Global Cognition and Modelling Tasks in Arts and Education

Abstract

The creation and use of models is the basis for cognition and action. The main challenge for education is to prepare for real action, using different possibilities to create action models (AM) and their components (templates) so as to build real action. The methodology used in the study is based on a critical analysis of different models of consciousness using the principle of complementarity. The informative theory of emotion as well as its generalisations and applications in decision making have been applied, with particular attention to educational tasks. The design and operation of consciousness and artificial intelligence (AI) is based on the creation, storage, and use of AM. Natural and artificial neural networks use the datasets needed for training. The task of education is to organise the most efficient use of available information to prepare for tasks whose content is not known in advance. As the uncertainty and novelty of tasks are rapidly increasing, preparations for the evaluation of information should be used with increasing generalisations. The role of art in education is therefore rapidly growing. Similar problems arise in the formation of weak AI (machine learning), which become more significant on the road to strong AI (super intelligence) or general AI (AGI). The results from the study support the complex development of arts, education, and AI. An emotion classification system has been developed to facilitate the understanding of various evaluation problems. The results obtained could be significant for ensuring the stability of AI. Proposals have been made for building a common world understanding and meaning of life through art within the educational system.