Tomorrow’s jobs: 7 future roles that will exist in the age of automation

Forget Skynet gaining sentience and starting a nuclear apocalypse aimed at humanity. The real fear a lot of folks have about artificial intelligence, robots and other automated processes is what it means for all of our jobs. According to a famous Oxford University study, around 47% of currently existing jobs could potentially be automated away within the next 15 years. Terrifying, right?

But there’s good news as well. While it’s inarguable that a certain number of jobs will vanish in the wake of automation, lots of new jobs are going to be created by technology as well. Jobs like data analyst, machine learning scientist, process automation specialists and digital marketing experts are all roles that we’re going to see a whole lot more of in the decades to come.

However, while undeniably important, all of these roles already exist in a reasonably well-established manner. Saying “well, there will be more of them” isn’t all that compelling. Instead, for this list, we’re focusing on the roles that either don’t exist right now, or exist in small quantities, which will offer real careers in the future.

Here are seven of your possible future modes of employment. Start writing your CVs now!

Augmented reality architect

Darqi Smart Glasses
DARQI

How does designing buildings or cityscapes change in an age of automation? Most likely, very significantly. While virtual reality (VR) means imagining entirely new virtual worlds, augmented reality (AR) means finding interesting ways to have virtual elements integrated within real environments.

AR is already being used as a tool by designers to pre-imagine completed works before they’re finished constructions. Examples include the likes of the design tool Morpholio AR Sketchwalk and the DAQRI Smart Helmet.

But as AR advances, our cities, offices and homes will become an amazing mix of both virtual and real elements for reasons that range from aesthetics like amazing AR sculptures and reality-defying features to more functional integrations that provide new ways of interacting with our surroundings.

Who will design these incredible AR constructions? Simple: augmented reality architects, of course.

Cyber city analyst

Talking of the cities of the future, it’s no secret that automation is going to mean smarter cities. A constant flow of data, relating to assets, external factors like weather, and individual citizens, will need to be analyzed, serviced, maintained and massaged so that it can be put to work in the most useful way possible. And don’t forget the constant stream of cyber-attacks that could bring everything to a grinding halt in a second.

Cyber city analysts will play a crucial role in ensuring that our future cities run smoothly. This role exists to a limited extent already. However, it’s only come to become more important in the smart cities of tomorrow.

Urban farming

Iron Ox Automated farming
Iron Ox

Farming was an industry which used to be a whole lot bigger. In 1820, more than half of the United States population lived and worked on farms. Today, that figure is fewer than 2%, as more and more people have moved to the city. But, weirdly, farming may be coming back into its own. Urban farming, that is.

Tackling the problem of limited free land in cities, the last few years have seen a big uptick in interest in farming in places like rooftops, warehouses and underground bunkers. Using hydroponic technology, it’s possible to perfectly control the growing conditions of a wide variety of plants, such as herbs and other produce.

Companies like Iron Ox (founded by a pair of former Google engineers) has managed to automate away some of the physical labor involved, but this is nonetheless set to be a growing industry. No pun intended.

Communicator

This is a bit of a broad one. But it’s crucial to point out, particularly if you’re not someone who wants to be working closely with technology every day.

In an essay titled “Why Are There Still So Many Jobs? The History and Future of Workplace Automation,” MIT’s professor of economics David Autor pointed out a weird thing about the rise of ATMs and the number of bank tellers employed in banks. As the number of bank tellers quadrupled between 1995 and 2010, you might assume the number of tellers diminished. In fact, Autor found that it increased the demand for tellers by making these branches more viable.

Unlike previous tellers, however, Autor wrote that these workers have become a part of something called “relationship banking.” That means not being a checkout clerk, but forging relationships with customers and introducing them to additional banking services like credit cards, loans, and investment products. A similar thing will be true for other fields.

Being able to communicate effectively has always been important. But as more and more of the mundane work-based tasks are taken by machine, similar skills will rise in prominence. It’s a great illustration of how machines and humans can interact in the workplace. Of course, if you’re someone who can interface with both humans and machines…

Data-driven life coaches

Everything from the speed that you read books to your heart rate to your fitness and exercise regimens are already being captured by machine. Think how much more data is going to be gathered by smart devices in the coming years. A.I. means this data can be analyzed in interesting ways. Relationships between, say, your diet and your mood can be discovered and highlighted to users in the form of pop-up messages.

But sometimes you need encouragement from other humans. This is one of the reasons that, despite a boom in fitness tracking technology, lots of people will still go to a personal trainer. Particularly if we’re trying to achieve something (lose weight, gain weight, learn a certain skill) a human’s “soft skills” like communication can be important in helping to push us.

While these roles already exist, however, the ability to combine those soft skills with the hard skills of data analysis is a market certain enterprising individuals will need to take advantage of.

Robot dispatcher

Self-driving cars are looking for 100% autonomy, thereby taking humans out of the loop altogether. But the same isn’t true for robot delivery drivers. For instance, Starship Technologies’ fleet of delivery robots are capable of driving themselves, but have a human watching at all times. This person isn’t physically on-site, and may not even be in the same country as the robot they’re overseeing, but they’re there nonetheless.

Should a problem arise, the operators watching each delivery (who may be overseeing 100 robots at a time) can step in to remotely take command. A similar thing is likely to happen with drone deliveries. While there’s been a whole lot of interesting research involving autonomous drones, drone deliveries will initially need human pilots and, after that, human co-pilots. Once a certain benchmark in efficiency is reached, it seems likely that drones will be capable of flying their missions with full autonomy.

But the requirement for a drone dispatcher will still be there. This job will involve monitoring whole packs of drones as they perform tasks. With online deliveries only becoming more important, it’s likely that this job will be a common one.

Artificial artificial intelligence assistant

No, you didn’t misread that. We really did mean artificial artificial intelligence. As the example of drone dispatcher shows, there are still plenty of ways in which humans have to be involved in the process of making machines that act smartly. If you’ve ever helped train an A.I. by answering an online CAPTCHA, you’ll know that human intelligence is needed to make machines get more intelligence.

Twitter, for instance, uses humans for a role called “judges.” These judges have to interpret the meaning of different search terms which trend. This is because humans understand oblique references more easily than machines do. Helping improve these systems by plugging in the necessary human qualities, whether this is done invisibly or as part of a more explicit “curated by people” approach, is going to be highly necessary.

As machines get smarter, these “Mechanical Turk” roles will no doubt change form. But, hopefully, as A.I. gets better, the specialist demands of Mechanical Turk tasks (help a computer learn X or Y) will increase — and reimbursement will improve as a result.

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