Robotics, the Internet of Things, Machine Learning and many other leading edge technologies are driving a wave of automation. You can check out at the supermarket using an automated terminal. Lowes recently introduced robots to help customers find what they’re looking for. Robotics is used in factories more and more. Amazon is using robots to fill orders and experimenting with drones for delivery.
It’s making some employees very nervous. How long until driverless cars replace taxi and limo drivers or the UPS guy? How many retail employees will survive the automation of in store service? Is any factory or line worker’s job safe? While many careers are under threat there are just as many which will survive well into the automated future. Here are some key categories to move into if you want to avoid replacement by the rise of the machines.
Creative & Innovative
One thing machines don’t do well and won’t do well anytime soon is match human creativity. We make leaps based on incomplete information that lead to innovative solutions to complex problems. Machine learning and 3D printing are playing a part in making innovative thinkers even more effective. In marketing, advanced analytics are helping creative thinkers build more effective marketing strategies and campaigns. 3D printing is allowing for rapid prototyping. That makes the process of iterating through product ideas a faster leading to a designer arriving at a hit faster.
Writers, film makers, singers and actors aren’t going to be automated out of a job either. IBM’s Watson can play a mean game of Jeopardy but can’t write the next Avengers or make a Billboard Top 40 hit. Writers are also safe even though some content, like news, will move towards automated creation and delivery.
In the next five to ten years, the work of inventors and creative types will be made a lot easier by the rise of the machines. This will open the field to more people. Now’s a good time to hone your creativity in preparation for the future.
The Department of Defense has put together a policy that prohibits an autonomous system from using lethal force without intervention of an actual person. This type of policy is soon to be repeated across job functions that we’re not ready to turn over to machines. Police, fire and medical personnel are all examples of places we want people making the final calls.
Their jobs will be made safer and more accurate by machine learning and robotics. People in harm’s way like firefighters and police offices will be using robots in high risk situations. Doctors will have not only robotic systems aiding in treatments like surgery but advanced analytics to help with diagnosis and record keeping.
Politicians also look safe from being replaced by machines although they’ll have more information than ever before. Systems to help them get reelected, understand the needs of their constituents and the long term impacts of their policy decisions are already deployed or under construction.
Teachers are also not going anywhere. Machine learning systems will allow educators to better understand how effective their teaching methods are. It will also provide recommendations about how to tailor their lessons to individual learning pace and preferences.
Someone has to program the machine learning systems and build the robots. Right now that’s a select few with specialized skills. However that’s changing. Tools are getting better and the education needed to build autonomous systems is being worked into many curriculums. When it comes to college education, the rise of the machines may have saved higher education from extinction. That’s because the combination of math and engineering necessary to be an automation engineer is still best taught by universities.
Leading Edge Careers
The leading edge of any field will always be between 3 to 5 years away from automation. It takes time to synthesize the new methodologies in an accurate way and bring the costs of automation down to a sensible level. In highly technical fields like biology, the automation curve can be even longer. No matter what field you are in now, if you’re on the cutting edge and can stay there, you’ll always have a job.
As the pace of progress speeds up, that’s a harder and harder prospect. Machine learning is also working to solve that problem. Machines are allowing us to better understand how we learn by combing through mountains of data and finding patterns of effective teaching methods. Machines are learning how we learn so we can learn faster by using the right learning methods.
The leading edge of any field will continue to require adaptable, quick to learn people with high end skills.
Entrepreneurs & Founders
AI’s and robots don’t found companies. They don’t get investors to put their money behind a concept. They don’t build a team around their vision. They can’t build a business from ground 0 but they can make it easier to do and put it within reach of more people.
Everyone has seen a product make it to market that they thought about years earlier. With advanced predictive models we can test those ideas for viability without risking time and capital. These same models can match venture capitalists with founders and early stage startups making raising money a lot easier. Crowdfunding is another source of capital that the rise of the machines is putting in front of founders. The venture model’s biggest threat is the ability for customers interested in new product ideas to connect directly with and invest in entrepreneurs.
While machines won’t be founding businesses, they’ll make building one easier. The role of the founder and small business owner isn’t going anywhere.
The Personal Touch Becomes a Luxury
I’ve been hearing a lot of discussion about personal service as a luxury item or status symbol. As machines become more prevalent in the service world, luxury retailers may use people as a differentiator. Luxury hotels will have people to check you in rather than automated kiosks. A high end car dealership may still provide people as part of the sales and service experience.
Excellent customer service is an area people will excel over machines for a long time to come. As automation becomes more common, human interaction will become more expensive and be relegated to luxury status. While machines can predict peoples’ needs, their levels of accuracy are pitiful in real time interactions. Customer service will suffer huge losses from the rise of the machines but luxury service will benefit from it. If you’re in a service field, it’s time to investigate a career at Cartier or the Ritz-Carlton.
The Bottom Line – People Adding Value to Automation
The real trend in the future of work is careers where people add value to automation. What many people do today is ripe for automation. This is the great fear of the rise of the machines. However I don’t see the dystopian future many others are predicting with massive unemployment.
While the 90’s and early 2000’s have been about doing more with less in the workplace I see the next 20 years being about doing more with more. When I think about the number of trivial things people have to do every day, those that are truly beneath a human’s intelligence it’s almost offensive. Why do baristas at Starbucks have to take my order? That could be automated in a dozen different ways. What would that free them up to do? How about giving them the freedom to make me the perfect drink; a drink that’s personalized to my tastes at the moment based on a rich dataset about my pallet and their creative talent.
There are hundreds of ways that freeing a person from repetitive, mindless tasks will give them the ability to do something more extraordinary. That’s the future of work I see. Rather than making us redundant, I see the rise of the machines freeing us to do more important tasks.
Vineet Vashishta is the founder of V-Squared Consulting, a leading edge data science services company. He has spent the last 20 years in retail/eComm, gaming, hospitality, and finance building the teams,infrastructure and capabilities behind some of the most advanced analytics companies in the US.
You can follow him on Twitter: @V_Vashishta.