I spent one afternoon in 2014 wandering the underground concourse stretching from Tokyo’s Shiodome to the old Shimbashi station. It took me less than half hour to get to Shimbashi station; it took one and a half hours to find my way back. I realized that I wasn’t quite as good as I had thought at throwing down my mental bread crumbs as I wandered from my hotel. I had somehow gotten turned around as they say, heading southeast when I thought I was going northwest. As I made my way through the maze, up and down escalators, reaching a point that was clearly taking me further from my destination and sometimes into dead ends, I thought about the movie Blade Runner and how much Tokyo resembled the futuristic depiction of the city in the movie. There were no flying food carts and although it was rainy it wasn’t nearly as dismal as the scenes in the movie. What reminded me of the futuristic version of the city was its density, the way the buildings were efficiently laid side by side with the pathways laid end to end between them and the constant streams of people flowing in and out of the gated train entrances; pouring down off of the streets like water flowing into a storm sewer. At 37 million people, Tokyo is the world’s largest city. It is amazing that any given time of day there are so many people walking from one place to another. Walking from the train to work, walking from work to the train, going to lunch, headed to dinner, going from point a to point b.

As humans, we spend a lot of time and energy relocating ourselves. If we want to construct a new building or start a new company we need to locate and assemble a group of people suited for the various tasks that make up the larger project at hand. Not only to we need to do this initially but this becomes a recurring activity. As our project progresses we may find that we need additional resources. We may find that some of our resources are not performing as expected and need to be replaced. These organizational activities are perhaps the greatest inefficiency in execution of our day to day endeavors. 

Machines don’t have these problems, at least not the same way humans do. Of course they break down from time to time, but in general they perform consistently. They don’t need to commute to the office every day only to return home at night. As a matter of fact in many cases they are capable of working 24 hours a day, seven days a week. In the movie Blade Runner, like many sci-fi flicks, the machines known as Replicants were in many ways superior to humans, almost flawless in their physical abilities and at least as clever. But there is another aspect that is not addressed in this film. Within certain limits, machines can be taught more efficiently than humans. For this very reason it is rather unusual  for a highly trained person to move from one career to another. The learning curve for a person to become a qualified doctor generally prohibits anyone to enter the field unless they have chosen this profession beginning at a young age. Machines on the other hand can be trained rather quickly. In fact, the learning achieved by one machine can readily be transferred to another almost immediately. This presents an opportunity for incredibly more efficient use of resources than is possible with humans. Rather than endlessly moving human resources from one city to another or back and forth between home and office, we can position machines in a geography where they will most likely be utilized and train them as needed. Of course, not all machines are created equal, it is not feasible to simply create millions of machines which can be used universally for any task we call upon them to undertake. But this is still far beyond the capabilities of how we utilize human resources today. We already do this in a useful way today. If we need to tackle a project we might download an application to our laptop which helps us do this. When we decide to become more healthy we might download the latest fitness app to our phone. We don’t go out and buy a new phone or laptop every time we want to expand its capabilities. As devices become more powerful and flexible we will see them take on more tasks in our daily life. And slowly we will begin seeing the same thing in autonomous machines. Right now this is not the case. Our more specialized devices tend to be somewhat limited in how much they can expand their capabilities, but that is changing. It is what is referred to in the industry as the convergence: the convergence of many machines to the need for relatively few.

Imagine being able to start a new project requiring one hundred human resources but instead having the option of simply resetting and configuring one hundred machines which can perform the same task as well or better – machines that don’t go home at night or on weekends, machines that don’t take a break for lunch, machines that don’t get sick when a friend comes in from out of town. Imagine a scenario where those one hundred machines all sit in a single room the size of your living room. And all of those machines can exchange ideas, learning, and capabilities almost as easily as we share a document today. Also, this exchange would not be limited to those hundred machines in the same room; machines could transfer their knowledge and experience to other machines across the globe, and beyond. What advantage would this provide to any company that took this approach? And what disadvantage would a human have applying for this job?