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About 20 years ago, in a paper entitled "Computational Mathetics: the Missing Link of Artificial Intelligence in Education", John Self argued that AI in Education has missed its connection with formal AI, its theoretical side. Some people argued that this was necessary so that AI in Education (AIED) could be able to deliver real world applications. However, in the real world, half of the population lives with less than 3 dollars a day with many socially excluded from education, health and other basic services. Social inclusion seeks to address the needs of this population, mostly living in underdeveloped countries, and also combat factors that are socially problematic in developed countries such as poor educational attainment, unemployment, poor health/special needs, low income, crime and poor housing/local environment. The AI in Education community has spent more than 30 years researching the design of adaptive technologies to support learning. However, the issue of supporting social inclusion has never been directly addressed. Has AI in Education also missed an important connection with the real world? We argue that AI in Education systems have a challenging role to play in helping to transform communities but we also accept that much has to be done to establish the ways in which work on AI in Education supports such activities indirectly, and to determine what future work needs to be done.

First Workshop on Artificial Intelligence in Education to Support the Social Inclusion of Communities (AIEDSIC)