On studying algorithms ethnographically: Making sense of objects of ignorance

Abstract

In this article, we make sense of financial algorithms as new objects of concern for organizational ethnography. We conceive of algorithms as ‘objects of ignorance’ jeopardizing traditional ethnography from the perspective of its categories and methods. We investigate the organizational politics taking place within high-frequency trading – a sub-field of algorithmic trading where automated decision-making without human direction has reached a peak, and show that financial algorithms raise particular epistemic and methodological challenges for practitioners and ethnographers alike. Consequently, we develop a typology for various interpretations of algorithms as ethnographic objects, accounting for their structural ignorance and shedding light on a continuum of the changing human-machine/trader-algorithm relation. To this end, we use the concepts of ‘quasi-object’ and ‘quasi-subject’ as developed by Michel Serres, and make the point that in order to study financial algorithms ethnographically, we need to think anew the dynamic relationship they embody, and acknowledge their constitutive heterogeneity.

Activists in the dark: Social media algorithms and collective action in two social movement organizations

“…This "dance of agency" (Pickering, 2008: 6), which has become prevalent in our analysis, is in line with previous literature, such as on algorithmic trading (e.g., Lange et al, 2019), arguing for an understanding of a rather symmetric relationship between human actors and algorithms, in which these actors influence and shape each other. Indeed, as our findings show, algorithms adapt to collective actions and may support, for example, the strength of a campaign, if interdependent actors make similar use of a hashtag.…”

“…From this standpoint, we outline the operations of social media algorithms based on their implications and qualitatively identify the ways in which algorithms shape collective action. As shown next, this research design allows us to map the shifting relations between activists' perceptions, the actualized technological features of social media, and the underlying adapting, changing, and mediating algorithmic operations (Lange et al, 2019).…”

Robo-advisors and the financialization of lay investors

“…The dearth of publicly available information on robo-advisors and difficulty in accessing robo-advisor investor subjects presented significant methodological challenges. Lange et al (2019) argue that algorithmic trading presents methodological challenges for researchers, as their internal operations are obscured in opacity due to their confidential and proprietary nature. A different approach was thus required.…”

Intelligente Systeme für das Bauwesen: überschätzt oder unterschätzt?

“…Sie beugen sich den Veränderungen ihrer Rolle durch Automatisierung und digitale Schnittstellen, die sie zu schnellerem, regelmäßigerem, unermüdlichem Handeln antreibt, eine hohe Anpassungsfähigkeit und -bereitschaft an Maschinentakt und -ergebnisse erfordert und sie auch emotional an deren Funktionstüchtigkeit bindet. Die Handlungsgewichte verschieben sich im Assistenz-Szenario stark in Richtung der digitalen Komponenten intelligenter Systeme, wenn auch zurecht angemerkt wird, dass diese Verschiebung weniger technischen Möglichkeiten als sozioökonomischen und organisationspolitischen Interessen zuzurechnen ist, etwa Rationalisierungs-und Kontrollbestrebungen (Hirsch-Kreinsen 2016;Lange et al 2019;Sadowski, Pasquale 2015). Die Entscheidungshorizonte der Maschinenbedienenden werden einerseits algorithmisch definiert, sind andererseits von Ursprung, Zuschnitt und Verfügbarkeit relevanter Inhalte abhängig.…”