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

IF 1.5 4区综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES

South African Journal of Science Pub Date : 2023-06-05 DOI:10.17159/sajs.2023/14722

Nezerith Cengiz, S. Kabanda

引用次数: 0

Abstract

PUBLISHED: 30 May 2023 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.

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有偏见和性别汇总的数据:被遗忘的一半人口

发布时间：2023年5月30日研究中的大数据、数据科学和人工智能在改善所有人的健康和生活质量方面具有巨大潜力。然而，在利用新数字技术带来的好处时，一个主要问题是将危害降至最低。历史数据中的固有偏见对数据的准确性及其对算法、机器学习以及最终对人工智能的影响构成了重大威胁。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

South African Journal of Science 综合性期刊-综合性期刊

CiteScore

3.20

自引率

4.20%

发文量

131

审稿时长

1 months

期刊介绍： The South African Journal of Science is a multidisciplinary journal published bimonthly by the Academy of Science of South Africa. Our mandate is to publish original research with an interdisciplinary or regional focus, which will interest readers from more than one discipline, and to provide a forum for discussion of news and developments in research and higher education. Authors are requested to write their papers and reports in a manner and style that is intelligible to specialists and non-specialists alike. Research contributions, which are peer reviewed, are of three kinds: Review Articles, Research Articles and Research Letters.