Generative AI Disproportionately Harms Long Tail Users

Barani Maung Maung; Keegan McBride; Jason S. Lucas; Maryam Tabar; Dongwon Lee

doi:10.1109/MC.2024.3408594

Generative AI Disproportionately Harms Long Tail Users

Barani Maung Maung
, Keegan McBride
, Jason S. Lucas
, Maryam Tabar
, Dongwon Lee

College of Information Sciences and Technology

Research output: Contribution to specialist publication › Article

3 Scopus citations

Abstract

Generative AI’s (GenAI’s) risks can be amplified in “long tail” populations and regions. We recommend strategies to mitigate these risks and conclude by calling for a more nuanced and global dialog on GenAI safety.

Original language	English (US)
Pages	82-85
Number of pages	4
Volume	57
No	11
Specialist publication	Computer
DOIs	https://doi.org/10.1109/MC.2024.3408594
State	Published - 2024

All Science Journal Classification (ASJC) codes

General Computer Science

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10.1109/MC.2024.3408594

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title = "Generative AI Disproportionately Harms Long Tail Users",

abstract = "Generative AI{\textquoteright}s (GenAI{\textquoteright}s) risks can be amplified in “long tail” populations and regions. We recommend strategies to mitigate these risks and conclude by calling for a more nuanced and global dialog on GenAI safety.",

author = "Maung, \{Barani Maung\} and Keegan McBride and Lucas, \{Jason S.\} and Maryam Tabar and Dongwon Lee",

note = "Publisher Copyright: {\textcopyright} 1970-2012 IEEE.",

year = "2024",

doi = "10.1109/MC.2024.3408594",

language = "English (US)",

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pages = "82--85",

journal = "Computer",

issn = "0018-9162",

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T1 - Generative AI Disproportionately Harms Long Tail Users

AU - Maung, Barani Maung

AU - McBride, Keegan

AU - Lucas, Jason S.

AU - Tabar, Maryam

AU - Lee, Dongwon

PY - 2024

Y1 - 2024

N2 - Generative AI’s (GenAI’s) risks can be amplified in “long tail” populations and regions. We recommend strategies to mitigate these risks and conclude by calling for a more nuanced and global dialog on GenAI safety.

AB - Generative AI’s (GenAI’s) risks can be amplified in “long tail” populations and regions. We recommend strategies to mitigate these risks and conclude by calling for a more nuanced and global dialog on GenAI safety.

UR - https://www.scopus.com/pages/publications/105004009823

UR - https://www.scopus.com/pages/publications/105004009823#tab=citedBy

U2 - 10.1109/MC.2024.3408594

DO - 10.1109/MC.2024.3408594

M3 - Article

AN - SCOPUS:105004009823

SN - 0018-9162

VL - 57

SP - 82

EP - 85

JO - Computer

JF - Computer

ER -

Generative AI Disproportionately Harms Long Tail Users

Abstract

All Science Journal Classification (ASJC) codes

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