Temporal Construction in Algorithmic Sensemaking: The Case of Financial Markets

This paper extends the theories of sensemaking in relation to two topics of increasing interest in organization studies: temporal orientation and automation of work. Drawing on approximately 150 interviews conducted collaboratively by a research team, I examine how sensemaking in algorithms structure temporalities as technological acceleration in the financial markets dramatically heightened the importance of time management. The temporal structuring in algorithmic sensemaking is a sociomaterial process, where the materiality of algorithms decouples sensemaking from organizational contexts but social cues are meaningful in constructing temporalities. I illustrate that while algorithmic sensemaking is inherently retrospective as classic texts of sensemaking argues, its sensemaking integrates the present and future with the past. As algorithmic trading minimize human intervention by design, algorithms continuously compare the present to the schemata extracted from the past to identify the optimal timing of action and reduce the time risk associated with fast-changing market environments. At the same time, algorithms make predictions of the future based on the retrospective schemata to prospectively prevent own actions from moving the market and therefore prolong the validity of the schemata.