Abstract

The Internet provides access to a global space of information assets and computational services. It also, however, serves as a platform for social interaction (e.g., Facebook) and participatory involvement in all manner of online tasks and activities (e.g., Wikipedia). There is a sense, therefore, that the Internet yields an unprecedented form of access to the human social environment: it provides insight into the dynamics of human behavior (both individual and collective), and it additionally provides access to the digital products of human cognitive labor (again, both individual and collective). Such access is interesting from the standpoint of research into machine intelligence, for the human social environment looks to be of crucial importance when it comes to the evolutionary and developmental origins of the human mind. In the present paper, we develop a theoretical account that sees the Internet as providing opportunities for online systems to function as socially-situated agents. The result is a vision of machine intelligence in which advanced forms of cognitive competence are seen to arise from the creation of a new kind of digital socio-ecological niche. The present paper attempts to detail this vision with respect to the notion of socially-scaffolded cognition. It also describes some of the forms of machine learning that may be required to enable online systems to press maximal cognitive benefit from their new-found informational contact with the human social world.