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The Rise of Algorithmic Work: Implic...

Cameron, Lindsey.

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The Rise of Algorithmic Work: Implications for Organizational Control and Worker Autonomy.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The Rise of Algorithmic Work: Implications for Organizational Control and Worker Autonomy./
Author:	Cameron, Lindsey.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	206 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-11, Section: A.
Contained By:	Dissertations Abstracts International81-11A.
Subject:	Business administration. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28006444
ISBN:	9798643185468

The Rise of Algorithmic Work: Implications for Organizational Control and Worker Autonomy.
Cameron, Lindsey.

The Rise of Algorithmic Work: Implications for Organizational Control and Worker Autonomy. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 206 p.

Source: Dissertations Abstracts International, Volume: 81-11, Section: A.

Thesis (Ph.D.)--University of Michigan, 2020.

This item must not be sold to any third party vendors.

In less than a decade the on-demand economy, a labor market characterized by short-term contracts where work is coordinated through algorithms, has radically reshaped organizations, employment relationships, workers' lives, and consumer behaviors. Despite optimistic and pessimistic predictions, few studies have examined how algorithms affect work and workers in practice. This dissertation focuses on understanding the impact of algorithms on workers in an environment where the entire human resource cycle is coordinated by algorithms. Existing organizational theories suggest that algorithmic systems will tighten the iron cage by providing more comprehensive and invasive methods of control. This dissertation, however, reveals the myriad ways that workers find autonomy in an algorithmic work environment.To theorize this central finding, I draw upon field work collected from the ride hailing industry, the largest sector in the on-demand economy. I begin with an overview of some of the changes in the contemporary workplace highlighting how they may challenge and extend mainstream organizational theories. I follow with a review of the on-demand economy, including its predecessors of production and service work, and how it affects workers, consumers, and communities. Next, I describe how algorithm-based control systems differ from prior systems and conceptualize algorithmic work-a set of job-related activities that are structured by algorithms-drawing on a synthesis of literature across six social science disciplines. I conclude this chapter with unexplored questions at the nexus of work, workers, and algorithms.In the two empirical papers, I draw on participant observation (including three years as a driver and a rider), longitudinal interviews, online archival data and focus groups. In the first study, I examine how workers interpret the insecure work conditions inherent in the on-demand economy. Focusing on the practices and perspectives of the two most salient features of their work environment-customers and technology-I explore how these interactions lead drivers to understand their work. Seeing their relationship with work as either an alliance or as adversarial, workers tend to view features of the work environment as either working on their behalf or against them. Over time these practices and perspectives culminate in different outcomes.In the second study, I begin by describing how algorithm-based control systems differ from prior systems and conceptualize algorithmic work. Algorithms manage by structuring choice at each human-algorithm interaction, to which drivers respond with a set of tactics: compliance, engagement, or deviance. While these tactics appear to be at odds, drivers describe their responses as evidence of their personal autonomy, in that the system allows them to maximize earnings and create a continuous stream of work from a discontinuous set of tasks. This autonomy demonstrates that although the algorithmic-manager may be an unforgiving taskmaster, workers perceive otherwise, thus suggesting that workers feel they have more autonomy in algorithmic rather than traditional work.This dissertation provides several theoretical and empirical contributions. First, I summarize perspectives of algorithms across the social sciences laying out several unanswered questions at the intersection of work, organizations, and algorithms. Further, I propose a definition of how algorithms operate in the workplace which I expand on. In contrast to iron cage metaphors, this dissertation suggests that workers do indeed experience a great deal of autonomy in the algorithmic workplace. This study thus has implications for our understanding of algorithms, organizational control, autonomy and the meaning of work.

ISBN: 9798643185468Subjects--Topical Terms:

3168311
Business administration.
Subjects--Index Terms:

Algorithms

The Rise of Algorithmic Work: Implications for Organizational Control and Worker Autonomy.
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520 $a In less than a decade the on-demand economy, a labor market characterized by short-term contracts where work is coordinated through algorithms, has radically reshaped organizations, employment relationships, workers' lives, and consumer behaviors. Despite optimistic and pessimistic predictions, few studies have examined how algorithms affect work and workers in practice. This dissertation focuses on understanding the impact of algorithms on workers in an environment where the entire human resource cycle is coordinated by algorithms. Existing organizational theories suggest that algorithmic systems will tighten the iron cage by providing more comprehensive and invasive methods of control. This dissertation, however, reveals the myriad ways that workers find autonomy in an algorithmic work environment.To theorize this central finding, I draw upon field work collected from the ride hailing industry, the largest sector in the on-demand economy. I begin with an overview of some of the changes in the contemporary workplace highlighting how they may challenge and extend mainstream organizational theories. I follow with a review of the on-demand economy, including its predecessors of production and service work, and how it affects workers, consumers, and communities. Next, I describe how algorithm-based control systems differ from prior systems and conceptualize algorithmic work-a set of job-related activities that are structured by algorithms-drawing on a synthesis of literature across six social science disciplines. I conclude this chapter with unexplored questions at the nexus of work, workers, and algorithms.In the two empirical papers, I draw on participant observation (including three years as a driver and a rider), longitudinal interviews, online archival data and focus groups. In the first study, I examine how workers interpret the insecure work conditions inherent in the on-demand economy. Focusing on the practices and perspectives of the two most salient features of their work environment-customers and technology-I explore how these interactions lead drivers to understand their work. Seeing their relationship with work as either an alliance or as adversarial, workers tend to view features of the work environment as either working on their behalf or against them. Over time these practices and perspectives culminate in different outcomes.In the second study, I begin by describing how algorithm-based control systems differ from prior systems and conceptualize algorithmic work. Algorithms manage by structuring choice at each human-algorithm interaction, to which drivers respond with a set of tactics: compliance, engagement, or deviance. While these tactics appear to be at odds, drivers describe their responses as evidence of their personal autonomy, in that the system allows them to maximize earnings and create a continuous stream of work from a discontinuous set of tasks. This autonomy demonstrates that although the algorithmic-manager may be an unforgiving taskmaster, workers perceive otherwise, thus suggesting that workers feel they have more autonomy in algorithmic rather than traditional work.This dissertation provides several theoretical and empirical contributions. First, I summarize perspectives of algorithms across the social sciences laying out several unanswered questions at the intersection of work, organizations, and algorithms. Further, I propose a definition of how algorithms operate in the workplace which I expand on. In contrast to iron cage metaphors, this dissertation suggests that workers do indeed experience a great deal of autonomy in the algorithmic workplace. This study thus has implications for our understanding of algorithms, organizational control, autonomy and the meaning of work.
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653 $a Organizational control
653 $a Uber
653 $a Meaning of work
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