There’s no doubt that A. I. and other tech is going to change the face of employment as we know it. According to one famous study, 47 percent of currently existing jobs in America are at high risk of potential automation in the coming decades. Here are 10 jobs at particular risk.
There’s no doubt that artificial intelligence (A. I.) and other cutting edge technologies are going to change the face of employment as we know it. According to one famous study, 47 percent of currently existing jobs in America are at high risk of potential automation in the coming decades.
What are some of the professions that will suffer the effects of the A. I. revolution? And is there anything people can hope to do about it? Read on to find out.
Why they’re screwed: Judging from the number of movies and TV shows about the profession, being a lawyer is a pretty great job: an interesting, high-earning career with bags of social status attached. However, hiring a lawyer is also expensive and a substantial portion of what lawyers do on a daily basis turns out to be a lot more routinized than some in the profession would have you believe.
While genuinely bespoke legal work still requires humans, A. I. can help perform tasks ranging from legal discovery (the pre-trial process in which lawyers decide which documents are relevant to a case) to creating contracts. They can even argue parking fines and handle divorce proceedings.
So there’s no hope? Junior lawyer jobs may be harder to come by than ever, but studying a combination of law and computer science could be extremely fulfilling. Whether it’s advising on how best to turn laws into algorithms or investigating the legal framework around new technologies like self-driving cars, there are plenty of interesting opportunities available.
Why they’re screwed: Think of adjectives to describe a data entry job and, chances are, a word like “repetitive” and “dull” might spring to mind. Given the enormous amount of data that’s generated by companies and individuals, the job category of data entry clerk won’t be going anywhere.
But the idea that a company needs to pay a human an hourly wage to transfer data from one format to another, or compile it into one place — and probably get a few (potentially crucial) typos thrown in there for good measure? Yeah, this job’s not sticking around for humans!
So there’s no hope? Where there’s still a job in existence, there’s hope that you can be the one to take advantage of it. As we mentioned, the importance of data accumulation is only going to get more important.
If you can add skills to your professional résumé to perhaps oversee the machines doing the data entry, or embracing the data science part of the job, you could turn a disappearing job into a more highly paid promotion.
Why they’re screwed: An algorithm could never write a listicle as compelling as this one, right? Guess again! Whether it’s using bots to generate sports reports and other news articles or attempts to use A. I. for more in-depth investigative journalism, there’s plenty to suggest that journalism isn’t safe from the clutches of artificial intelligence.
Heck, combine advances in computational creativity and text generation with the sorry financial state of many media companies and the results don’t add up to anything approaching optimistic for wordsmiths.
So there’s no hope? A. I. doesn’t have to be your enemy. As it turns out, bots could be the hired researcher human journalists always dreamed of, with the ability to pull up statistics and unearth interesting patterns in data which can lead to entirely new ways of telling and presenting stories.
In the future, there’s also the possibility that A. I. automated agents could be used to help personalize human-written stories for readers, based on their knowledge, location, age, or reading level. Doing so could expose human writers’ work to even larger audiences.
Why they’re screwed: In a chapter from their 2004 book, The New Division of Labor, MIT and Harvard economists Frank Levy and Richard Murnane argued that a computer would never be able to drive a car, due to the enormous complexity of information involved with this task.
Today, we know that is categorically false, due to the thousands of miles successfully driven by self-driving cars. Fleets of autonomous vehicles owned by companies like Uber will have an enormous impact on professional human taxi drivers, while autonomous trucks will mean the same thing for long-distance drivers.
Things don’t look too hot for driving instructors either. After all, will kids born in 2018 even need to pass a driving test?
So there’s no hope? Based on the response to Uber in some major cities like London, human cab drivers may be able to resist the threat of self-driving cars for a short time. Sad as it is to say, however, human drivers should probably think about reskilling.
Why they’re screwed: Considering that they need cooling fans at the best of times, working in a hot kitchen sounds like a terrible idea for a computer. But A. I. is always ready to surprise us. One example of a chef robot was created using IBM’s Watson technology. Called Chef Watson, it’s able to generate entirely new recipes from scratch using an astonishing knowledge of taste chemistry and flavor pairings.
Meanwhile, robots like Miso Robotics’ burger-preparing Flippy are capable of preparing meals and serving them up at speeds that human chefs struggle to achieve. Add table delivery drones into the mix and you don’t even need human waiters to deliver the food to customers.
So there’s no hope? As with a lot of areas, humans who are ready to take advantage of the technology stand to benefit. If you’re a chef, you could conceivably use robots to churn out identical dishes to your specifications in greater quantities than you yourself could cook.
Using technologies like 3D food printing will also make possible the creation of entirely new dishes that would have been previously unimaginable.
Why they’re screwed: Like being a lawyer, working in the finance sector has traditionally been a high status, high income job. However, increasingly A. I. is taking over. Computers can spot patterns and make trades faster than even the most eagle-eyed of human analysts.
With billions of dollars (or more) at stake, it’s no wonder that machine learning tools are all the rage, while some estimates suggest that around 30 percent of banking sector jobs will be lost to A. I. within the next decade.
So there’s no hope? There will be fewer jobs, but there are certainly opportunities. So-called “quants” who are able to combine knowledge of the financial sector with computer science and math are highly sought after to help develop the algorithms which increasingly drive this field.
Elsewhere, the importance of “relationship banking” to help build up customer loyalty and provide personalized service will continue to grow.
Why they’re screwed: Chatbots are getting way smarter, as tools like Google Home and Amazon’s Alexa show us. That doesn’t bode well for a lot of telemarketers and phone-based customer service assistants, who are often speaking according to a script.
With miserable conversion rates for direct telephone sales and fewer people willing to wait customer service assistants to become available, smart chatbots can perform a lot of these tools admirably. That’s not good for people working in this field, who have already been hit by the outsourcing of many of these jobs to people in other countries like India.
So there’s no hope? Not necessarily. One A. I. company, Mattersight, uses voice recognition technology to figure out the personality type of customer service line callers and patch them through to humans with a similar personality type.
