Recently, computer technologies based on neuroscientific insights into brain function and structure have been promoted for application in education. Brain-inspired ‘neurocomputational’ techniques including advanced machine learning, neural networks, artificial intelligence and cognitive computing are increasingly intervening in social life and institutions, designed to ‘learn’—like the human brain—through social interaction with both people and other machines. The novel practices and environments produced by these biologically-inspired neurocomputational technologies require new forms of ‘biosocial’ analysis (Meloni, Williams & Martin 2016; Youdell 2016) that are attentive to the intersections of the social, biological and computational aspects of learning, but also critically interrogate the scientific claims upon which such innovations are based. This paper provides an original analysis of current brain-based R&D by the edu-business Pearson to apply artificial intelligence in education, and by the computing company IBM to develop cognitive systems for learning. In 2016, the two organizations announced a global partnership to begin embedding IBM’s cognitive systems in Pearson’s digital courseware. These emerging forms of neurocomputation are intended to function according to neuroscientific understandings of the brain, and to impress themselves on the cerebral lives of learners by being embedded in educational spaces. To examine the biologically-inspired and technologically-mediated educational environments imagined by IBM and Pearson, the paper advances the idea of ‘brain/code/space’ as a conceptual framework. This integration of geographical research on ‘brain culture’ (Pykett 2015) and technologically-mediated ‘code/space’ (Kitchin & Dodge 2011) describes environments that possess brain-like functions of learning and cognition performed by computational processes. The neurocomputational imaginaries of Pearson and IBM are seeking to transform educational environments into brain/code/spaces, with potential future implications for: (1) the performativity of education systems, as brain-inspired technologies are designed to optimize human capital development through acting as cognitive enhancement systems; and (2) understandings of learning that are based on claims about the brain as a complex networked learning platform that is multiply connected to a vast ecosystem of both human and nonhuman cognitive platforms.

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