Biased and sex-aggregated data: The forgotten half of the population

Big data, data science and artificial intelligence (AI) in research hold enormous potential to improve health and the quality of life for all. However, when harnessing benefit from new digital technologies, a major concern is to minimise harm. Inherent bias in historical data presents a major threat...

Full description

Saved in:
Bibliographic Details
Published in:South African Journal of Science 2023-05, Vol.119 (5-6), p.4-5
Main Authors: Cengiz, Nezerith, Kabanda, Siti M.
Format: Article
Language:English
Subjects:
Bias
Decision making
Womens health
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Big data, data science and artificial intelligence (AI) in research hold enormous potential to improve health and the quality of life for all. However, when harnessing benefit from new digital technologies, a major concern is to minimise harm. Inherent bias in historical data presents a major threat to the veracity of data and the impact thereof on algorithms, machine learning and, ultimately, AI. In this respect, Invisible Women: Exposing Data Bias in a World Designed for Men by Caroline Criado Perez makes a timely contribution by exploring the gender data representation gap in health care, education, economic development, and public policy. Criado Perez is a feminist author, journalist and social activist who has successfully campaigned for empowerment and representation of women in a multitude of different contexts, including the media presence of female experts and social media, in particular.
ISSN:0038-2353
1996-7489
DOI:10.17159/sajs.2023/14722