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We discuss the participatory learning paradigm and emphasize the all‐inclusive role that what is already believed plays in every aspect of the learning process. One manifestation of this is the appearance of an acceptance mechanism. This mechanism determines which data (experiences) will be used for learning based on its compatibility with what we already believe. A prototypical example of a participatory learning system is introduced. Methods for formulating the required compatibility function are discussed. We introduce the concept of a critic that monitors the performance of the system and gives us some independence from our current beliefs. Finally, we consider a participatory learning system which does not require that the attribute being learned take numeric values. We emphasize that understanding this paradigm can be useful both to help build a digital learning algorithm as well as to provide an instrument for enhanced interaction with others.

Participatory learning: a paradigm for building better digital and human agents