Algorithmic futuring: predictive infrastructures of valuation and investment in the assetization of edtech

Abstract

Futures of education are increasingly defined through predictive technologies and methods. We conceptualize ‘algorithmic futuring’ as the use of data-driven digital methods and predictive infrastructures to anticipate educational futures and animate actions in the present towards their materialization. Specifically, we focus on algorithmic futuring in the education technology investment industry, and the role of predictive infrastructures of valuation and investment in the assetization of edtech. Edtech investment actors make predictions based on the calculated future asset value of digital technologies. Methods and narratives of algorithmic futuring produced through predictive infrastructures are intended to render an assetized future of education seemingly attractive, attainable, and actionable. Our analysis foregrounds three forms of algorithmic futuring practised by an edtech investment organization: forecasting targets; managing uncertainty; and provoking assetization. Each has significant impacts on what futures are put into motion in the present, and exploit a gap in public investment in edtech futures.