Robots and automated machines have been conveniently filling jobs that humans find boring and autonomous while we implement machine learning, sensors, and artificial cognition in hopes of them being able to take on even more human jobs, alleviating the need for human labor and opening the job field so that humans can continue to self-actualize through new jobs. It’s hard to believe when you hear that 70 percent of today’s jobs will be replaced by robots by the end of the century!
Just 200 years ago, the Industrial Revolution began and left less than 1 percent of the human/animal 
workforce in lieu of implementation of automated machines. Instead of creating a large unemployable workforce, it instead allowed those workers to segue into a new workforce while making their jobs easier through use of farming machines that till or pick vegetables and machines in the assembly line to put machines together or lift heavy objects. As horses and mules were largely phased out as a workforce, humans will soon be replaced by machines that can outperform tasks without being overworked or bored. “We’re moving the unskilled jobs into skilled jobs. And that is going to be a challenge for us going forward,” says Henrik Christensen, director of the Institute for Robotics and Intelligent Machines at the Georgia Institute of Technology. “If you are unskilled labor today, you’d better start thinking about getting an education.” But soon, even lawyers and paralegals, pharmacists, store clerks, cashiers, journalists, can give benign tasks to competent machines who can easily handle their more mundane tasks of each profession, like point-of-sale checkout, filling prescriptions, or handling paperwork.
The coming quantum computer movement looks to progress real artificial intelligence in robots by honing in on the way machines learn, remember, and work so they can be adaptable to the external stimuli around them.”We employ the theory of a quantum random walk to show how an agent can explore its episodic memory in superposition to dramatically speed up its active learning time,” Martin-Delgado said. “Utilizing quantum physics to promote artificial intelligence learning has the ability to provide a quadratic increase in speed in active learning, critical when the environment changes on timescales of the ‘thinking’ time of the robot.” These robots and capabilities are being built to take on tasks that require abstract thought processes and higher knowledge. There are already computers that churn out stories and newscasting based on submitted data-and they can do it within seconds instead of hiring and expensing the means for a beat reporter to attend and write about a game.
People often repress or express the awkward uneasiness around robots, but many who are building them and working alongside them are combating the want for robots to try and be human-like, because, frankly, the “uncanny valley” that our brains take us to when we witness humanoid robots isn’t what will help robots to segue into the workplace. However, robots will eventually perform we have been doing, and do them much better than we could. They’ll do jobs we can’t do at all, and they’ll come to do jobs that we never imagined needing to be done. As we segue out of these position, we will be able to finally discover new jobs for ourselves, new tasks that expand who we are. We can teach the robots take our jobs like we did in the Industrial Revolution so we can follow the intrinsic motivation to do more work that matters to us!