RESEARCH
Algorithmic Interventions: The Power and Politics of Public Decision-Making Systems
Algorithmic interventions are a new and expanding avenue to influence social policy. Decision-making software is now being integrated within governing institutions ranging from the criminal justice system to social welfare programs. However, within any governing context, both the determinations about implementation and the software’s efficacy are dependent on many institutional and strategic constraints. In particular, I discuss three considerations when analyzing decision-making software used in government agencies or institutions: the intervention’s alignment, strength, and scope. The relative policy alignment of the algorithmic intervention focuses on whether an intervention seeks to strengthen a current policy or reform (or otherwise change) it. The strength of the algorithmic intervention refers to how binding the output is for the decision-making structure (i.e. requiring mandatory outcomes or providing a suggestion as a decision aid). Lastly, the scope of an algorithmic intervention refers to the number of points in the process that the algorithm impacts. In an apolitical world we might expect these considerations to be purely decided on bureaucratic optimization, but in the highly politicized and contentious arena of criminal justice or social welfare services, we can expect each of these decisions to be opportunities for strategic interactions between interested parties. This research explores these interactions and discusses how they might be considered when evaluating the implementation of such technology.
Dissertation
Research
Doctoral Candidate
The University of Minnesota- Twin Cities
2012 - 2018 (expected)
Dissertation: “Algorithmic Interventions: The Politics and Governance of Public Decision-Making Software”
Fields: International Relations, American Politics
Supporting Program: Science and Technology Policy
B.A. Political Science
The University of Nevada, Reno
2008 - 2012
Education
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Technical Competencies
R
Python​
STATA
Machine Learning techniques
Awards and Accomplishments
National Science Foundation Graduate Research Fellow
2014-2017
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Clara Ueland Graduate Fellow, 2012-2013
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Ronald E. McNair Post-baccalaureate Scholar
2011-2012
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Nevada Women’s Fund Scholarship Recipient
2011
National Science Foundation Graduate Research Fellow
2014-2017
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Clara Ueland Graduate Fellow, 2012-2013
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Ronald E. McNair Post-baccalaureate Scholar
2011-2012
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Nevada Women’s Fund Scholarship Recipient
2011
Curriculum Vitae
Project Fellow, 2016-2017
University of Minnesota, The City of St. Paul, MN
This is an initiative between the University of Minnesota and the City of St. Paul, MN. I serve as a researcher and data analyst for several projects that focus on data-driven justice initiatives.
Legal Research Aid, 2013-2014
University of Minnesota Law School
I worked on drafts of a petition to the Inter-American Commission on Human Rights on the behalf of a child soldier previously detained at Guantanamo Bay.
University of Minnesota Law School
Research Assistant, 2013-2014
University of Minnesota-Twin Cities
I worked as a researcher and social media consultant for an online human rights initiative
Research Assistant, 2010-2012
University of Nevada, Reno
I assisted in a large-scale survey project focused on lobbying strategies in the California State Legislature
Related Experience
Teaching
Experience
University of Minnesota
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Cyber War & Foreign Policy, University of Minnesota, Guest Lecturer, Spring 2017
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U.S. Foreign Policy, University of Minnesota, Teaching Assistant, Spring 2017
Volunteer Activities
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Boreas Leadership Program
Student Advisory Team
2016-Present​
Graduate Student Life Committee
Committee Member
2016- Present
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Secondhand Hounds
Foster and Volunteer
2014 – Present
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League of Women Voters
Project Committee Member
2013
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Big Brothers, Big Sisters
Mentor
2010-2012​
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Obama for America
Intern
2007-2008