BiasFinder: Metamorphic test generation to uncover bias for sentiment analysis systems
Artificial intelligence systems, such as Sentiment Analysis (SA) systems, typically learn from large amounts of data that may reflect human bias. Consequently, such systems may exhibit unintended demographic bias against specific characteristics (e.g., gender, occupation, country-of-origin, etc.). S...
Saved in:
Main Authors: | ASYROFI, Muhammad Hilmi, YANG, Zhou, IMAM NUR BANI YUSUF, KANG, Hong Jin, Ferdian, Thung, LO, David |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2022
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7611 https://ink.library.smu.edu.sg/context/sis_research/article/8614/viewcontent/2102.01859.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
BiasRV: uncovering biased sentiment predictions at runtime
by: YANG, Zhou, et al.
Published: (2021) -
BiasHeal: On-the-fly black-box healing of bias in sentiment analysis systems
by: YANG, Zhou, et al.
Published: (2021) -
Fairness testing of machine translation systems
by: Sun,Zeyu, et al.
Published: (2024) -
Timing and heat sources for the Barrovian metamorphism, Scotland
by: Viete, D.R., et al.
Published: (2014) -
Applicant perceptions of test fairness: integrating justice and self-serving bias perspectives
by: Chan, D., et al.
Published: (2011)