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You Are Part of the Machine : = Understanding Algorithmic Discrimination in Artificial Intelligence.

Record Type:	Electronic resources : Monograph/item
Title/Author:	You Are Part of the Machine :/
Reminder of title:	Understanding Algorithmic Discrimination in Artificial Intelligence.
Author:	Walker, Julia.
Description:	1 online resource (60 pages)
Notes:	Source: Masters Abstracts International, Volume: 83-12.
Contained By:	Masters Abstracts International83-12.
Subject:	Political science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29067726click for full text (PQDT)
ISBN:	9798802732694

You Are Part of the Machine : = Understanding Algorithmic Discrimination in Artificial Intelligence.
Walker, Julia.

You Are Part of the Machine :Understanding Algorithmic Discrimination in Artificial Intelligence. - 1 online resource (60 pages)

Source: Masters Abstracts International, Volume: 83-12.

Thesis (M.A.)--The University of North Carolina at Chapel Hill, 2022.

Includes bibliographical references

This thesis seeks to identify the increasing apparency of discriminatory behavior in the decision-making processes of artificial intelligence algorithms and identify which states are best prepared to prevent this new discrimination-both in terms of artificial intelligence readiness and responsible deployment. Through comparative analyses between the infrastructures of OECD states leading the way in artificial intelligence development and deployment, it seeks to explain why those states that have the greatest capacity and readiness for artificial intelligence may not necessarily be the states most apt at responsibly preventing artificial intelligence discrimination moving forward. From these analyses, it is argued that several clear patterns can be identified: states with smaller and less developed private technology sectors have a stronger focus on responsible development over large-scale deployment and states with a pre-existing prioritization for human rights and privacy infrastructure are more prepared to enact stronger protections against automated discrimination. Upon further case study analysis between the United States and Estonia, it is argued that these trends are indicative of a greater dichotomy between states that prioritize private sector innovation and those that prioritize responsible, equitable artificial intelligence applications in public sector services.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798802732694Subjects--Topical Terms:

528916
Political science.
Subjects--Index Terms:

AI preparednessIndex Terms--Genre/Form:

542853
Electronic books.

You Are Part of the Machine : = Understanding Algorithmic Discrimination in Artificial Intelligence.
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500 $a Advisor: Hooghe, Liesbet.
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504 $a Includes bibliographical references
520 $a This thesis seeks to identify the increasing apparency of discriminatory behavior in the decision-making processes of artificial intelligence algorithms and identify which states are best prepared to prevent this new discrimination-both in terms of artificial intelligence readiness and responsible deployment. Through comparative analyses between the infrastructures of OECD states leading the way in artificial intelligence development and deployment, it seeks to explain why those states that have the greatest capacity and readiness for artificial intelligence may not necessarily be the states most apt at responsibly preventing artificial intelligence discrimination moving forward. From these analyses, it is argued that several clear patterns can be identified: states with smaller and less developed private technology sectors have a stronger focus on responsible development over large-scale deployment and states with a pre-existing prioritization for human rights and privacy infrastructure are more prepared to enact stronger protections against automated discrimination. Upon further case study analysis between the United States and Estonia, it is argued that these trends are indicative of a greater dichotomy between states that prioritize private sector innovation and those that prioritize responsible, equitable artificial intelligence applications in public sector services.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
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650 4 $a European studies. $3 3168420
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