There are some peer reviewed academic journal available. They have in common, that the published information has a high quality and most of them have a long tradition in the classical university ecosystem. Since the advent of Open Access there is need to start new academic journals. The open question is how to combine the Open Access philosophy with a peer review pipeline.
The technical side of an Open Access journal is very easy. In most cases, it's enough to upload a pdf document to a webserver and the paper can be read by a worldwide audience. We can discuss about the details, that means which software is producing the pdf format and which sort of webspace is the right one for hosting a journal, but in general this kind of pipeline will result into a high quality journal. That means, the document can be displayed on any device, and the webserver will deliver the information to any reader in the world within seconds.
The more advanced and seldom discussed issue is how to create a peer reviewed journal. A normal Open Access journal doesn't has a peer review, but it's some sort of pdf hosting website. That means, the admin of the journal uploads the pdf file, but the paper was never read by someone before the publication. In the classical academic publication system there is some sort of prepublication peer review available which allows to increase the quality, but its unclear how to reproduce this workflow in an open Access journal.
The current situation is, that some journals are experimenting with overlay journals, open peer review system and community driven peer review. One option is that somebody is only allowed to upload a new paper if he has peer reviewed an existing one. Another option is, to ignore peer review at all and allow the normal reader to comment newly published information. This will result into some sort of arxiv website which is extended with a comment section.
A truely peer review system is working a bit different. To framework for explaining the details is located in the software industry. The git version control system has a build in peer review feature. This feature can be activated with a dual branch workflow.
But let us go a step backward. Software development with git works usually with a single branch model. In the trunk branch the changes are submitted to a remote server. A single branch workflow doesn't has a peer review. A peer review has to do with creating two branches which are out of sync. A stable branch and an unstrable branch are needed as the minimum requirement.
Peer review and merging two out of sync branches is the same. The amazing feature of merging two branches is, that it will produces a conflict in any case. This kind of conflict creates a need for the stakeholders to negotiate about the issue. This negotiation is equal to a peer review. It is very different to comment a paper from the readers perspective, because a branch merge is done in the pre-publication step.
Now it make sense to transfer this philosophy to an Open Access journal. A minimal peer reviewed open access journal contains of two sections: unstable upstream and stable downstream. In the upstream section the incoming papers are stored, very similar to the arxiv repository. In the stable downstream section, the next issue of the journal is created. The interesting point is, that the stable section doesn't referencing to the upstream section but a complete copy is created. It's the same principle like in a git version control system. The stable branch and the unstable branch can be edited independent from each other. That means, the paper in the upstream section can be modified without affecting the paper in stable section.
Peer review can be realized with a dual branch model which is out of sync. To sync the branches a negotiation is required. Negotiation means to discuss the next issue of the journal with colleagues. An interesting side effect is, that the social roles in each branches are different from each other. That means, an author is allowed to upload a paper to the upstream section, but this doesn't mean, that this paper gets published in the downstream section.
Let us create a single example. The author uploads paper1 to the upstream section of the journal. The journal editor reads the paper and comes to the conclusion that the quality is too low. He decides not to publish this paper in the next issue. It is available in the upstream section, but it doesn't get copied into the downstream section. This produces a communication conflict, because the journal editor sends a rejection notice to the original author. This sort of communication is typical for all peer reviewed journal. What is available is a conflict between different social roles of the journal. These conflicting roles are attractive for normal readers because it makes the publication system more robust against wrong information.
From a technical point of view, there are many options how to realize a dual branch system. One option is to use the github project for hosting an academic journal. A more easier to realize system is to ignore the git tool at all and store the branches in different sections of a wiki. That means, the upstream branch is section 1 and the downstream branch is section2. This allows to create a peer reviewed academic journal on a single wiki page.
Peer review
Let us describe in the context of the branch model, what peer review is about. If the Open Access journal was created with the described workflow it contains of two sections: unstable upstream and stable downstream. The interesting point is, that this outline doesn't solve problems, but it will create many new tasks. One of them is the question which of the papers should be copied into the downstream section. That means, from the perspective of the journal editor the situation is, that some papers are available in the upstream section, but it's not clear which of them will fit into the next issue of the journal.
There are more than a single option to adress this question. A naive attempt is to use a dice and decides with a random generator which of the paper fulfill the quality standards of the journal. A second more elaborated decision making strategy is, if the journal editor decides by himself which of the upstream papers is well suited. And the best practice method is, that the journal editors delegates this question to a group of peer reviewers.
Because this point is equal to peer review it make sense to describe the process in detail. The starting point is, that the journal has two sections (upstream and downstream). To copy a paper into the downstream section a decision is needed about the quality. This decision is delegated to a group of people. What the group can do in response is to peer review the paper or not. In the worst case, the journal editor doesn't find an external peer reviewer. So he has to decide by himself if the paper fulfills the need of the readers.
But even in this case, its a peer reviewed journal. Because there was a decision which was taken. The decision if a paper fulfills the standards or not is only needed in a two branch model. In a normal repository there is no need to judge about a paper.
In the software industry, the principle has a long history. In the git tool a so called branch can be created easily. Creating a branch means to copy a folder and then it's possible to edit the folder without altering the original folder. Sometimes it's called a fork. Because the same sourcecode is available at two places at the same time. The interesting point is, that after creating a branch both branches will get out of sync. That means, a user can edit branch1 and branch2 isn't affected. This principle is a very powerful one and allows to divide software development tasks into subproblems.
Branches are used in the Open Source world for many things. There are feature branches available to fix a problem, and there are stable branches available to update complete operating systems. What comes very close to a peer reviewed academic journal is a stable release linux distribution like Debian. It's the same principle. Debian is peer reviewed software, that means, the Debian ISO file is different from the debian upstream branch.
Freezing the upstream
Every open source project starts with an upstream branch. The upstream is a repository which stores the sourcecode on a server. In most cases, the upstream is equal to a github folder, but the upstream can also be located on a SVN server or a FTP server. The upstream repository allows the creator of the software to update the project. He can upload new files and alter existing one. In case of content the upstream is equal to a wordpress blog. It's a place in the internet in which information is stored.
The interesting point in open source projects is, that apart from the upstream repository a second action is needed, which is called freezing. Freezing means to convert the sourcecode in the upstream into a release which can be delivered to the normal user. The interesting point behind freezing is, that from the programmers perspective this step has a low priority. What the software authors is trying to do is to improve the software with new updates. He isn't interested in stopping this update cycles. The only one who needs a freezed stable release is the end user.
In the Linux ecosystem there is a long duration discussion available if the normal user has a need for a freeze version or if he can use a rolling release version. Rolling release means, that no freeze is available but the normal user installs the same version as provided by the upstream. The interesting point is, that rolling release was never a success for real projects. All the major software systems like Debian, Windows 10, Red Hat, Apple Mac OS and Android are delivered in a release version which is froozen. So called nightly build versions are only available as an alternative. But they are not installed on productive systems.
The reason why it make sense to analyze the Open Source development model is because the concept of freezing the upstream is available since many years and it's discussed in the literature. Its the best practice method in open source software development. The same concept can be adapted to scholarly paper writing. Freezing a paper is equal for creating a peer review. The shared principle is, that the original author of a paper isn't interested in freezing a paper. Because this is equal to loose the control over the content.
In the reality a peer review is something which is working against a paper. A peer review is desired by the readers. A peer reviewed journal communicates between authors and readers as an intermediate.
April 18, 2020
April 15, 2020
Building a modern robot from scratch
The main reason why Artificial Intelligence has failed in the past in real robotics projects is because its focused on computer science but not on the underlying domain. The untold assumption is, that np hard problems have to be solved with a certain algorithm which should be implemented in a programming language. After executing the program it will solve a certain AI problem, for example to grasp an object with a dexterous hand.
Why this assumption won't result into a grasping robot is because nobody knows how the algorithm can solve a task. In contrast to sorting an array, so called AI tasks have nothing to do with computing itself, but they have to do with driving a car, the shape of objects and communicating in natural language.
The better idea for realizing AI systems is to start with a teleoperated robot which is extended later with a database of trajectories. In the first step the human operator controls the robot arm with a joystick. This allows him to grasp an object. In the step 2 the pipeline is extend with grounded natural language and a learning from demonstration motion database. Both modules are not located in classical computer science nor mathematics but they have to do with applications of Artificial Intelligence.
Perhaps it make sense to go into the details. Suppose the human operator is able to grasp an object with a joystick. In theory, he can do so many hundred times, but the goal is to transfer the task into software for higher productivity. One important step towards this direction is to repeat the same action and record the trajectory. The result is a motion capture database. If the scene in front of the robot fits to the recorded scene the recorded action is reproduced in the playback mode. An interpolation between different trajectories will increase the accuracy.
The next step towards advanced robotics is to tag the trajectory database with grounded language. That means, the database is annotated with labels like “open gripper”, “close gripper” and “push object”. This allows to search in the database easier. For example, if the next task is about “push object”, an SQL query to the motion database will return all the trajectories from this domain. Then the solver will select some of them and creates the interpolated trajectory which is executed on the robot.
The combination of teleoperated robotics, learning from demonstration, and natural language grounding is a powerful technique to realize robotics projects which can be used in reality. That means, the system is not only an academic project to teach the students who they should do something, but the robot can be used for solving practical tasks.
The reason why this approach is nearly unknown in mainstream robotics and AI has to do because its easy and very complex at the same time. The described method combines artifacts from different domains. It has to do with motion capture (which is used in movie production), with grounded language (which is used in natural language processing) and with spline interpolation which is located in regression analysis. Combining all these subjects into a single project is not common in normal computer science. What computer scientists in the past have done is to solve a single problem. For example, they want to search in a database for a value. This limited problem is analyzed in depth, and the algorithm is created in a high level programming language. Unfortunately, this problem solving strategy fails in AI domains.
A good starting point for all sort of AI applications are teleoperated robots. Teleoperation means, that the machine has human level capabilities as default. The idea is, that a human operator is in charge of the system all the time. He is not allowed to leave the joystick because then the robot will fail to solve a task. If this teleoperated paradigm is working, the next step is to think about how to reduce the workload of the operator. That means, that he can control the robot hand more easier and relax a bit.
Trajectory replay
The interesting effect of a trajectory replay is, that on the first trial it won't work. If the robot repeats the prerecorded trajectory in a new situation the robot isn't able to reach the goal. But this failure doesn't show, that the idea is wrong, but it shows, that trajectory replay isn't the answer to the problem, but its the problem itself. The question is how to program a trajectory replay system which can adapt to different situations? Learning from demonstration is some sort of challenge which has to be addressed with modern algorithms.
Why this assumption won't result into a grasping robot is because nobody knows how the algorithm can solve a task. In contrast to sorting an array, so called AI tasks have nothing to do with computing itself, but they have to do with driving a car, the shape of objects and communicating in natural language.
The better idea for realizing AI systems is to start with a teleoperated robot which is extended later with a database of trajectories. In the first step the human operator controls the robot arm with a joystick. This allows him to grasp an object. In the step 2 the pipeline is extend with grounded natural language and a learning from demonstration motion database. Both modules are not located in classical computer science nor mathematics but they have to do with applications of Artificial Intelligence.
Perhaps it make sense to go into the details. Suppose the human operator is able to grasp an object with a joystick. In theory, he can do so many hundred times, but the goal is to transfer the task into software for higher productivity. One important step towards this direction is to repeat the same action and record the trajectory. The result is a motion capture database. If the scene in front of the robot fits to the recorded scene the recorded action is reproduced in the playback mode. An interpolation between different trajectories will increase the accuracy.
The next step towards advanced robotics is to tag the trajectory database with grounded language. That means, the database is annotated with labels like “open gripper”, “close gripper” and “push object”. This allows to search in the database easier. For example, if the next task is about “push object”, an SQL query to the motion database will return all the trajectories from this domain. Then the solver will select some of them and creates the interpolated trajectory which is executed on the robot.
The combination of teleoperated robotics, learning from demonstration, and natural language grounding is a powerful technique to realize robotics projects which can be used in reality. That means, the system is not only an academic project to teach the students who they should do something, but the robot can be used for solving practical tasks.
The reason why this approach is nearly unknown in mainstream robotics and AI has to do because its easy and very complex at the same time. The described method combines artifacts from different domains. It has to do with motion capture (which is used in movie production), with grounded language (which is used in natural language processing) and with spline interpolation which is located in regression analysis. Combining all these subjects into a single project is not common in normal computer science. What computer scientists in the past have done is to solve a single problem. For example, they want to search in a database for a value. This limited problem is analyzed in depth, and the algorithm is created in a high level programming language. Unfortunately, this problem solving strategy fails in AI domains.
A good starting point for all sort of AI applications are teleoperated robots. Teleoperation means, that the machine has human level capabilities as default. The idea is, that a human operator is in charge of the system all the time. He is not allowed to leave the joystick because then the robot will fail to solve a task. If this teleoperated paradigm is working, the next step is to think about how to reduce the workload of the operator. That means, that he can control the robot hand more easier and relax a bit.
Trajectory replay
The interesting effect of a trajectory replay is, that on the first trial it won't work. If the robot repeats the prerecorded trajectory in a new situation the robot isn't able to reach the goal. But this failure doesn't show, that the idea is wrong, but it shows, that trajectory replay isn't the answer to the problem, but its the problem itself. The question is how to program a trajectory replay system which can adapt to different situations? Learning from demonstration is some sort of challenge which has to be addressed with modern algorithms.
What is the current status in commercial robotics?`
Artificial Intelligence is from a technical point of view a complex domain. There are lots of papers with theories about neural networks and all sorts of robot control systems available. Even experts are not sure, which of them is a well written paper and which is providing boring information. A better idea is to judge about the status of robotics by take a look into commercial available products. Some brandnames are available like Agility Robotics, Boston Dynamics, Waymo, Moley robotics. They have in common that more than a single youtube video are available in which the engineers are demonstrating what is possible today.
The latest series of Agility robotics is able to walk on two legs, can climb stairs and is able to hold a box in the hands. The Waymo car is able to drive on the street alone, while the latest robot from Moley is able to cook a meal. All of the videos have someting in common. They are very new which means, that the videos are uploaded in the last 2 years and all of them showing robotics not available before. That means, the technology has made a big progress and it seems that all the difficulties are solved.
What will happen, if only the robotics from the mentioned companies are used in reality? Lots of human work can be done with these machines. There is no need for human truck drivers, for human cooking chef and for a human postal service. The main problem with this development is, that it is much faster than even experts have assumed. And what will happen in 2 years or even 4 years from now? Under the assumption that the trend is valid, the robots get improved and the result is, that the robots in reality have more skills than the robots from movies.
The interesting situation is that the current society isn't prepared for this kind of technology. What is expected by science fiction authors is, that in around 30 years from now some small progress is made towards fully autonomous production. But if the revolution is available within 2 years it will become too fast for the world. The only hope for critiques of technology is, that the videos of Boston Dynamics and Agility robotics are fake. That means, that the robots are performing great in a staged scenario but struggle on real tasks. This will make it impossible to use robots in real life condition.
Analyzing if robots are useful in practical application can be done by monitoring two parameters. First, the price of goods and second how important human work is for a society. If a robot revolution is there, the price for goods will drop to zero and human work becomes a low priority, because all the work is done by robots which are working for lower cost. If the engineers are struggle to introduce robots in the real world, the price for goods remains constant and human labor can't replaced by machines.
The latest series of Agility robotics is able to walk on two legs, can climb stairs and is able to hold a box in the hands. The Waymo car is able to drive on the street alone, while the latest robot from Moley is able to cook a meal. All of the videos have someting in common. They are very new which means, that the videos are uploaded in the last 2 years and all of them showing robotics not available before. That means, the technology has made a big progress and it seems that all the difficulties are solved.
What will happen, if only the robotics from the mentioned companies are used in reality? Lots of human work can be done with these machines. There is no need for human truck drivers, for human cooking chef and for a human postal service. The main problem with this development is, that it is much faster than even experts have assumed. And what will happen in 2 years or even 4 years from now? Under the assumption that the trend is valid, the robots get improved and the result is, that the robots in reality have more skills than the robots from movies.
The interesting situation is that the current society isn't prepared for this kind of technology. What is expected by science fiction authors is, that in around 30 years from now some small progress is made towards fully autonomous production. But if the revolution is available within 2 years it will become too fast for the world. The only hope for critiques of technology is, that the videos of Boston Dynamics and Agility robotics are fake. That means, that the robots are performing great in a staged scenario but struggle on real tasks. This will make it impossible to use robots in real life condition.
Analyzing if robots are useful in practical application can be done by monitoring two parameters. First, the price of goods and second how important human work is for a society. If a robot revolution is there, the price for goods will drop to zero and human work becomes a low priority, because all the work is done by robots which are working for lower cost. If the engineers are struggle to introduce robots in the real world, the price for goods remains constant and human labor can't replaced by machines.
What is a fully automated factory?
There is a myth available about so called perpetual motion machine. That is a wonder machine, which will work without interruption after pressing the on button. Most engineers have come to the conclusion, that such a machine would violate the physical laws, or to be more specific the law of thermodynamics. What the engineers are not aware is, that perpetual motion machines are not invented as real machines, but they are the subject of stories about automation.
The concept is about a technology which doesn't need human work but works without human labor. The question is not how to build such a machine with the law of physics, but such a machine has to fit into economic context. To be more specific, a perpetual motion machine is something which the owner of a factory likes to buy to reduce the costs. What the owner of a factory is trying to achieve is to produce a maximum output with a minimum amount of work. This will increase his profit.
What is available in the reality are example of factory automation. The typical machine needs a lot of energy and is repeating the same task over and over again. A printing machine is an example, but a pizza making assembly line is also a good example. From a physical standpoint these machines are the opposite of perpetual motion machine, but from an economic standpoint they are. What automated factories have in common is, that the costs for the factory owner is low, and at the same time the factory is producing lots of pizzas. Each of them costs nearly nothing. It's surprising at which low price it's possible to produce goods if all the steps are fully automated.
Suppose a fully automated pizza line was installed in a factory, and the raw materials are available. From a users perspective such a device is a miracle. The user can enter who many pizzas he like to eat, and after entering the number of 100k the start button is pressed. The machine won't stop until all the units are created. No further interaction is needed. The most interesting point is, that such a workflow is available in the reality. That means, real pizza making factory can be visited and they are used to produced food for the population.
To understand fully autonomy machines better we have to ask for potential bottleneck. What all these devices have in common that they need something as input. Its electricity plus raw materials. If no energy is available and no cheese is there, the machine won't work. The interesting point is, that these input materials are endless. Producing energy at low costs is an easy task and producing tones of cheese is also a solved task. If the production of raw materials is combined with fully autonomous assembly lines the result is a fully automated economy. Literately spoken, such a system can produce endless amount of goods for zero costs.
The concept is about a technology which doesn't need human work but works without human labor. The question is not how to build such a machine with the law of physics, but such a machine has to fit into economic context. To be more specific, a perpetual motion machine is something which the owner of a factory likes to buy to reduce the costs. What the owner of a factory is trying to achieve is to produce a maximum output with a minimum amount of work. This will increase his profit.
What is available in the reality are example of factory automation. The typical machine needs a lot of energy and is repeating the same task over and over again. A printing machine is an example, but a pizza making assembly line is also a good example. From a physical standpoint these machines are the opposite of perpetual motion machine, but from an economic standpoint they are. What automated factories have in common is, that the costs for the factory owner is low, and at the same time the factory is producing lots of pizzas. Each of them costs nearly nothing. It's surprising at which low price it's possible to produce goods if all the steps are fully automated.
Suppose a fully automated pizza line was installed in a factory, and the raw materials are available. From a users perspective such a device is a miracle. The user can enter who many pizzas he like to eat, and after entering the number of 100k the start button is pressed. The machine won't stop until all the units are created. No further interaction is needed. The most interesting point is, that such a workflow is available in the reality. That means, real pizza making factory can be visited and they are used to produced food for the population.
To understand fully autonomy machines better we have to ask for potential bottleneck. What all these devices have in common that they need something as input. Its electricity plus raw materials. If no energy is available and no cheese is there, the machine won't work. The interesting point is, that these input materials are endless. Producing energy at low costs is an easy task and producing tones of cheese is also a solved task. If the production of raw materials is combined with fully autonomous assembly lines the result is a fully automated economy. Literately spoken, such a system can produce endless amount of goods for zero costs.
April 12, 2020
OpenRA servers hit new record in numbers of players
The OpenRA game is available since many years. Its an open source clone of the famous Command&Conquer series. What makes the software interesting is, that it will run under Windows and LInux as well. In contrast to other Real time strategy game, no costs are charged for the users. Since two weeks the amount of players on the server has hit new records. In the past, it was difficult to find enough player to fill a map, but since a while this is not a problem.
Today there are more than 300 players at the same time on the servers, and new games are starting all the time. Technically this was possible in the past as well, what was missing in the year 2019 were a larger amount of players. It seems, that some newbies have discovered the game and are participating in the matches. On the website there is a statistics available https://www.openra.net/players/ which shows the increase of active players since April 2020.
Perhaps it make sense to introduce the game itself. What the users has to do is to manage a large amount of units at the same time. In contrast to a simple jump'n'run game there is not only a single character on the screen, but the user is in charge of 50 and more units at the same time. It's some sort of chess, but much faster. In the typical match 4 vs. 4 players, the situatiion will become chaotic very soon. That means, each player is in control of 50 and more units and the map is showing hundred of sprites at the same time who are doing something or not.
The OpenRA game has much in common with World of Warcraft. The difference is, that the graphics is only 2d and no background story is told. The result is, that the game engine itself is very little. The .exe file needs only 18 MB on the harddrive, which includes all the graphics, the multiplayer mode and even a replay mode to analyze games played in the past.
Today there are more than 300 players at the same time on the servers, and new games are starting all the time. Technically this was possible in the past as well, what was missing in the year 2019 were a larger amount of players. It seems, that some newbies have discovered the game and are participating in the matches. On the website there is a statistics available https://www.openra.net/players/ which shows the increase of active players since April 2020.
Perhaps it make sense to introduce the game itself. What the users has to do is to manage a large amount of units at the same time. In contrast to a simple jump'n'run game there is not only a single character on the screen, but the user is in charge of 50 and more units at the same time. It's some sort of chess, but much faster. In the typical match 4 vs. 4 players, the situatiion will become chaotic very soon. That means, each player is in control of 50 and more units and the map is showing hundred of sprites at the same time who are doing something or not.
The OpenRA game has much in common with World of Warcraft. The difference is, that the graphics is only 2d and no background story is told. The result is, that the game engine itself is very little. The .exe file needs only 18 MB on the harddrive, which includes all the graphics, the multiplayer mode and even a replay mode to analyze games played in the past.
April 08, 2020
From a burnout society to an open society
In the sociology literature it was observed that modern societies are effected by the burnout problem. If a burnout doesn't effect a single individual but a larger group, it's called a burnout epidemic. That means, that the situation is out of control and the question is how to handle the stress level of the group.
A naive assumption is, that the problem of stress, burnout and burnout epidemic will disappear without external intervention and that in the future, the tasks for the individual will become easier to solve, but not more complicated. A look into the reality shows, that since the advent of the Internet and a demanding complexity in the macro economy, the problems will become bigger but never smaller. That means, that future societies will be effected more by the stress problem, but not less.
The good news is, that an answer to the situation is available. It was first introduced for the software industry but can be adapted to other domains as well. The answer is to transfer existing processes into Open processes. Instead of creating proprietary software the idea is write open source software. Instead of creating paywall protected academic papers the idea is to publish a paper as Open Access. And in contrast to manage a society as closed society the better idea is to establish a open society culture.
But what does the term Open means in reality? At foremost it has to do with a different role model between consumer and producer of a good. Open Source software is from an economic standpoint an example for a consumer first ideology. The consumer which is the end user of the software, gets the latest security updates, the most advanced software and he doesn't has to pay anything for it. All the Debian users who have installed the software on their PC never pay something in return. They get only the latest linux kernel, the LaTeX tool and the powerful gimp graphics program and they have to provide nothing in exchange. The same case is true for the OpenAccess ecosystem, in which the enduser can read as many high quality pdf papers in Google Scholar without paying a single cent.
On the other hand, somebody has to produce all these good. The OpenSource software has to be written and a pdf paper too. The interesting point is, that this problem is up to the single producer and isn't managed by a company.
Today, software industry and academic content creation are the only domains in which the term Open was introduced. In all the other domains of economy, for example in logistics, retail industry and in the medical sector the paradigm is focussed on the classical closed economy model. Closed economy means, that that the consumer of a good has to pay the price, and the producer of the good gets a monthly salary. There is a reason why open source is available since the 1980s, while Open logistics not. Because software can be distributed over the Internet, but logistics services not. With so called telerobotics this can be changed. Suppose there is a truck which can be controlled from remote. There is no need that the driver is located physically in the truck, but everybody who has access to the internet is able to control the truck. Under such a contraints, it's possible to manage the task of cargo transportation as a game. Very similar to writing software it can be handled with the open paradigm. From the consumers perspective the situation is pleasant. Suppose a consumer has a need that the load is transportated from a to b. Similar to all Open services, he never pays a price for the task, but he asks if somebody is able to do it for free.
This sounds a bit uncommon, so let us go a step backward into the domain of the software industry. The current situation for endusers who are familiar with Linux is, that they are searching for a piece of software. For example a file manager. And the additional criteria is, that this software needs a GPL license. All the proprietary file manager are ignored by the consumer. He defines the GNU license as mandatory.
Now its easier to imagine what future consumers of logistics services will do. They are defining as a criteria, that the transportation needs to be handled without any costs. It's up to the opponent how he can reduce his costs downto zero. If somebody isn't able to do so, he doesn't get the task.
Today's economy isn't powerful enough for the Open society ideology. If somebody is asking for a truck for free, he won't find a single example. But with advanced technology and especially with remote control of machines it's possible to realize this ideology in the future. A possible toy example is a cheap drone which is controlled over the internet, and the advanced feature is, that the consumer doesn't has to pay for the service, but it's financed with advertisement or something else. Similar how Open Source and Open Access is financed.
Open society means to extend the term Open Source, Open Access and Open Science to the society in general. That means, that all services which are offered are provided without costs to anybody. This sounds a bit like socialism, but it's the opposite. It can be described as an advanced from of capitalism in which the stress level is increased.
A naive assumption is, that the problem of stress, burnout and burnout epidemic will disappear without external intervention and that in the future, the tasks for the individual will become easier to solve, but not more complicated. A look into the reality shows, that since the advent of the Internet and a demanding complexity in the macro economy, the problems will become bigger but never smaller. That means, that future societies will be effected more by the stress problem, but not less.
The good news is, that an answer to the situation is available. It was first introduced for the software industry but can be adapted to other domains as well. The answer is to transfer existing processes into Open processes. Instead of creating proprietary software the idea is write open source software. Instead of creating paywall protected academic papers the idea is to publish a paper as Open Access. And in contrast to manage a society as closed society the better idea is to establish a open society culture.
But what does the term Open means in reality? At foremost it has to do with a different role model between consumer and producer of a good. Open Source software is from an economic standpoint an example for a consumer first ideology. The consumer which is the end user of the software, gets the latest security updates, the most advanced software and he doesn't has to pay anything for it. All the Debian users who have installed the software on their PC never pay something in return. They get only the latest linux kernel, the LaTeX tool and the powerful gimp graphics program and they have to provide nothing in exchange. The same case is true for the OpenAccess ecosystem, in which the enduser can read as many high quality pdf papers in Google Scholar without paying a single cent.
On the other hand, somebody has to produce all these good. The OpenSource software has to be written and a pdf paper too. The interesting point is, that this problem is up to the single producer and isn't managed by a company.
Today, software industry and academic content creation are the only domains in which the term Open was introduced. In all the other domains of economy, for example in logistics, retail industry and in the medical sector the paradigm is focussed on the classical closed economy model. Closed economy means, that that the consumer of a good has to pay the price, and the producer of the good gets a monthly salary. There is a reason why open source is available since the 1980s, while Open logistics not. Because software can be distributed over the Internet, but logistics services not. With so called telerobotics this can be changed. Suppose there is a truck which can be controlled from remote. There is no need that the driver is located physically in the truck, but everybody who has access to the internet is able to control the truck. Under such a contraints, it's possible to manage the task of cargo transportation as a game. Very similar to writing software it can be handled with the open paradigm. From the consumers perspective the situation is pleasant. Suppose a consumer has a need that the load is transportated from a to b. Similar to all Open services, he never pays a price for the task, but he asks if somebody is able to do it for free.
This sounds a bit uncommon, so let us go a step backward into the domain of the software industry. The current situation for endusers who are familiar with Linux is, that they are searching for a piece of software. For example a file manager. And the additional criteria is, that this software needs a GPL license. All the proprietary file manager are ignored by the consumer. He defines the GNU license as mandatory.
Now its easier to imagine what future consumers of logistics services will do. They are defining as a criteria, that the transportation needs to be handled without any costs. It's up to the opponent how he can reduce his costs downto zero. If somebody isn't able to do so, he doesn't get the task.
Today's economy isn't powerful enough for the Open society ideology. If somebody is asking for a truck for free, he won't find a single example. But with advanced technology and especially with remote control of machines it's possible to realize this ideology in the future. A possible toy example is a cheap drone which is controlled over the internet, and the advanced feature is, that the consumer doesn't has to pay for the service, but it's financed with advertisement or something else. Similar how Open Source and Open Access is financed.
Open society means to extend the term Open Source, Open Access and Open Science to the society in general. That means, that all services which are offered are provided without costs to anybody. This sounds a bit like socialism, but it's the opposite. It can be described as an advanced from of capitalism in which the stress level is increased.
Language patterns in crisis communication
In role playing games, video games and online forums there is a special sort of communication pattern available. It's a conflicting language which is escalated by individuals. The interesting point is, that conflicts in crisis communication are the gold standard for mastering the game. And preventing such a language style won't work in solving real problems.
Let us assume what will happen, if Stackoverflow prevents to downvote existing answers, if Wikipedia stops banning of newbies and if the participants of a video game are only allowed to send greetings to the team players but are not allowed to criticize each other. This is equal to an anti-crisis communication. That means, no problems are there, and no conflicts have to be solved. Such a situation is equal to not playing the game at all.
All the issues in Stackoverflow, all the edits in WIkipedia and all the existing multi-player games in the internet has to do with solving problems. That means, at first there is some sort of issue, and different users have to interact to solve this issue. They are doing so with a crisis communication which is equal to a panic mode. Players who have learned to use such a language are able to become successful in such a game. While players who are not able to cope the stress get excluded from the game or resign by itself.
The best example is perhaps the Wikipedia game. It's a website in which the users are creating an encyclopedia. Everybody who is familiar with wikipedia will describe the situation in the talk sections are stressful. Wikipedia internal conflicts are solved and created with a panic based natural language. In the easiest case, an admin comes to the conclusion that an edit of the newbie doesn't make sense. But longer term Wikipedia editors are criticizing each other in the same tone. Does this crisis communication shows, that the Wikipedia has failed and the projects become obsolete within 2 months? No, it's the opposite. Because at the same time, the Wikipedia articles which are presented as a frontend to the reader have a higher quality since ever.
That means, a stable communication system contains of crisis communication and relaxed appearance at the same time. Let us observe a conflicting computer game from the outside. The different players in the game are communicating against each other. They are tracking conflicts and are not motivated to slow down their voice. At the same time, the game is running great. That means, the experts are playing the game and the success is guaranteed. This sort of mixed impression is available for all complex group oriented games. For example, at Stackoverflow each day thousands of downvotes and negative comments are posted. At the same time, the answer quality of the website is high. That means, if somebody has a problem with programming in a certain language he will find the answer at this single website very sure.
The reason why conflicts and complex problem solving are belong together has to do with asymmetric information. The typical situation in Wikipedia is, that user1 is an expert for a domain, while user2 not. From a technical point of view, both users are not able to work together, because their knowledge doesn't fit together. The same is true for most multi-player online games in the internet. Player1 is a newbie, player2 is an expert and they have never played before in this game. The result is, that they don't understand each other. The interesting situation is that the game will start with this bad situation. The result is, that during the game the users are communicating wrong, and they will make mistake. After recognizing the mistakes, they will lame each other not playing well enough.
This situation isn't located in a certain player, but it's the general pattern for all online games, and for all online forums. The starting situation is, that from an objective point of view, the newly created group isn't prepared and shouldn't work together. But this is never a barrier. No matter which player are attending a game server, the game will start in every case.
The reason why so much conflicts are available is because the players are different. The conflicts will become greater if the background of the player doesn't fit to each other. The users are arguing from very different point of views about the same subject. And the conflict is a clearing mechanism for negotiating with each other, especially in a complex domain.
To fasten things up, it make sense to assume that in every multi-player video games are conflict will become visible and the only question is how the group will solve these conflicts. Solving the conflict means, that the individual needs are matched to the need of the group. For example, a successful interaction with Wikipedia means that an individual is allowed to post something and at the same time the Wikipedia project will profit from it. It's some sort of win-win situation.
If a group or an individual struggles in solving issues, it will become a loose-loose-situation. That means, the user edit get rejected and at the same time, Wikipedia loose an important character who won't contribute anymore.
Let us assume what will happen, if Stackoverflow prevents to downvote existing answers, if Wikipedia stops banning of newbies and if the participants of a video game are only allowed to send greetings to the team players but are not allowed to criticize each other. This is equal to an anti-crisis communication. That means, no problems are there, and no conflicts have to be solved. Such a situation is equal to not playing the game at all.
All the issues in Stackoverflow, all the edits in WIkipedia and all the existing multi-player games in the internet has to do with solving problems. That means, at first there is some sort of issue, and different users have to interact to solve this issue. They are doing so with a crisis communication which is equal to a panic mode. Players who have learned to use such a language are able to become successful in such a game. While players who are not able to cope the stress get excluded from the game or resign by itself.
The best example is perhaps the Wikipedia game. It's a website in which the users are creating an encyclopedia. Everybody who is familiar with wikipedia will describe the situation in the talk sections are stressful. Wikipedia internal conflicts are solved and created with a panic based natural language. In the easiest case, an admin comes to the conclusion that an edit of the newbie doesn't make sense. But longer term Wikipedia editors are criticizing each other in the same tone. Does this crisis communication shows, that the Wikipedia has failed and the projects become obsolete within 2 months? No, it's the opposite. Because at the same time, the Wikipedia articles which are presented as a frontend to the reader have a higher quality since ever.
That means, a stable communication system contains of crisis communication and relaxed appearance at the same time. Let us observe a conflicting computer game from the outside. The different players in the game are communicating against each other. They are tracking conflicts and are not motivated to slow down their voice. At the same time, the game is running great. That means, the experts are playing the game and the success is guaranteed. This sort of mixed impression is available for all complex group oriented games. For example, at Stackoverflow each day thousands of downvotes and negative comments are posted. At the same time, the answer quality of the website is high. That means, if somebody has a problem with programming in a certain language he will find the answer at this single website very sure.
The reason why conflicts and complex problem solving are belong together has to do with asymmetric information. The typical situation in Wikipedia is, that user1 is an expert for a domain, while user2 not. From a technical point of view, both users are not able to work together, because their knowledge doesn't fit together. The same is true for most multi-player online games in the internet. Player1 is a newbie, player2 is an expert and they have never played before in this game. The result is, that they don't understand each other. The interesting situation is that the game will start with this bad situation. The result is, that during the game the users are communicating wrong, and they will make mistake. After recognizing the mistakes, they will lame each other not playing well enough.
This situation isn't located in a certain player, but it's the general pattern for all online games, and for all online forums. The starting situation is, that from an objective point of view, the newly created group isn't prepared and shouldn't work together. But this is never a barrier. No matter which player are attending a game server, the game will start in every case.
The reason why so much conflicts are available is because the players are different. The conflicts will become greater if the background of the player doesn't fit to each other. The users are arguing from very different point of views about the same subject. And the conflict is a clearing mechanism for negotiating with each other, especially in a complex domain.
To fasten things up, it make sense to assume that in every multi-player video games are conflict will become visible and the only question is how the group will solve these conflicts. Solving the conflict means, that the individual needs are matched to the need of the group. For example, a successful interaction with Wikipedia means that an individual is allowed to post something and at the same time the Wikipedia project will profit from it. It's some sort of win-win situation.
If a group or an individual struggles in solving issues, it will become a loose-loose-situation. That means, the user edit get rejected and at the same time, Wikipedia loose an important character who won't contribute anymore.
April 01, 2020
Recent developments in the SE.AI website
The SE.AI website https://ai.stackexchange.com/ is the dominant AI related online forum in the internet. It contains of 6k questions and is part of the larger Stack exchange network. Since a while major changes are taking place in the website. The situation in the past was, that the moderator played a minor role. He didn't posted many comments nor answers, but his objective was administrative nature. He was some kind of technical administrator but wasn't involved in running the website.
Since the year 2019 the situation has changed drastically. The new agenda in SE.AI is, that the moderator is the top rated user in the forum. That means, the current moderator has posted the most answers and has earned the most reputation points. That means, the moderator knows most about Artificial Intelligence and at the same time he is solving conflicts in the community.
Before we can judge about this development it make sense to describe this management style from an abstract point of view. It's equal to elect the best player in a soccer team as the team leader. The result is, that the team leader is the weak point in the overall system. Let us construct an example. Suppose a difficult question is asked in the forum. Only the moderator is able to provide the answer because he has the most experience of all the users. The other users in the community have a weaker position and they not enough skills about Artificial Intelligence. That means, the knowledge and power is distributed unequal.
This management style has some advantages but also disadvantages. The advantage is, that it will minimizes the conflicts in the team. The moderator is accepted because of two reasons, first his social role is strong, and secondly his knowledge is strong. The disadvantage is, that a moderator driven community is vulnerable to a takeover. If the single point of failure makes a mistake the entire group becomes in trouble. The second problem is, that the stress level for the moderator is higher. To defend his strong position he has to create the most postings and has to know everything. The danger is, that the moderator isn't able to do on the long term.
In the management theory there are two different principles discussed: top down moderation and bottom up moderation. Top down moderation is available in SE.AI. It's the classical form of group organization. The group has a strong internal cohesion but fails to adapt to the environment. The team is fixed, new members aren't welcome the moderator is not allowed to leave the group.
It's a bit difficult to predict the future development of SE.AI. One option is, that the moderator is able to handle the disadvantages of top down management style and remains in a active position for the next 10 years. The second option is, that the group isn't able to adapt to future needs. For example, that a request from the outside isn't answered correct. Basically spoken, SE.AI is doing an experiment to investigate if top down leadership works in reality.
Since the year 2019 the situation has changed drastically. The new agenda in SE.AI is, that the moderator is the top rated user in the forum. That means, the current moderator has posted the most answers and has earned the most reputation points. That means, the moderator knows most about Artificial Intelligence and at the same time he is solving conflicts in the community.
Before we can judge about this development it make sense to describe this management style from an abstract point of view. It's equal to elect the best player in a soccer team as the team leader. The result is, that the team leader is the weak point in the overall system. Let us construct an example. Suppose a difficult question is asked in the forum. Only the moderator is able to provide the answer because he has the most experience of all the users. The other users in the community have a weaker position and they not enough skills about Artificial Intelligence. That means, the knowledge and power is distributed unequal.
This management style has some advantages but also disadvantages. The advantage is, that it will minimizes the conflicts in the team. The moderator is accepted because of two reasons, first his social role is strong, and secondly his knowledge is strong. The disadvantage is, that a moderator driven community is vulnerable to a takeover. If the single point of failure makes a mistake the entire group becomes in trouble. The second problem is, that the stress level for the moderator is higher. To defend his strong position he has to create the most postings and has to know everything. The danger is, that the moderator isn't able to do on the long term.
In the management theory there are two different principles discussed: top down moderation and bottom up moderation. Top down moderation is available in SE.AI. It's the classical form of group organization. The group has a strong internal cohesion but fails to adapt to the environment. The team is fixed, new members aren't welcome the moderator is not allowed to leave the group.
It's a bit difficult to predict the future development of SE.AI. One option is, that the moderator is able to handle the disadvantages of top down management style and remains in a active position for the next 10 years. The second option is, that the group isn't able to adapt to future needs. For example, that a request from the outside isn't answered correct. Basically spoken, SE.AI is doing an experiment to investigate if top down leadership works in reality.
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