Manna

by Marshall Brain

  In version 3.0, the software gained the ability to fire employees as well. I had a friend who got fired that way. He came into the store late for his shift, and it was his third time being late. He punched in and put on his headset. He walked over to the eye scan station to log in. He said Manna sounded normal, and had him working normally for about half an hour. Then Manna asked him to walk to Zone 7 at the back of the store. A Burger-G security guy was standing there with three sheets of paper. The security guy was wearing the solid black security uniform, the opaque sunglasses and a headset integrated into the helmet. He looked back and there was another security guy standing near the door. Manna said to him, “Steven J. Canis, employee number 4378561, your employment at Burger-G store number 152 is hereby terminated in accordance with employee manual paragraph 12.1, failure to appear at work on time.” Manna read him the three pages of termination information paragraph by paragraph and asked him to confirm each paragraph. He could not return to that Burger-G store for a year. He could not reapply to Burger-G for five years. Stuff like that. Manna made him sign the papers and the security guys escorted him out of the store to his car. The security guys never said a word, but Manna was talking to him during the entire walk, telling him to look down, to make no gestures, to speak to no one. The last thing Manna said to him was, “Remove your headset and hand it to the security officer on your left. Goodbye.”

  It didn’t take long for word to get around. Pretty much, if you knew you were going to be late and you had been late before, you called Manna on your cell phone and quit. Manna emailed the forms to you, had you phone in when you got them so it could read them to you, and you signed them. It really cut down on people being late.

  By version 4.0, Manna gained the ability to outsource. Let’s say that Manna decided it was time to repaint the lines in the parking lot. Manna would make this decision using customer surveys and by periodically asking employees questions about the parking lot, the paint inside the store, the exterior of the store, the roof, etc. An inspector from Burger-G corporate would also come once a month and feed information about the store and grounds into the Manna system.

  When Manna made the decision to repaint the stripes in the parking lot, it would call several companies and get bids. Manna did not do this on the phone, obviously. It did it electronically through the Internet. By this time, most companies were hooked into the Manna network, even if the company did not use Manna to manage employees. The two pieces of software — the Manna software running the Burger-G restaurant and the Manna software running the parking lot maintenance company — would bid and negotiate through the Internet.

  Because everything was done by machine, the restaurant’s Manna system could send out a request for bids to all the parking lot maintenance companies in the area. Those companies would send bids back through the network. The restaurant’s Manna system would then connect with hundreds of other Manna systems to check references and get feedback on past experiences with each vendor. Based on the bid prices and the feedback, Manna would select a vendor, negotiate terms, make a deposit and schedule the repainting job. The entire process from start to finish took less than 10 seconds.

  As these communication networks between all the different Manna systems built up, things started to get uncomfortable for every worker. For example, the Manna software in each store knew about employee performance in microscopic detail — how often the employee was on time or early, how quickly the employee did tasks, how quickly the employee answered the phone and responded to email, how the customers rated the employee and so on. When an employee left a store and tried to get a new job somewhere else, any other Manna system could request the employee’s performance record. If an employee had “issues” — late, slow, disorganized, unkempt — it became nearly impossible for that employee to get another job. Nearly every company with minimum wage employees used Manna software or something similar, and performance records on employees were a major commodity freely exchanged between corporations. A marginal employee got blacklisted in the system very quickly.

  That ability to blacklist employees is where things got ugly, because it gave Manna far too much power. Manna was everywhere, and it was managing about a half of the workers in the United States through headsets, cell phones and email. Manna moved in and took over a big chunk of the government as well. There came a point where tens of millions of humans did nothing at work unless told to do so by a Manna system.

  You can imagine what would happen. Manna fires you because you don’t show up for work a couple times. Now you try to go get a job somewhere else. No other Manna system is going to hire you. There had always been an implicit threat in the American economy — “if you do not have a job, you cannot make any money and you will therefore become homeless.” Manna simply took that threat and turned the screws. If you did not do what Manna told you to, it would fire you. Then you would not be able to get a job anywhere else. It gave Manna huge leverage.

  For example, Manna could call in reinforcements as it needed them. You would get a call from Manna and it would say, “Your Burger-G restaurant is experiencing unexpected customer volume. Can you help?” The word “help” meant, “Can you be here in less than 10 minutes?” You could say yes or no. The problem was that if you said “no” too many times, you got fired. And when you got fired, it meant you were blacklisted in the system.

  Once you figured that out, you were pretty much forced to say “yes”. That meant that the printed schedules started to become pretty much irrelevant. Manna would call you when it wanted to call you. Then it started calling you to other restaurants. If things got slow in the restaurant, Manna would send you home, then call you back in later if things got busy again. You really could not say “no” very often, meaning that Manna could interrupt your life at any time.

  Version 4.0 of Manna was also the first version to enforce average task times, and that was even worse. Manna would ask you to clean the restrooms. But now Manna had industry-average times for restroom cleaning stored in the software, as well as “target times”. If it took you too long to mop the floor or clean the sinks, Manna would say to you, “lagging”. When you said, “OK” to mark task completion for Manna, Manna would say, “Your time was 4 minutes 10 seconds. Industry average time is 3 minutes 30 seconds. Please focus on each task.” Anyone who lagged consistently was fired.

  At the supercenter, Brian said that Manna was now tracking how fast employees walked from point A to point B in the store, and if you did not walk fast enough Manna would warn you about it. It was just like working on an assembly line, where they could speed up the line to make people work faster. But now the assembly line was everywhere, and if you didn’t keep up you knew that you would be blacklisted nationwide.

  The most surprising part of the Manna system, however, was the effect it had on wages. As Manna spread to so many businesses, your choice was to work for Manna or to be unemployed. When you started to work for Manna, it paid you minimum wage. There was no reason for it to pay you any more — your choice was minimum wage or zero. There was no way to ask Manna for a raise. You could quit, but when you quit you would be applying to another business that used Manna. It was going to give you minimum wage too.

  This was the societal power of Manna, and the basic equation was pretty simple. You could take the job for minimum wage, or you could be unemployed making zero. At any moment Manna could replace you with another warm body, and that meant that you did what you were told for minimum wage or you got fired. Manna, and the corporations that used it, knew that that was the equation. There were plenty of unemployed people who would take your spot as soon as you left.

  The effect of Manna was to stratify out all the minimum wage workers in America. At the bottom you had the people who were unemployable. They had screwed up and been blacklisted by Manna. They were back living with their parents or sleeping on the sofa with a friend. You could get yourself un-blacklisted, but if you got blacklisted more than a couple times, you were dead.
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  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 coc
kpit 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 university research team created a machine able to process 10 quadrillion operations per second on 100 trillion bytes of RAM. They had created a $500,000 machine with processing power approaching that of a human brain. With that much processing power and memory on tap, the researchers were finally able to start creating real vision processing algorithms.

  Within a year they had two demonstration projects that got a lot of media attention. The first was an autonomous humanoid robot that, given an apartment number, could walk through a city, find the building, ride the elevator or walk up the steps and knock on that apartment door. The second was a car that could drive itself door-to-door in rush hour traffic without any human intervention. By combining the walking robot and the self-driving car, the researchers demonstrated a completely robotic delivery system for a pizza restaurant. In a widely reported publicity stunt, the research team ordered a pizza and had it delivered by robot to their lab 25 minutes later.

  A network of 1,000 video game consoles was not exactly portable, so the demonstration robots that this research team created did not have the brain on-board. The robots talked to the system through wireless connections. However, this research team had proven that machine vision was possible and workable in some of the most complex and real-world tasks imaginable.