Portal:Complex Systems Digital Campus/MULTILINGUALISM

MULTILINGUALISM and Mutual WellBeing

Description
The multiculturalist inclusive knowledge society within the digital world CS-DC UNESCO UniTwin

The digital world is creating pre-conditions for a much longer survival of the several thousands indigenous areas and their intercultural relations toward an inclusive knowledge society. The new revolution of internet with the blockchain allows the constitutions of DAC (Digital Autonomous Community-Cooperative-College-Campus-Company) that can project and federate directly indigenous communities in the knowledge society without abandoning their community practices. Digital Autonomous Community can regulate through Digital Autonomous Cooperative or Companies their producing and consuming activities internally and externally with the rest of the world.

Digital Autonomous universitary Campus will have the data for studying the co-evolution of all other DACs for their coordination and their individual-collective interests. They will also coordinate lifelong personalized education for all. This personalized education will start since the early primary school in the Digital Autonomous Colleges for preparing all young people to such digital world for an inclusive knowledge society. The most difficult scientific and societal challenge is how one indigenous culture with its own indigenous language can strongly interact with the other cultures with their languages.

This challenge can be progressively solved through the community DAC practices above because these practices will produce huge corpora of phrases in indigenous languages with their translations in national languages. In a ten years horizon such community practices will allow the automatic translation from indigenous languages into other indigenous languages through automatic translation of national languages that will be available in the same horizon. Two great processes during human interactions through digital devices allow to make such challenge successful: a) the conservation of sense between translated contextual sentences and the disambiguation of the meaning of each word in its context by taking the intersection between the two polysemic meaning of the two corresponding words in the two languages, as done by humans when learning different languages b) this fondamental process is reinforced by immediate active learning when an understanding mistake happens, again as done during direct human interactions. Huge corpora of phrases in indigenous languages with their translations in national languages for sharing know how in building, educating, cooking, dancing and singing, in interacting and managing ecosystems and environment, e.g. in knowing which plant has excellent properties for food, health or parfum, etc .. Also bilingual comments on big cohorts of pictures and movies will be provided by the DACs for all these topics.

Three territories will be selected: two in the lusophone area where the CS-DC have founding members involved in this trend of research: Mozambic (200 languages) and Amazonia (300 languages); the third one is area around the Artic pole where some indigenous Universities is already existing. Notice that, in each territory (and this fact can define the territory) a main local languages (trade languages, written languages, ..) is frequently existing and understood by a lot of speakers of the other local languages. This main language is playing a central role in the automatic translation task.

The main assumption is that everyone involved in such research-action process can use a mobile phone for the Decentralized applications (Dapps) of this project either for her personal data or for public communications (and signed through the blockchain process).

Cost: 40M$ until 2020 (Google, Facebook, Microsoft Fondations) -	PhD and Postdoc for the UniTwin Network: 25M$ including 20M€ for the "indigenous Universities" of the UniTwin (no salary and no travel for senior scientists: they are using e-tools) -	Observation equipments for protocols and cloud computing for the community DACs: 15M€

Some (incomplete) references

 * 6 times less scientists and engineers in sub-saharian Africa than in the developing countries and 12 time less than in developped countries (Hippolyte Fofack, World Bank Senior Economist): in World Bank, professionals plan capacity building facility for Nigeria, Mathias Okwe, Guardian News January 11, 2005.
 * 10 times more suicides of young people in Amazonia (report of the French Senate)
 * Opportunity of 100 millions of new jobs with the Blue Economy
 * The climate change will affect in a very bad way sub-saharian Africa; and great mitigation can come from Amazonia
 * Between 50% and 90% of the 7000 human languages are endangered ones in the XXI Century in the UNESCO Map and UNESCO Atlas. 50% of the 7000 human languages are in 8 countries: India, Brazil,Mexico, Australia, Indonesia, Nigeria, Papua New Guinea, and Cameroon.
 * There is a fundamental linkage between language and environmental knowledge embedded in indigenous names, oral traditions and taxonomies that can be lost when a community shifts to another language.
 * Connecting Africa with internet. The computer is becoming the cheapest technological object (5€ for the Raspberry Pi), opening the road of ubiquitous network of connected sensors
 * LIFI

Description
Enlarging the community tissue of all kinds of DAC in the territory involved in the project, especially DACampus & Colleges (primary and secondary). Encouraging the community tissue to federate at all levels, step by step according to the needs, its community DACs into a global one in all domains, economic, social, environmental, educational and cultural.

Description
Multi-linguist Knowledge Map of the challenge: a) at the beginning, the relevant multi-linguist part of Wikipedia, of Web of Science at the beginning b) its progressive translation of the main relevant topics in the main territory local language by the territory DACampuses & Colleges for different classes of ages and competences c) the dynamics of the knowledge map is through the new items in Wikipedia and Web of Science, published both in the main local language and the international language, e.g. in the new CS-DC series of journal with reading committees. Notice that a special effort will be done for the theoretical Knowledge map especially in mathematics, relevant for the objectives of the territory.

Description
Multi-linguist personalized education for all scientists and societal actors involved in the project: connectivist MOOCs will be designed for the different classes of age and competences for involving each learner in a lifelong personalized education; each learner has some tutors two years in advance in the fields he/she is studying; the principle is the inverse school where learners are solving difficult problems in cloud classrooms and the study of preferred MOOCs at home, with online questions of each learner to the other members of the cloud classroom and to their personalized tutors.

Description
Protocols used for sustainable dynamical big data available: a) the big data provided by the economic, social, environmental, educational and cultural practices the community DAC b) the contribution of the community to an evolution of wikipedia and of the web of science c) the corpus of translated conceptual sentences. A lot of big data will be picture and movies obtained under some protocols (at least, if possible, geo-localized and precisely dated)

Description
Olympiads for the best multi-level models: international Olympiads will be organized for the most important topics of the territory and will strongly involve its scientists:
 * 1) the automatic translation of the local language to national language through the main local language
 * 2) the co-evolution of the economic, social, environmental, educational and cultural practices in the different community DAC at all levels and
 * 3) the influence on the dynamics of wikipedia and the web-of-science. Notice that the exploitation of raw data needs deep learning and algebraic topology for solving the "ground problem" in Artificial Intelligence: the augmented phenomenological reconstruction of the raw dynamics by (hyper)symbolic dynamics is the first step before a theoretical reconstruction. (see the CS-DC flagship on reconstruction)

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