Decision Time: Normative Dimensions of Algorithmic Speed

ACM Conference on Fairness, Accountability, and Transparency (FAccT '22)

18 Pages Posted: 27 Apr 2022

Date Written: April 7, 2022

Abstract

Existing discussions about automated decision-making focus primarily on its inputs and outputs, raising questions about data collection and privacy on one hand and accuracy and fairness on the other. Less attention has been devoted to critically examining the temporality of decision-making processes—the speed at which automated decisions are reached. In this paper, I identify four dimensions of algorithmic speed that merit closer analysis. Duration (how much time it takes to reach a judgment), timing (when automated systems intervene in the activity being evaluated), frequency (how often evaluations are performed), and lived time (the human experience of algorithmic speed) are interrelated, but distinct, features of automated decision-making. Choices about the temporal structure of automated decision-making systems have normative implications, which I describe in terms of "disruption," "displacement," "re-calibration," and "temporal fairness," with values such as accuracy, fairness, accountability, and legitimacy hanging in the balance. As computational tools are increasingly tasked with making judgments about human activities and practices, the designers of decision-making systems will have to reckon, I argue, with when—and how fast—judgments ought to be rendered. Though computers are capable of reaching decisions at incredible speeds, failing to account for the temporality of automated decision-making risks misapprehending the costs and benefits automation promises.

Keywords: automated decision-making, ADM, speed, time, temporality, AI ethics, data ethics

Suggested Citation

Susser, Daniel, Decision Time: Normative Dimensions of Algorithmic Speed (April 7, 2022). ACM Conference on Fairness, Accountability, and Transparency (FAccT '22), Available at SSRN: https://ssrn.com/abstract=4078006 or http://dx.doi.org/10.2139/ssrn.4078006

Daniel Susser (Contact Author)

Penn State University ( email )

E325 Westgate Building
University Park, PA 16802
United States

HOME PAGE: http://www.danielsusser.info

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