Algorithmic Interventions: The Power and Politics of Algorithmic Decision Systems

Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Algorithmic Interventions: The Power and Politics of Algorithmic Decision Systems

Published Date

2019-08

Publisher

Type

Thesis or Dissertation

Abstract

Algorithmic Decisions Systems (ADS) are now commonly integrated within governing institutions ranging from the criminal justice system to social welfare programs. In an apolitical world, we might expect these considerations to be purely decided on bureaucratic optimization, but within highly politicized and contentious policy areas, we can expect each of these decisions to be opportunities for strategic interactions between interested parties. My dissertation seeks to address three core questions regarding governmental adoption of Algorithmic Decision Systems. 1) What attributes of these systems may lead legislators to support their use? 2) Does the inclusion of ADSs increase legislative support for bills that include these systems? 3) Do changes in the narrative around ADSs, particularly perceived public backlashes, impact legislative support? Throughout Chapters 1 and 2, I trace the history of ADSs as a natural evolution of bureaucratic systems and unpack the characteristics of ADSs that may be attractive to policymakers. In Chapter 3, I use a game-theoretic model to explore the way that ADSs are used to expand legislative control over bureaucratic decision-making. In Chapter 4, I use an empirical model to analyze legislative support for criminal justice legislation in U.S. state legislatures over the period 2012-2018, I provide evidence that suggests that inclusion of ADSs did increase some forms of legislative support for bills that included them, but that these effects were eroded and then overcome in later years by the recent critical turn and public backlash against ADSs. Lastly, I conclude my dissertation by discussing possible research avenues for future scholarly work on governmental adoption of Algorithmic Decisions Systems.

Description

University of Minnesota Ph.D. dissertation. August 2019. Major: Political Science. Advisors: Benjamin Bagozzi, Joanne Miller. 1 computer file (PDF); ix, 135 pages.

Related to

Replaces

License

Collections

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Suggested citation

Halen, Jennifer. (2019). Algorithmic Interventions: The Power and Politics of Algorithmic Decision Systems. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/225031.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.