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Beyond algorithmic reformism: Forward engineering the designs of algorithmic systems:

Beyond algorithmic reformism: Forward engineering the designs of algorithmic systems: This article develops a method for investigating the consequences of algorithmic systems according to the documents that specify their design constrains. As opposed to reverse engineering algorithms to identify how their logic operates, the article proposes to design or "forward engineer" algorithmic systems in order to theorize how their consequences are informed by design constraints: the specific problems, use cases, and presuppositions that they respond to. This demands a departure from algorithmic reformism, which responds to concerns about the consequences of algorithmic systems by proposing to make algorithms more transparent or less biased. Instead, by investigating algorithmic systems according to documents that specify their design constraints, we identify how the consequences of algorithms are presupposed by the problems that they propose to solve, the types of solutions that they enlist to solve these problems, and the systems of authority that these solutions depend on. To accomplish this, this article develops a methodological framework for researching the process of designing algorithmic systems. In doing so, it proposes to move beyond reforming the technical implementation details of algorithms in order to address the design problems and constraints that underlie them. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Big Data & Society SAGE

Beyond algorithmic reformism: Forward engineering the designs of algorithmic systems:

Big Data & Society , Volume 7 (1): 1 – Mar 20, 2020

Beyond algorithmic reformism: Forward engineering the designs of algorithmic systems:

Big Data & Society , Volume 7 (1): 1 – Mar 20, 2020

Abstract

This article develops a method for investigating the consequences of algorithmic systems according to the documents that specify their design constrains. As opposed to reverse engineering algorithms to identify how their logic operates, the article proposes to design or "forward engineer" algorithmic systems in order to theorize how their consequences are informed by design constraints: the specific problems, use cases, and presuppositions that they respond to. This demands a departure from algorithmic reformism, which responds to concerns about the consequences of algorithmic systems by proposing to make algorithms more transparent or less biased. Instead, by investigating algorithmic systems according to documents that specify their design constraints, we identify how the consequences of algorithms are presupposed by the problems that they propose to solve, the types of solutions that they enlist to solve these problems, and the systems of authority that these solutions depend on. To accomplish this, this article develops a methodological framework for researching the process of designing algorithmic systems. In doing so, it proposes to move beyond reforming the technical implementation details of algorithms in order to address the design problems and constraints that underlie them.

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References (46)

Publisher
SAGE
Copyright
Copyright © 2022 by SAGE Publications Ltd, unless otherwise noted. Manuscript content on this site is licensed under Creative Commons Licenses.
ISSN
2053-9517
eISSN
2053-9517
DOI
10.1177/2053951720913064
Publisher site
See Article on Publisher Site

Abstract

This article develops a method for investigating the consequences of algorithmic systems according to the documents that specify their design constrains. As opposed to reverse engineering algorithms to identify how their logic operates, the article proposes to design or "forward engineer" algorithmic systems in order to theorize how their consequences are informed by design constraints: the specific problems, use cases, and presuppositions that they respond to. This demands a departure from algorithmic reformism, which responds to concerns about the consequences of algorithmic systems by proposing to make algorithms more transparent or less biased. Instead, by investigating algorithmic systems according to documents that specify their design constraints, we identify how the consequences of algorithms are presupposed by the problems that they propose to solve, the types of solutions that they enlist to solve these problems, and the systems of authority that these solutions depend on. To accomplish this, this article develops a methodological framework for researching the process of designing algorithmic systems. In doing so, it proposes to move beyond reforming the technical implementation details of algorithms in order to address the design problems and constraints that underlie them.

Journal

Big Data & SocietySAGE

Published: Mar 20, 2020

Keywords: Critical algorithm studies; predictive policing; design studies; algorithmic bias; algorithmic opacity; algorithmic accountability

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