The Flash Crash: A Review

Akansu, Ali N.

doi:10.2139/ssrn.3076563

Cited by 1 publication

(1 citation statement)

References 21 publications

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“…The interconnectedness of algorithmic actions showed that its force was boosted by the speed at which the systems operate. The millisecond time scale of modern financial markets dominated by algorithmic high-frequency trading made human interventions impossible (Akansu 2017). Once the algorithms started to execute their pre-programmed but misguided scripts, no human could re-evaluate the strategies and break the circuits.…”

Section: Contextmentioning

confidence: 99%

Dynamics of Social Harms in an Algorithmic Context

Malik

Viljanen

Lepinkäinen

et al. 2022

Int J for Crime, Justice & Social Democracy

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Growing evidence suggests that the affordances of algorithms can reproduce socially embedded bias and discrimination, increase the information asymmetry and power imbalances in socio‑economic relations. We conceptualise these affordances in the context of socially mediated mass harms. We argue that algorithmic technologies may not alter what harms arise but, instead, affect harms qualitatively—that is, how and to what extent they emerge and on whom they fall. Using the example of three well-documented cases of algorithmic failures, we integrate the concerns identified in critical algorithm studies with the literature on social harm and zemiology. Reorienting the focus from socio‑economic to socio-econo-technological structures, we illustrate how algorithmic technologies transform the dynamics of social harm production on macro and meso levels by: (1) systematising bias and inequality; (2) accelerating harm propagation on an unprecedented scale; and (3) blurring the perception of harms.

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Section: Contextmentioning

confidence: 99%