Library privatization as answer for everything

The classical debate around the future of libraries is held around the contrast between online and offline media. The library is strong in offline media, that means in printed books, and printed newspapers. Some Open Access activists have argued that this isn’t the future and that Science and information distribution has to become electronically. As a result, the library is no longer needed and can be replaced by Google.

This idea ignores what libraries are today. They are more then only provider of printed books, they have more in common with traditional bookstores and restaurants. And bookstores with printed books can’t be replaced completely by the internet. Because there is a huge demand for such products and this will stay constant at least for the next decades. The good news is, that a new form of debate is possible about the future of libraries, this time with a different spin. Instead of replacing libraries by the digital version, the exciting idea is to change the legal status of the library. Today, all public libraries are owned by non-profit organization like the government or the church. They have endless money, are producing huge costs, but nobody cares, because it is in the public domain. The better alternative is to privatize libraries. That means to transform them into a for-profit organization which is listed at the New york stockexchange like the railway and the postal service.

The surprising feature is, that this debate isn’t about the question if printed books or digital information will have a future. The business of the library (borrowing of printed books) can be remain the same. That means, the libraries didn’t have to digitize their books and they don’t need internet terminals. The only change is, that the legal structure behind the library is different. It is no longer part of the government or the church but the library will become a market participants like Starbucks. In my opinion, this is a great idea and will solve all today’s problem. If any resistance against this developing is occuring, the answer is to raise the privatization level even more. A second advantage is, that this structure is fair to existing companies who are also interested in making a library-like business with borrowing printed books but in former time they were not able to do so, because the public library had a monopoly on this domain. Privatization would help to increase the competition, that means, that different companies are able to run different sorts of libraries and the customer has the choice. Like in the market of fitness studious, where he also can chose in which one he want’s to go.

As far as i can see from a short Google search, the debate around library privatization isn’t held today. It seems, that most participants don’t see a need for discussing the details. But it is only a question of time. This debate will become more successful, then a debate about Open Access which doesn’t change anything.

The funny thing is, that most public libraries are seeing themself as a private service-provider. According to their self-awareness they have customers and are optimizing their return on investment. The library itself beliefs that she is private, at least since 30 years. But this description isn’t grounded in reality, because the public library is from the legal status a not-for profit government organization. Who is wrong? The self-awareness of the library is right, it is a for profit company. The next logical step is to update the legal status.

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Future of Open Access is privatization

My first impression of the Open Access debate was, that it’s about electronic documents. In the past, academic papers were written with a typewriter and printed out on a paper, while the future workflow will be centered around the internet. That means, the scientist is creating his paper on the Desktop PC, doesn’t print out anything and send the final PDF version to his publisher. From a technical point of view, this vision is right, and it well save a lot of money, but Open Access is much more. Open Access means to change not only the technical side, but the legal status of the libraries. Today’s libraries are so called public libraries. That means, they are owned by the government. The future is to transform academic libraries into for-profit companies with customers, employees and an annual report. Switching the storage format from printed journals to electronic journals is nice, but the more important step is to switch the legal status to a private company.

If the customers of future libraries are preferring printed journals over electronic versions, who cares? The library has to fulfill the customers needs. The more important issue is, that the library can have customers, income and shareholders. It is not only a question of mentality, but it is question of formal rules. Future libraries have not compete with Google. Google is an all digital company, while a library is based on physical locations in cities with physical customers. No, future libraries have to compete with other physical companies like McDonalds, Starbucks and Barnes & Noble. Barnes & Noble is like a library located in the physical world. It is not a search engine for webcontent, but a normal retail company. And the libraries have to changed into this type of organization.

Let us take a look at todays libraries. According to the “Global Library Statistics”, https://www.oclc.org/en/global-library-statistics.html The United states have 47500 libraries countrywide which costs 11 billion US$ per year. Not included the academic libraries, special libraries and national libraries. In comparison, Barnes and Noble have a revenue per year of 4 billion US$. But there is huge different. Banres and noble is a company, while the status of the library is not defined. They are owned by the government, by the church or by the cities. The libraries are not listed at the New york stackexchange and they have no anual report according to the US-GAAP standard. Sure, the libraries have some kind of income & costs table because otherwise we wouldn’t know that the total costs was 11 billion US$ per year, but it is not the annual report of a for-profit company.

The future of the library sector is to become a commercial company with a profit orientation. This will help to reduce the costs, make the structure more efficient and make the transition to Open Access easier. The funny thing is, that this doesn’t mean, that in the future all the customers will have to pay huge amount of money. It is possible that for a certain timeframe, the government will sponser the libraries with huge amount of money. The difference will be that the library are no longer part of the government but become separate. The question which has to be answered is: if radio stations, TV stations, Barnes and Noble, and even security firms and supermarkets can be run at a for-profit company, why is that not possible for a book borrowing service?

According to the Open Access the top priority for the libraries is to change their publication mode into an all-digital one. I don’t believe, that this priority is right. Libraries didn’t have to band printed journals, if customers are there who want to read printed books, the library can fulfill the need. What libraries has to change is only their legal status. They have to become Starbucks like organisations. This will solve all problems of today’s libraries, especially this one which have to do with an identity crisis and a missing vision for the future.

Let us take a look to another company which works different from Google and isn’t located in the internet business: the postal service. Every day, millions of letters are send with the classical postal service, and a prediction say, that this will be the same in ten 10 years. Is the postal service obsolete, only because E-Mail is available? No it is not obsolete, and the postal service make a huge amount of profit. That means, printed letters, and physical information have a future. 100 years ago, in some countries the postal service was a government like organisation. It wasn’t listed at the stock exchange and had no customers. Is today’s situation so much worse, then 100 years ago? Or is a for profit company more efficient?

More about library privatization

A look into the discussion on https://academia.stackexchange.com shows, that the admins are not very motivated to talk about library privatization. As a reaction to my question, they asked back for references and questioned, if this has something to do with Academia overall. Perhaps I can deliver some details.

At first it is important to talk about the legal status of libraries. That means, it has to do who own a public library, the government or the stockmarket. This is important because lending is at first a business. Let us take a look in some business which are dealing with this subject. Since the 1980s Video rental shops are available, https://en.wikipedia.org/wiki/Video_rental_shop Alone in the U.S. the classical physial rental store has many million customers. In the recent years a new business model was founded, called online streaming service. This generates also lots of profit. And a very new business model is called ebook flatrate. That means, the customer is no longer buying a book, but paying a fee for reading it within a week.

What is the idea behind all these companies? The idea is, that on the one side some media like films, tv-series, books, CD-ROMs and computergames are available. The content was created by book publishers, game publishers and by hollywood. On the other side is the customers who is interested in the content and has money for doing so. Like in any business, both market participants are meeting each other and change money for services.

And now comes the surprising question: what has this to do with public libraries? The answer is, that public libraries are also offer books, DVDs and computergames. And the question is: why?

Or let me become more specific. The traditional Open Access debate is about digitizing library. This is not a major problem. Because for printed books and movies on DVDs in the future will be also a market. The more interesting question is, if a public library or a video rental shop should provide the media to the customer.

The most impressive example for an online library is Scribd. This service works similar to Amazon Kindle Unlimited and the idea is that the customer pays a flatrate for reading a book. The surprising fact is, that on Scribd all the books are available which are also provided by an Academic library. The difference is, that Scribd is a for-profit company. Is it possible to run a high-quality media lending service as a for profit company? Yes, the video rental shops, Scribd and Netflix are the best examples. These companies would gets lots of more customers, if the public library are also working as a for profit company.

Bug: Stackexchange isn’t interested in discussing library privatization

Today I’ve posted a question to the famous Academia SE website, https://academia.stackexchange.com The question was about potential library privatization and what arguments are speaking against this development. From my perspective it was a good question and well formulated, but it took only 5 minutes until the admin has put the question on hold with the comment that it is off-topic.

Library privatization means to transform the classical library in a privately owned for profit company with the aim to increase the productivity and be competitive with the Internet.

The second software crisis

The original software crisis starts in the mid 1970s and defined as lack of lowlevel software for running a computer. Namely Compiler, operating systems, applications for text processing and network operating systems. The original software can be called solved, because today everything is available both as commercial product and since the 1990 as Open Source software, called Linux. If somebody today needs a compiler for translating object oriented sourcecode in machinecode he has the choice between at least 100 different alternatives. Some of them will cost money (Visual C++) others are for free (GNU C++).

Identifying the key components which have solved the software crisis is easy. With the advent of microcomputers, the computing idea became a mainstream subject. In the 1980s even kids were able to program small BASIC programs at home. In parallel the software industry growed and created a huge market for all kind of applications. Learning to program is a standard subject in any university course around the planet and online forums like Stackoverflow extend the idea further that everybody is welcome in learning it.

But there is a second software crisis at the horizon. That is software not for running a computer, but for realizing Artificial Intelligence. This time it is much more difficult to solve the problem. That means, the former infrastructure which solved the first crisis is not enough to come up with the second. The software industry today combined with github, stackoverflow and programming courses at university level are not enough in teaching what AI is. That problem is, that AI is not only a computer science topic but has a much broader impact. The AI topic is discussed mostly in academic papers, without writing a paper it is not possible to grasp a subject in detail. The problem is, that until now, there is not a real infrastructure available to create and dristribute AI related papers. This bottleneck prevents a raising Artificial Intelligence community.

It is important to separate between programming itself, and AI programming. Programming itself is easy. It is described in the literature since the 1970 and contains subject like compilers, object-oriented programming, databases and operating systems. The problem is, that even somebody is an expert in all of these subject he isn’t prepared for Artificial Intelligence. AI is something which is more complicated then only programming. AI is a combination between computer programming and AI theory.

Programming of an operating system needs surprisingly less scientific effort. It is enough to have read 10 major books and the newbie can start to write his own compiler, driver or operating system. Programmers are mostly only programmers, that means, they have understand the computer system but they are not academics. In contrast, the AI topic is located primarly in the gutenberg galaxis. It contains of around 1 million different papers written by others, and a beginner should have read all to can discuss current developments. Without access to Google Scholar it is not possible to contribute in any useful way to the AI community. If somebody doesn’t know what a LSTM network is, what STRIPS mean or what reinforcement learning is, he will not understand more difficult ideas.

Become a good programmer can be realized without knowing the academic literature or simply ignoring it. Trying the same in the AI domain isn’t an option. AI can be visualized as a huge mountain of books which has to climbed until the top. It is not possible to bypass the mountain or pretend that it doesn’t exist. The problem is, that browsing through Google Scholar and writing papers alone is nothing what is teached in today’s university system. And that is the reason, why AI failed in general. There are simply no students available which have read enough papers and written enough by it’s own, to call themself an expert. That means, the total number of people who are familiar with the AI subject is very very small. This results into a second software crisis. That means, they are virtual no programs available and no tutorials how to write such programs. AI is hidden behind company door and is done in secrecy.

Why C++ is superior to Python, Java and C#

On the first look, C/C++ is a complicated language, mostly because of the pointer syntax and because every programmers has it’s own programming style. In contrast, the Python syntax is much more cleaner and provides beginner a good platform for programming prototypes, while C# is a good tool for programming real applications which has to be run fast. So, is C++ perhaps outdated?

No it is not, because the assumption that Python is easier to learn is a misconception. Let us first introduce a concept which improves the productivity of a programmer more then any other concept, it is called “operating system library”. The reason why today games can be programmed by a single person on a single day while in the 1980s this wasn’t possible has to do with out of box libraries which are available today. A well implemented library like SFML allows the programmer to program a 2d jump’n’run game including a game logic, animated sprites and a sound, without writing too much complicated code. And a library for parsing PDF allows the programmer to realize a GUI application also without much effort.

The number one question in programming is not about the perfect programming language with the cleaner syntax, it is about access to existing libraries and writing new libraries for future use. Without any doubt, C/C++ is the best programming language for programming libraries. It is used by Linux, Mac OS and Windows all the time, and there is no alternative out there. Sure, in theory it is possible to write an operating system in Java or in Python, but the reality is, that this is not done, because an operating system has to be fast, and needs access to the hardware.

Sure it is possible to use Python sourcecode for accessing a C/C++ library. But it is not able to replace C/C++ with python, because somebody has to create the library first. If no library is there, Python programmers are not able to create one from scratch. Because writing a library needs lot of lines of code. The main problem with today’s C++ ecosystem is not the language itself, but a lack of libraries. That means, not the C++ syntax is complicated, but the libraries are which are not providing all the features the user need. For example, SFML doesn’t provide 3D access. And as a result, using SFML is complicated. A switch from C++ to Python or C# will not improve the situation, because the working of a library has to with the API it provides, not with the language syntax.

The way to future computing is organized around better libraries. If the library gets a cleaner API, it can be used easier by the programmer, no matter which language he prefers. And C/C++ is the answer for writing better libraries. It is some kind of standard programming language for that task. Any operating system is written in C/C++ and libraries are part of the operating system. That means, existing problems in C++ can’t be solved by a different programming language, they can only be solved within the C/C++ ecosystem.

Python, C# and Java have the problem, that they didn’t understand this concept. They believe, that programming in C++ is too complicated and that they can provide help for the enduser. On the short hand, they are true. A gui application written in Python is easier to program then a GUI application in C++. But what will happen, if all the programmers will switch from C++ away to Python? Right, nobody is there for improving the libraries and this will result into much more problems, then Python can solve. In the software ecosystem is only one bottleneck available: the libraries written in C++. If somebody improves the quality there he will raise up the standard for all operating systems, all programming languages and all sort of software. Criticizing C/C++ as the wrong language is not a contribution to that goal, but a statement to ignore the problems. C# programmers have give up to write better software. They are simply doing their own business and are no longer work together with other programmers on the overall project. The same is true for Go programmers, Rust programmers and all the other C/C++ replacements available today. It the energy which was invested into writing go libraries from scratch would be redirected into improving existing C/C++ libraries the software quality would be greater today.

Perhaps some numbers

If a game engine was used a simple game can be realized in 500 lines of code. In which language the code was written isn’t very important. Python has the cleanest syntax, but C/C++ code is also readable. The problem is not, if the code contains some pointers or a complicated syntax, the only problem is, if the lines of code will raise from 500 to 5000 because the absence of a library. That will kill the productivity drastically.

Python was invented as a high productivity language. And C# was invented as a pointer-free language. What the language developers has forget to tell is, that the productity is based on the existence of C/C++ library. Without lowlevel C libraries for getting access to the graphic card, the harddrive and the soundcard, Python and C# are nothing. Without a library in the background, the language can’t even put a simple hello world to the screen. What so called high-level-language didn’t have understood is, that not their clean syntax will raise the productivity, but the fact they run on top of existing operating system APIs. Pushing the existing productivity to new highs can’t be done with high-level scripting languages, it can only be done with better C/C++ libraries. And teaching the students how to program in Python doesn’t provide the knowledge in writing better C++ libraries. So it is the wrong way in computer science curriculum. If the students are honest to themself, they know that Python is wrong. It makes no sense to invent a second language only for getting easier access to the C language. If somebody is interested in bringing C forward, he can improve existing compilers and write new c interpreters from scratch but please: do not invent another programming language.which is easier to use then C/C++.

How to realize a scientific Artificial Intelligence project

Intelligent machines are without any doubt the future, and that a scientific project is needed to understand AI in detail is also clear. But how exactly can an Artificial Intelligence project be made in reality? What are the keysteps in booting up a research laboratory? This will be answered in the following tutorial.

At first, it is important to know that a science project has to do with buying something. The desired goods can be hardware, software and ideas. But let us make a small example. Suppose, the idea is to start a deeplearning research project. The first step is, that the lab needs some infrastructure:

• fast internet connection

• Workstation PC (5000 US$ each), router hardware

• 3d printer, beamer for conferences, haptic devices for input

• motion tracking hardware, Mocap hardware

• nvidia deeplearning cluster, cloud based server for running a wiki

To get in touch with such technology is simple, if enough money is available. Most of the devices are available in normal computer retail stores, others (for example deeplearning hardware and mocap tracking markers) are available in special store. It sounds surprising, but at least 10% of a research project is about finding the right hardware, and decide which of them has to be bought.

Suppose, all the hardware is there and the lab has around 1 million US$ less money. What’s next? Also the step 2 has to do with buying something. Buying another hardware makes no sense, because if everything is available then on some point it makes no sense to buy the 100th workstation. The next buying decision has to do with scientific ideas. Usually, each of the devices contains a manual, and also the AI literature provides some instructions. The question is now, how to use the equipment in the right way. For example it is possible to install Windows 10 on the workstation PCs or a Linux distribution. It is possible to focus on LSTM neural network or on Convolutional networks. It is possible to investigate research topic A or B. From a certain point of view, this can also be called a buying decision, because the scientists has to decide to get in touch with a certain idea and stay away from another one.

Perhaps one example. It is possible to use a out-of-the-box deeplearning software like Tensorflow or program everything from scratch. The question is not, how to use Tensorflow or how to program with C/C++, the question goes only about the decision itself. That means, to compare what is better and what the researcher want’s. Usually such decisions are made after reading lots of information and discussion the market with other experts. This takes also a lot of time.

Suppose, the research lab has bought computer hardware, and has bought some key ideas. The next step is to do write down a first description of the project. That means, to talk about the own buying decision and communicate it to the outside. In most cases, the people who gave the money are interested in such kind of feedback, because they want to know, for what the 1 million US$ was spend and about which topic in detail, the deeplearning project is about. Until now, the project took around 80% of the overall time. That means, the setup and buying decision need most of the time. With the remaining 20% of the time, the researcher can try to realize their own ideas. In most cases, they will fail, but that isn’t a problem, if the failure is documented well. Writing down, that the own attempt to boot up the workstation and make something useful with Tensorflow wasn’t successful is in case of doubt a real science project. For the beginners that’s sound crazy, because nobody has done real research. All what the project was about is to buy thinks, recognize what’s wrong with them and write down, that’s unclear what the problem is. But, that is the essence of a real AI project. If such a project took 12 months and costs 10 million US$ it can be called a great one and a template for copying the principle.

The most important discovery is, that apart from buying something, there is no way to make science. If somebody is on the standpoint, that he do not buy any product out there, and don’t want to buy any idea available he is not a scientists. Apart from “going shopping” there is nothing what a scientist can do. The only difference to the normal understanding of shopping is, that the products are different. Buying new shoes in a deeplearning project is out of the scope, except it is about image recognition for an online store. Scientific research is modern form of go hunting. At first, the prey is circled and then the meat gets slaughtered. Communication with the outside and other researchers is important because this will increase the success probability. Apart from this archaic ritual there is no other possibility to make science. If somebody isn’t interested in this social game, he isn’t part of the scientific community.

Sometimes, tigers are called hunters but they can be called customers too. They searching for food like humans go to the supermarket and search what’s inside deep cooling rack. And scientists are doing basically the same. Most of the time they are hanging around in computer stores, in libraries and on conferences, because they are searching for intellectual food. That the currency they are focussed on.

Youtube has a dedicated category under the name “shopping haul”. That are videos about people who are visiting a store and putting everything in the basket what is really good. Usually a haul takes time, because it is not possible to buy everything, so a decision has to be made. A haul can took place in many locations: in a computer store, in a supermarket, in a clothing store and so on. For the case of a science, the only difference is the store. Which has mostly to do with an academic book store or a computer store. If the scientists is a good one, he will take some time for doing a carefully decision and he can explain the details.