Jobs of the Future: How to Survive the Coming Robot Revolution
Automation is here. With increasingly more connected devices, equipment and machinery and their connectedness becoming more sophisticated it’s inevitable that low-complexity jobs can be automated away. In fact, there is reason to believe that more intermediate-complexity jobs are likely going to be automated as well. This article explore where we will be the jobs of the future (for humans)?
It almost seems like everyday that we hear how Google is making progress on their automated car program. They’ve been testing more and more, putting more of their trial cars with their unique machine-learning and artificial intelligence algorithm on some fake roads to help it learn and correct it’s mistakes. It may still be a while before we see fully-automated cars on the road but we already have people being displaced by jobs.
Look at Uber.
Uber came in, seemingly out of nowhere and displaced current taxi services who were stiffiled by high regulations and barriers to entry from local taxi licences and permits. People displacing people in their jobs. It’s starting and it’s just the tip of the iceberg.
Next, we can see that Uber will have a fleet of cars and will no longer need their driver to move people from A to B. Automation is coming and this one we can see a mile away because of the long lead times to develop.
In the full automation scenario like this, by the time Uber has their fleet, GM, Tesla, Google and a myriad of other service providers will already have found a solution or partial solution in this vertical of automated vehicles. If we can do that to driving then what other complex work can also be replaced by a robot and some code?
The fact is even as close to 4 years ago, we couldn’t have imagined that a fully automated car was even possible. Now we hear about the progress being made daily and we certainly are biased to think that it’s inevitable. The sky’s the limit.
Amazon Go has also been able to effectively displace cashiers and perhaps even stock-persons in a retail setting. They’ve dreamed up a comprehensive solution where a person can walk into a store, pick up something and put it in the bag and they ring up the register simply by walking out the door. While the person was putting the items in their bag, the system of cameras, scanners, Amazon’s database of merchandise already put that on the register with the final payment being made simply by existing the store.
So I would say, these low-skill jobs such as being a cashier is on it’s way out. A driver of any kind — obsolete.
So what kind of jobs are received to be too complex or too important to automate?
In terms for jobs and the tasks required to the jobs, there are some categories that are considered too complex for automate (at this point in time anyway):
- Specialized Coaching Services (Financial Planners, Gym Trainers, Teachers)
- Specialized Health Professions (Dentist, Doctors, Optometrists, Nursing)
- Specialized Management (Management of Digital Products, Services)
The complexity comes from the ability to manage people, manage situations that involve people to produce an undetermined outcome, require emotional sensitivity.
People Still Need People
Managing people will remain a job that likely cannot be automated because it requires the manager to motivate, assess, determine the best course of action to maintain a high performing worker.
Managers require the skills to be able to negotiate, be able to navigate and most importantly be able to communicate effectively with his workers below him and the executives above him. These skills are less likely capable of being able to do so by a robot and is unlikely that these people will be found.
Those working with people are also likely to keep their jobs – those like coaches or grade school teachers are likely something very hard to replicate with a robot. How do you infer and feel emotions from the person in order to reflect the right amount of motivate to spurn action from your student or clients? These are still very complex areas to navigate where the outcome is more about the journey than the destination.
It requires work, it requires human support in order to complete and those are the jobs that will remain while most other jobs will be automated.