphene and other sustainable materials, or the design of pharmaceuticals to cure any disease, or even aging…it’s almost breathtaking to imagine what a beautiful future that kind of power could help us to build. Do we even need to worry about jobs if we have the potential to unlock unlimited productivity that could benefit all of humanity?

For better or for worse, the possibilities of the data economy are almost limitless. Regarding the impact of AI and Big Data on our daily lives, only one thing is certain – things will never be quite the same.