Tauchain, the Internet of languages, and precise communication (ambiguity minimized)

ti mupli lo ka frili fi lo ka fanva fi lo glico lo nu la lojban

The previous two posts leading up to this were "The power of ambiguity and of ambiguity minimization in communication" and "Tauchain may allow for the development of the first Smart Constitution".

Tauchain and the "Internet of Languages"

Tauchain is more than just a blockchain. Tauchain itself is built from TML. TML stands for Tau MetaLanguage. TML is what is currently being developed on github. The current status of is that a draft of the forward chaining mechanism has been completed. The following step will likely be a draft of the backward chaining mechanism. The strategic importance of TML is that it offers the semantic preserving translation layer. Why is this such a big deal?

TauML enables:

Human --> Machine --> Human.

TML is the translator software (semantic preserving translation of one language to another).

So TML will allow you to speak in your language which for example could be simple English. Technically simple English and Lojban are examples of ambiguity minimized communication languages. Simple English is called a controlled natural language while Lojban is a constructed language. TML is a "meta language" and a tool which is designed to allow the translation between any languages while preserving meaning. So the brilliance of what TML is that it will let humans better communicate with humans and ultimately reach agreement. The most brilliant part of all is that our discussions in simple English or Lojban can be effortlessly translated into a decidable language via TML.

Decidability is king when it comes to languages. Why? Decision problems (which programs represent) are ultimately questions. So as a community we will be able to propose collaboratively a question for the machines to answer and we will be able to guarantee that there will be returned a yes or no answer to that question. This is the technical explanation for the benefit of decidability.

The field of computational complexity categorizes decidable decision problems by how difficult they are to solve. "Difficult", in this sense, is described in terms of the computational resources needed by the most efficient algorithm for a certain problem. The field of recursion theory, meanwhile, categorizes undecidable decision problems by Turing degree, which is a measure of the noncomputability inherent in any solution.

So in essence we will be able to speak to the machines via direct translation from our own human languages (simple English, Lojban), into the decidable language.

TML also benefits humans by facilitating better human --> human communication:

Human --> Machine --> Human (Alice communicates in simple English, it translates into Lojban, and from Lojban either back to simple English or to any other desired human readable language which Bob prefers).

And now you have an understanding of what TML does. Assume Alice and Bob both have their own languages which they must translate effectively between each other in order to have a precise conversation. TML offers the translation layer to make this possible so that meaning is preserved between all languages.

Summary

• Human --> Machine --> Human (Alice communicates in simple English, it translates into Lojban, and from Lojban either back to simple English or to any other desired human readable language which Bob prefers).

• Human -> Machine (Alice communicates in a decidable programming language or formal language to the machines by communicating in simple English and letting TML translate it into a formal language suitable for machines).

• Humans --> Machines (This is when we all collaboratively agree on what we want to say by communicating in human readable among ourselves in controlled natural languages and or constructed languages, where we agree or disagree and then translate it into machine languages.

• Humans --> Humans (simple English to Lojban, English to Spanish etc)

Hopefully this paints a clearer picture. TML facilitates communication by managing the language layer of the Tauchain. One of the most important tasks we will have in the beginning is to strategically choose good languages so that we can effectively reach agreement or disagreement. In some cases we will have to minimize ambiguity so that we can scale discussion on the human level but in other instances we will have to be concerned about how our wants are effectively translated and sent to the machines. If we think of the machines like the genie which can manifest what we want if only we can speak to it in the right way then we have to find the best way to speak to the machines but at the same time to collaborate we have to also constantly look for the best way to speak to each other.

Precise communication is what I like to call ambiguity minimized communication. TML will allow us to use controlled English in a manner which is acceptable for machine translation. It may even be possible to take Lojban and use that for even greater precision in communication between humans so that human to human communication is efficient. TML will theoretically allow for ambiguity when and where necessary and ambiguity minimization when and where preferred.

References

1. https://en.wikipedia.org/wiki/Decision_problem
2. https://en.wikipedia.org/wiki/Attempto_Controlled_English
3. https://en.wikipedia.org/wiki/Constructed_language
4. https://en.wikipedia.org/wiki/Knowledge_representation_and_reasoning
5. https://en.wikipedia.org/wiki/Formal_language
6. http://lojban.lilyx.net/zmifanva/