The racializing forces of/in AI educational technologies

In this article, we examine the sociopolitical implications of AI technologies as they are integrated into writing instruction and assessment. Drawing from new materialist and Black feminist thought, we consider how learning analytics platforms for writing are animated by and through entanglements of algorithmic reasoning, state standards and assessments, embodied literacy practices, and sociopolitical relations. We do a close reading of research and development documents associated with Essay Helper, a machine learning platform that provides formative feedback on student writing based on standards-aligned rubrics and training data. In particular, we consider the performative acts of the algorithm in the Essay Helper platform – both in the ways that reconstitutes material-discursive relations of difference, and its implications for transactions of teaching and learning. We argue that, through these processes, the algorithms function as racializing assemblages, and conclude by suggesting pathways toward alternative futures that reconfigure the sociopolitical relations the platform inherits.