Algorithmic Autonomy in Data-Driven AI

Fuente: arXiv
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Main Authors: Wang, Ge, Pea, Roy
Format: Preprint
Published: 2024
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author Wang, Ge
Pea, Roy
author_facet Wang, Ge
Pea, Roy
contents In societies increasingly entangled with algorithms, our choices are constantly influenced and shaped by automated systems. This convergence highlights significant concerns for individual autonomy in the age of data-driven AI. It leads to pressing issues such as data-driven segregation, gaps in accountability for algorithmic decisions, and the infringement on essential human rights and values. Through this article, we introduce and explore the concept of algorithmic autonomy, examining what it means for individuals to have autonomy in the face of the pervasive impact of algorithms on our societies. We begin by outlining the data-driven characteristics of AI and its role in diminishing personal autonomy. We then explore the notion of algorithmic autonomy, drawing on existing research. Finally, we address important considerations, highlighting current challenges and directions for future research.
format Preprint
id arxiv_https___arxiv_org_abs_2411_05210
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Algorithmic Autonomy in Data-Driven AI
Wang, Ge
Pea, Roy
Human-Computer Interaction
Computers and Society
In societies increasingly entangled with algorithms, our choices are constantly influenced and shaped by automated systems. This convergence highlights significant concerns for individual autonomy in the age of data-driven AI. It leads to pressing issues such as data-driven segregation, gaps in accountability for algorithmic decisions, and the infringement on essential human rights and values. Through this article, we introduce and explore the concept of algorithmic autonomy, examining what it means for individuals to have autonomy in the face of the pervasive impact of algorithms on our societies. We begin by outlining the data-driven characteristics of AI and its role in diminishing personal autonomy. We then explore the notion of algorithmic autonomy, drawing on existing research. Finally, we address important considerations, highlighting current challenges and directions for future research.
title Algorithmic Autonomy in Data-Driven AI
topic Human-Computer Interaction
Computers and Society
url https://arxiv.org/abs/2411.05210