The Societal Impacts of Algorithmic Decision-Making
Loading...
No Access Until
Permanent Link(s)
Collections
Other Titles
Authors
Abstract
Algorithms are used to make decisions in an ever-increasing number of socially consequential domains. From risk assessment tools in the criminal justice system to content moderation tools to assessments in hiring, algorithms play a key role in shaping the lives of people around the world. Algorithms offer many potential benefits: they are consistent, scalable, and can leverage more data than any human could reasonably consume. However, without careful consideration algorithmic decision-making also carries a number of risks, like replicating human biases, creating perverse incentives, and propagating misinformation. This thesis seeks to develop principles for the responsible deployment of algorithms in applications of societal concern, realizing their benefits while address- ing their potential harms. What does it mean to make decisions fairly? How do theoretical ideas about societal impacts manifest in practice? How do existing legal protections apply in algorithmic settings, and how can technical insights inform policy?In this thesis, we explore these questions from a variety of perspectives. Part II leverages theoretical models to surface challenges posed by algorithmic decision-making and potential avenues to overcome them. Part III incorporates models of behavior to better understand the interplay between algorithms and humans decisions. In Part IV, we explore how these insights manifest in practice, studying applications in employment and credit scoring contexts. We conclude in Part V with open directions for future research.
Journal / Series
Volume & Issue
Description
481 pages
Sponsorship
Date Issued
2021-08
Publisher
Keywords
algorithmic fairness; employment discrimination; game theory
Location
Effective Date
Expiration Date
Sector
Employer
Union
Union Local
NAICS
Number of Workers
Committee Chair
Kleinberg, Jon M.
Committee Co-Chair
Committee Member
Levy, Karen
Tardos, Eva
Weinberger, Kilian Quirin
Tardos, Eva
Weinberger, Kilian Quirin
Degree Discipline
Computer Science
Degree Name
Ph. D., Computer Science
Degree Level
Doctor of Philosophy
Related Version
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
Related Publication(s)
Link(s) to Related Publication(s)
References
Link(s) to Reference(s)
Previously Published As
Government Document
ISBN
ISMN
ISSN
Other Identifiers
Rights
Attribution-NonCommercial 4.0 International
Types
dissertation or thesis