A challenge for developing context riding mechanisms

Abstract

AI technologies that capture the context of interactions are emerging. The paper proposes an information contextualization technology that transforms certain information into information that fits into a conversation between people or adapts a person's statements into something that fits into a conversation already in progress. By examining actual examples of information contextualization technology, we discuss the potential of context-riding assistants for relating people and information to the interaction context.