blacklisted more than a couple times, you were dead.
Then there were all the unemployed people. Between Manna improving efficiency and forcing out the managers, plus overseas outsourcing taking out white collar jobs, plus machines like the automated checkout lines and burger flippers coming on line and so on, there were plenty of people who were unemployed. Unemployed people went around all day applying to jobs. But in a sense, that was pointless. All of the interconnected Manna systems knew every single person in the job pool. Manna also knew the performance of every single person who had ever worked in the system. You were in an incredibly bad spot if you were unemployed.
Then there were all the people being managed by Manna. They all made minimum wage. If you were wearing a headset at work you were making minimum wage and everyone knew it. And everyone knew that if you did not do what Manna told you to do, as fast as Manna told you to do it, you would be unemployed and making nothing.
And then there was everyone else — the doctors, lawyers, accountants, office workers, executives, politicians. The executives and politicians made a ton of money and they were never going to be wearing headsets. Joe Garcia at Burger-G was making $100 million per year and flaunting it like a rock star.
And Manna was starting to move in on some of the white collar work force. The basic idea was to break every job down into a series of steps that Manna could manage. No one had ever realized it before, but just about every job had parts that could be subdivided out.
HMOs and hospitals, for example, were starting to put headsets on the doctors and surgeons. It helped lower malpractice problems by making sure that the surgeon followed every step in a surgical procedure. The hospitals could also hyper-specialize the surgeons. For example, one surgeon might do nothing but open the chest for heart surgery. Another would do the arterial grafts. Another would come in to inspect the work and close the patient back up. What this then meant, over time, was that the HMO could train technicians to do the opening and closing procedures at much lower cost. Eventually, every part of the subdivided surgery could be performed by a super-specialized technician. Manna kept every procedure on an exact track that virtually eliminated errors. Manna would schedule 5 or 10 routine surgeries at a time. Technicians would do everything, with one actual surgeon overseeing things and handling any emergencies. They all wore headsets, and Manna controlled every minute of their working lives.
That same hyper-specialization approach could apply to lots of white collar jobs. Lawyers, for example. You could take any routine legal problem and subdivide it — uncontested divorces, real estate transactions, most standard contracts, and so on. It was surprising where you started to see headsets popping up, and whenever you saw them you knew that the people were locked in, that they were working every minute of every day and that wages were falling.
A decade later I was getting out of school. I had a BA in education and a master’s degree in educational administration. My plan was to teach in high school for two or three years so that I had experience “in the trenches”, and then move into an administrative or government position. I was ready to start teaching and I was looking forward to it. Education was one area that, so far, had been largely untouched by Manna, so in that sense I was lucky. I was also lucky that there were jobs available, and I did not have a lot of problems finding an open position. That was a miracle.
My graduation year was an important year for me — I had been working at Burger-G all through school to make spending money, and now I would have my first real job free from Manna.
But it turned out to be a pivotal year for America as a whole. It was a funny coincidence. My graduation year was the year that computer vision came of age.
Chapter 3
No one really thought of the Manna software as a robot at all. To them, Manna was just a computer program running on a PC. When most normal people thought about robots, they thought about independent, autonomous, thinking robots like the ones they saw in science fiction films. C-3PO and R2-D2 were powerful robotic images, and people would not believe they were looking at a robot until robots looked like C-3PO.
The mechanical chassis for a C-3PO type robot had been around since the turn of the century. Honda did the trailblazing with its ASIMO robot, and once Honda had proven the concept many other manufacturers followed Honda’s lead. ASIMO could walk up and down stairs, kick a ball and so on, and it looked completely natural. The problem was that ASIMO needed a human operator pushing a joystick to tell it what to do.
The thing that held robots back was vision. Nearly everything a person does is aided by vision — so much so that we take vision completely for granted. But if you close your eyes and try to do anything, you realize just how important vision is.
For example, when you enter a room where the light is dim, you think in your head, “I need to turn on the lights.” You use your eyes to look on the wall for a light switch. When you find it you use your eyes to guide your hand to the switch. You then use your eyes to figure out what kind of switch it is. Is it a toggle switch? A push- button switch? A dimmer switch with a knob? A dimmer switch with a slider? None of the above? Once you figure it out, you use your eyes to guide your fingers to manipulate the switch in the appropriate way. Or maybe you look at the wall and there is no switch to be found. Now you start looking for a lamp in the room. Is it a touch lamp? Or is the switch on the base of the lamp? Maybe the switch is near the bulb, and you have to push it or twist it or pull a chain… Your vision guides you every step of the way. It is nearly impossible to do anything in a complex environment without vision. And turning on a lamp is a very simple thing. It gets a lot more complicated when you are trying to run through a forest, ride your bicycle down a busy a street or find your way to a particular address in a large subdivision.
Without vision, robots could not move around or manipulate objects. All of the other hardware was there. Legs and balance systems to allow bipedal motion had been in place for decades. Robotic fingers and hands with very fine motor control were easy to create. AI software to set goals and make decisions was getting more powerful every day. Everything was there but the vision system.
You could see that society was ready for the robots to arrive. The first real robotic system installed in a human position of trust was in the airline industry. The terrorist attack on the World Trade Center in 2001 had been a wake-up call. Then there was a run of six airline accidents, all attributed to pilot or ATC error, which made everyone nervous. Then the unthinkable happened. Two airline pilots, both sleeper agents for an Asian terrorist organization, flew their planes into massive U.S. targets almost simultaneously and killed nearly 50,000 people. One hit a basketball arena full of spectators, and the other ripped through the Democratic national convention. That was the end of human pilots in the cockpit.
As it turned out, the transition to robotic planes was remarkably easy. Airplanes were already controlled by autopilots while enroute. Radar systems on the ground and in the planes were already taking off and landing the planes automatically. An airplane did not need a vision system — its “vision” was radar, and radar had been around for more than half a century. There was also a secondary backup system that gave airplanes a form of consciousness. Airplanes could detect their exact location using GPS systems. These GPS systems were married to very detailed digital maps of the ground and the airspace over the ground. The maps told the airplane where every single building and structure was on the ground. So even if the autopilot failed and told the plane to go somewhere unsafe, a “conscious” plane would refuse to fly there. It was, quite literally, impossible for a conscious plane to fly into a building — the plane “knew” that flying into a building was “wrong.” If the autopilot went insane, the conscious plane shut it off and radioed for help. If all the engines failed or fell off, the plane knew what was on the ground in the vicinity and did its best to crash into an unpopulated area.
Soon there were no human airline pilots and no human air traffic controllers in the system. Everything about flying through the air was automated. The cockpit was stripped out of airplanes and the space became a lounge or a seating area. With human beings out of the loop, the safety record of the airline industry improved and people came to trust the airlines again. No one cared at all that there was no human pilot in the cockpit — people actually trusted machines more than human beings.
The first breakthrough in true computer vision came from a university. The newest video game consoles came out, and these consoles had extremely powerful CPUs able to process 10 trillion operations per second. By adding 100 gigabytes of RAM to the console and then networking 1,000 of these video game consoles together, a
