AIMC Topic: Sexism
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The Gender Gap Tracker: Using Natural Language Processing to measure gender bias in media.
PloS one
Jan 29, 2021
We examine gender bias in media by tallying the number of men and women quoted in news text, using the Gender Gap Tracker, a software system we developed specifically for this purpose. The Gender Gap Tracker downloads and analyzes the online daily pu...
How language shapes prejudice against women: An examination across 45 world languages.
Journal of personality and social psychology
Feb 20, 2020
Language provides an ever-present context for our cognitions and has the ability to shape them. Languages across the world can be gendered (language in which the form of noun, verb, or pronoun is presented as female or male) versus genderless. In an ...
Word embeddings quantify 100 years of gender and ethnic stereotypes.
Proceedings of the National Academy of Sciences of the United States of America
Apr 3, 2018
Word embeddings are a powerful machine-learning framework that represents each English word by a vector. The geometric relationship between these vectors captures meaningful semantic relationships between the corresponding words. In this paper, we de...
The Ugly Truth About Ourselves and Our Robot Creations: The Problem of Bias and Social Inequity.
Science and engineering ethics
Sep 21, 2017
Recently, there has been an upsurge of attention focused on bias and its impact on specialized artificial intelligence (AI) applications. Allegations of racism and sexism have permeated the conversation as stories surface about search engines deliver...
Gender and ethnicity bias in generative artificial intelligence text-to-image depiction of pharmacists.
The International journal of pharmacy practice
Nov 14, 2024
INTRODUCTION: In Australia, 64% of pharmacists are women but continue to be under-represented. Generative artificial intelligence (AI) is potentially transformative but also has the potential for errors, misrepresentations, and bias. Generative AI te...
Gender-sensitive word embeddings for healthcare.
Journal of the American Medical Informatics Association : JAMIA
Jan 29, 2022
OBJECTIVE: To analyze gender bias in clinical trials, to design an algorithm that mitigates the effects of biases of gender representation on natural-language (NLP) systems trained on text drawn from clinical trials, and to evaluate its performance.
Prestigious AI meeting takes steps to improve ethics of research.
Nature
Jan 1, 2021
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