Going to the robots: a shift of workforce

     People sometimes say that we are "going to the dogs" -- well, I would say that we are really "going to the robots". Robots were named in 1920 by the Czech playwright, Karel Čapek, within his hit play "R.U.R" -- or Rossums UniversalRobots. The word robota initially was used to indicate servitude or forced labor. So, in accordance with the original usage, there are quite a few humans who would qualify. Within the play, the manufactured robots were described as soulless humans -- manufactured biological creatures without access to feelings or independent thoughts.
     Current usage applies to non-living mechanisms (with in-betweens of Cyborg and Android). In the past, it has been primarily used for non-living mechanisms which retain the general shape and capabilities of living humans. It has now expanded to mechanical reproduction of actions previously only possible by humans -- "robot arms", ATMs (replace bank tellers), self-check counters (replace cashiers), "humanoid" (adjuncts to healthcare, services -- huge future potential), and so forth. Robots are classified in various ways -- methods of movement, category of use, versatility (programmed for one use, capable of multiple uses, or adaptive (AI)), and others.
     Leaving out definitions of Artificial Intelligence (AI) and potential challenges therein, there are many consequences of a shift of labor to robots. By definition, a robot capable of performing a human duty, or action, displaces the human -- the human is no longer needed for this duty. However, the robot needs to be designed, built, programmed, and maintained. One can put together formulas of sorts. (#Robots * useful lifetime) replace workers (net negative of workers). (#people needed for design, building, programming, and maintenance * time needed) required by robots (net positive of workers). Design, building, and programming takes a finite (limited -- it stops at some point) amount of time and the efforts during that time may create a large number of robots. Maintenance is ongoing but one person might take care of dozens, or even hundreds, or robots.
     The final effect is that robots replace workers but require more highly skilled people for a smaller amount of time. This means that, as robotization of society occurs, people will need more and more education and technical and focused training. And, for each specific number of robots put into the workplace, fewer people are needed for support activities. The more robots, the fewer (but more highly educated and trained) people needed.
     This type of shift of workers occurred in the "Industrial Revolution" (mid 1700s to mid 1800s). Very early robots such as automated looms displaced traditional weavers from their professions. In response, there were riots which were stopped with considerable violence. Eventually, workers learned new trades and shifted up in education to take new roles which developed.
     This same shift will be needed for the new "robotic revolution". Greater amounts of education and training for people but, since fewer people will be needed to attain the same results, fewer hours of work per person. This could conceivably iterate (the process continues with additional, more highly educated, workers displaced) until one has a similar situation as posed by Isaac Asimov in The Naked Sun, where there are plantations of robots with isolated humans having few required tasks.
     I am not ready to anticipate robot plantations as of yet. But, we may very well be entering into a period where active labor is done by fewer and fewer people with higher levels of education and training. If so, there will be a strong need of greater emphasis (and availability and affordability) on continued education, more deliberate labor policy oriented at reducing the number of work hours per worker, and methods of distributing savings and benefits across the entire labor pool.

Controlled falling: how to teach a robot to walk

     Every part of growing up is a miracle in its own way. However, if you happen to be an engineer or a computer scientist, you may find yourself looking at your child in a somewhat different way than most parents. Every act is a matter of "how did they do that?" Or, a matter of "I didn't know they couldn't do that originally".
     Learning to walk is a gradual process. The first part is a matter of figuring out just how to control those wonderful muscles on purpose. For fortunate babies, they have a working nervous system and all of the appropriate muscles are there but that doesn't mean that they pop out into the world ready to do a 100-yard dash. Think of a control room with hundreds, or thousands, of unlabelled switches -- each of which cause a muscle to respond in some way. How do we use an electrical switch box which has lots of unlabelled switches? Try them out and see what they do. (And then, perhaps, label them after we notice their effects.) For a robot, this is a bit simpler as there is a specific control register (or bit within a register) that causes a specific servo-motor to work.
     Now that the child knows what muscle connects to each impulse (and I am not going to try to pretend that I know just how this really takes effect), she (or he) has to practice. This may entail kicking dad in the face a few times and laughing or hitting brother in the nose. Strength is developed as the muscles are exercised. And a special sense (not always fully present in autistic children and others) called "proprioception" starts to be better known. Proprioception is also sometimes known as "body sense" or "kinesthetic awareness". No matter what you want to call it -- it allows us to know just where our body parts are. Is my finger extended? Is my leg bent? This is important if we want to apply the right muscle at the right time.
     For a robot, this has to be done in different ways (although, once again, I do not claim to know just how body sense works within a human). One dominant method is to keep track of relative position. This works like the cursor on a screen -- when the system is powered on, a specific point is considered "home" position and the cursor is moved relative to that position. The same can be done with any servo-mechanism between the limits of its movement. However, it must start at a known location and there cannot be any exterior limit on the movement (which would cause a need for recalibration). Other methods are possible but require more active sensors (and, thus, are more expensive).
     Two more requirements exist for easy movement. These are the ability to know how hard a muscle is pushing against something (the floor, for example) and how fast it is moving. The human nervous system makes use of tactile feedback to determine how hard the muscle is straining and the body sense to know how fast it is going. With a robot, a feedback loop using torque measurement may allow the robotic arm to hold an egg -- or to crush it. Speed is determined by the rate of change of movement -- how fast position changes versus and internal clock.
     With these four aspects -- ability to move, knowing where the parts are, knowledge of amount of force, and knowledge of speed -- coordinated movement is possible. Early programming of robots tried to imitate the specific movements of human muscles within their ranges of motion. It is possible to do it this way provided that there is complete control of the environment. Nothing in the wrong place, no unexpected alterations in the footing or the locations of other relevant objects. Consider a factory line with fully repetitious movement and behaviors (until a part sticks or parts run out or a dog runs into the factory ... or) and one can relatively easily see a robot taking over the factory job. In fact, many of the jobs taken over so far have been of this nature. 100% replacement is not possible because of the many exceptions that can take place and which requires more flexibility to handle -- but a considerable reduction in human staff is possible.
     But we were talking about walking weren't we? Could we use the same methodical programming to teach a robot to walk? Barely possible but, once again, only within a highly controlled environment.
     Imagine that child learning to walk. They stretch. They pull. They start becoming caterpillars on the carpet while they both strengthen and practice their muscles. Finally, they pull themselves up. And fall down. And go up. And fall down. Then they are able to stay standing up -- but hanging on. Then they let go. And fall down. And so on.
     This is a type of programming -- but not "linear" programming. This is not "do A, followed by B and then C". It isn't even exception-handling programming "do A, followed by B, then D if condition C else do E". This is neural programming. Sequences are attempted and then, based on results, discarded or modified or increased. A goal has been set and if enough sequences are tried then, at some point, success will be reached.
     Note that a new item has now been added -- a goal. In order to have a goal there must be a way to determine if you have reached that goal. For a child that is emulating other people who are walking. For a robot, it is necessary to have goals that can be specifically quantified -- expressed as numbers -- against precise targets. For walking that might be obtaining a certain height, directional velocity, and stability. Note that balance, for a human, is obtained by the feedback from the inner ear. Tools, such as gyroscopes, are available to both help maintain, and recognize loss of, stability. Laser positioning devices can be used to indicate height. Global Positioning System (GPS) information can be used for large-scale movement for direction and a combination of position and speed tracking can be used for shorter distance velocity calculations. I am sure that other tools also exist.
     For a child, they see others walk -- and those others encourage them (and protect and guide) -- and they go through a seemingly never-ended process of trial and error. They train parts of their brain and nervous system such that the thought "walk" indicates a complex series of changes, movements, and activities. I shudder to think of trying to program that linearly.
     A robot can learn in the same manner but they have to have ALL of the correct tools -- servo-motors, proper range of motion, torque feedback, auto-recognition, or storage (with its likelihood of losing calibration), of movement, and so forth. As long as they have a goal against they can match their efforts, they can keep trying combinations until they succeed. However, there is a "secondary" aspect of this type of learning -- to keep the "winning" processes and discard the "losing" processes. Humans do this (in some way that I cannot explain) but robots have to do it also. In many ways this is even more difficult because it is unlikely that the next attempt will be EXACTLY like the one in which they previously "won".
     As a note, other types of activities can be approached in the same manner -- trial and error measured against a goal. But the less physical the more difficult the definition of the goal.
     #robotics,#AI,#NeuralProgramming

Artificial Intelligence: Beyond the Turing test

     In 1950, the British mathematician Alan Turing gave an answer to the question -- how can you tell if a machine is intelligent? His (paraphrased) response was "if you cannot tell the difference between a human answering questions and a machine answering questions then it has achieved intelligence". This Turing Test is not universally accepted but it is probably the most widely used foundation of answering the question of what is Artificial Intelligence (AI).
     Alan Turing's test was based on the idea of an interviewer and a responder. Someone asks a question and someone answers a question. This led to a series of experiments in computer programs that simulated (or imitated) "normal" human interviewer/questioner situations. It might be between a therapist and patient or doctor and patient or a student and professor/teacher. Naturally, there had to be a way to make it impossible to physically tell whether it was a machine or not. It also had, built into the test, the requirement of equivalent skill in understanding and speaking/responding in a human language.
     In today's world, computer programs have advanced beyond simple questions and answers. We have computer programs beating humans in Chess, and Go, (and other games). The Turing Test might not be considered to apply to these situations but many people would consider this a form of AI. We have computer program/systems that make use of pattern recognition to identify potential suspects or targets of drones. So far, the final decision is still made by humans but stories/films such as The Minority Report indicate a possibility of the machines making final decisions even about what might happen.
     That is the "line in the sand" for people thinking about AI. Who makes the final decisions? Is it a human (with all of her, or his, faults and experience) or a machine (who, at heart, is still the results of a programmer's abilities and recognition of exceptions)? Isaac Asimov, in his Three Laws of Robotics, had the AI programming include self-restraints as to what the program/robot could do, or could not do, without undergoing self-destruction.
     Speed and safety. The primary reason for computer programs is NOT that they can do things that humans cannot do; the primary reason is that they do things much, much, faster (and reproducibly). So, if you design an AI that handles the coordination and operation of a nuclear reactor, you want the program to be able to respond very quickly. Putting a human into the decision path slows everything down. Who has the final responsibility?
     The same question exists within the possibility of self-driving automobiles and trucks. It is likely that AI programs can already drive as well as an average driver -- assuming that all of their sensors work properly (they can detect objects and highway lines and sounds and bouncing balls and the cars and buildings around them, ...). Certainly, in another five or ten years, AI self-driving programs will be able to control a vehicle much safer (and more rationally -- no road rage potential) than humans. But they would be making the final decision.
     If a self-driving AI makes a mistake or a necessary decision that costs lives, who has the responsibility? The programmer? The company that built the vehicle? The owner of the vehicle? What happens if the self-driving car is involved in an accident with a human-driven car? Is there presumption of innocence on the part of the self-driving car?
     In all these cases, the program and machine are taking the place of the human. If you keep them "behind the curtain" there may be no way to identify whether they are human or machine. They PASS the Turing Test. But, when the curtain is removed, what is the final verdict? Who/what has the responsibility? Who/what makes the final decision?

The Luddite effect -- when the new does not transition the old

    In the eighteenth and nineteenth centuries in London, as part of the "Industrial Revolution", a group of workers in the textile industry started gathering together to fight against technical replacements for their labor. Their fear was based in reality. The textile industry in England was a large one within which a considerable portion of the workers earned their living. A mechanized loom might replace the manual efforts of dozens of women and men.
    Similar to the situations that often exist today, these people were hard-working and had developed their skills over their lifetimes and, sometimes literally overnight, there was no longer any market for those skills. The response -- a losing battle -- was to destroy machines, make threats to those who were instigating the changes, and disrupt the ability for the new factories to produce. Some historical accounts indicate that the leaders of the workers recognized that there was no way to defeat the change but wanted better leverage to provide retraining and support of the unemployed.
    Government response was primarily organized around protecting the new factories, their owners, and products. Severe laws were passed and a number of "show trials" were held with death or penal transportation/exile as potential penalties. These laws, in effect, did succeed in breaking the movement.
    Other areas of skilled labor were also displaced within the context of the Industrial Revolution. Although history books usually focus on the improved ability to manufacture goods (and decrease of prices for the average consumer), they do not often indicate the huge labor displacement which was a direct effect of the change.
    The Luddites provide a practical history lesson. Change is difficult for societies to adopt and it is particularly hard on those who have invested much time and effort on the old. If change is to happen (and it is difficult to avoid it) then the process of moving away from the old must be kept in mind.
    There are a number of changes currently going on in current times. One is semi-involuntary, one is semi-voluntary, and another is fully voluntary.
    Climate change is semi-involuntary. This is because it was probably avoidable but made difficult to avoid because of inertia of old methods of business. Although there is still the chance to make the change less severe, it has already made significant changes to the world. The Great Barrier Reef is close-to-death largely because of the increase in global water temperature. The glaciers continue to shrink around the world -- this is especially important in the Asian subcontinent where winter storage of water in snowpacks and glaciers provide water to billions of people. "100-year-floods" and "100-year-storms" are occurring more often as the water temperature rises.
    A semi-voluntary area of change is the shift from non-renewable energy sources. Since the change has to be encouraged, and pushed for, it falls into the voluntary category. It is reaching the tipping point where it is almost easier to use new, renewable, energy sources than to keep using the old ones. However, just as happened in the textile industry, it is very important to recognize, and assist, the people and families dedicated to the old energy systems. Solar panel factories located at old coal mines to allow easier transitions?
    A full voluntary area of change is the strong push towards greater and greater independent automation. Phones get smaller and more powerful. Robots can take over more manual labor in a programmable fashion (as opposed to dedicated design such as in the textile mills). Innovation and extensive education becomes more and more necessary for general job positions.
    Whether voluntary, involuntary, or a mixture of such, change requires preparation and assistance in moving from the old. The is a necessity for the change and, when it is forgotten, much suffering can occur as well as rebellion (isolated or global).
    What happens to the old when the new comes? This is an age old question but, with more rapid change comes the need to actively address the needs for migration, retraining, and restructuring.

Jazz and Laughter: participation makes the difference

    Have you ever been in a room, talking with someone in a quiet corner, when a sudden noise comes from another section of the room? There is another group of people over there and they are very animated and the noise bursts out again. It is someone laughing -- and others in the group are joining them and obviously having an enjoyable time. Yet that noise, even once it is recognized as someone laughing, may not sound that pleasant. Some laughs are called "lilting" or other pleasant references but others are sometimes compared to sounds of other animals or objects in collision.

    Whether the sound, at a distance, is pleasant or unpleasant, it can still be considered very appropriate within a group who are all participating in the interaction together. It is this participation that lowers the guards, and criteria, and allows everyone to relax into a mutual experience. If you hear it from a distance -- not as part of the group -- it is a noise. If you are part of the experience it melds into the overall situation.

    It is not always necessary to be with the group in order to participate. In the above case, you are unlikely to be able to hear and see what is going on without being among the others. In the case of music, it is often a degree of intensity. In order to immerse in the music, it is necessary to be able to hear it properly. That may mean being in a quiet room, with other quiet people, so that all of the sound can be noticed, listened to, examined, and felt.

    On the other hand, it is just as valid of an experience of music to be in the midst of an explosion of sound and people and participate in the emotions of the fellow concertgoers and the movements of the band -- in spite of the fact that it may be so loud that the notes can no longer be distinguished from each other. In the one case, it is the music that is experienced and, in the other, it is the experience that is set to music.

    Jazz is an interesting juxtaposition of music and experience. A jazz piece, even when played by the same group of musicians, is not expected to sound the same twice in a row. The variation expands further when it is played by a different gathering. Although a spectator may not be directly singing or playing an instrument they have to be an active participant to fully take part. There are factors of anticipation -- what will happen next -- and surprise -- not expecting what did happen. The music will flex according to the weather and the internal needs of the players and the audience.

    There has been much speculation about whether robots could ever "replace" a human. Alan Turing presented what is called the "Turing Test" which says that if you are separated from a computer that can give responses -- so you have no direct knowledge of whether it is a computer or not -- and a human cannot tell whether or not it is a computer giving responses then it "passes". It is truly Artificial Intelligence.

    I would submit that an even better test would require the AI to be able to participate within a set of people and know when to laugh.

    What activities come to mind when you think of a need to be an active participant?