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Article
Publication date: 14 March 2023

Paula Hall and Debbie Ellis

Gender bias in artificial intelligence (AI) should be solved as a priority before AI algorithms become ubiquitous, perpetuating and accentuating the bias. While the problem has…

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Abstract

Purpose

Gender bias in artificial intelligence (AI) should be solved as a priority before AI algorithms become ubiquitous, perpetuating and accentuating the bias. While the problem has been identified as an established research and policy agenda, a cohesive review of existing research specifically addressing gender bias from a socio-technical viewpoint is lacking. Thus, the purpose of this study is to determine the social causes and consequences of, and proposed solutions to, gender bias in AI algorithms.

Design/methodology/approach

A comprehensive systematic review followed established protocols to ensure accurate and verifiable identification of suitable articles. The process revealed 177 articles in the socio-technical framework, with 64 articles selected for in-depth analysis.

Findings

Most previous research has focused on technical rather than social causes, consequences and solutions to AI bias. From a social perspective, gender bias in AI algorithms can be attributed equally to algorithmic design and training datasets. Social consequences are wide-ranging, with amplification of existing bias the most common at 28%. Social solutions were concentrated on algorithmic design, specifically improving diversity in AI development teams (30%), increasing awareness (23%), human-in-the-loop (23%) and integrating ethics into the design process (21%).

Originality/value

This systematic review is the first of its kind to focus on gender bias in AI algorithms from a social perspective within a socio-technical framework. Identification of key causes and consequences of bias and the breakdown of potential solutions provides direction for future research and policy within the growing field of AI ethics.

Peer review

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-08-2021-0452

Details

Online Information Review, vol. 47 no. 7
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 12 October 2022

Gong-Bing Bi, Wenjing Ye and Yang Xu

Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined…

Abstract

Purpose

Existing literature demonstrates the important role of information transparency in enterprise development and market surveillance. However, little empirical research has examined the information transparency effect in supply chain management. This study aims to fill this gap by exploring the significant role of information transparency on supply chain financing and its mechanism, taking trade credit as the starting point.

Design/methodology/approach

From the data set comprising 3,880 Chinese firms with A-shares listed on the Shenzhen and Shanghai Stock Exchanges from 2011 to 2020, we obtain the basic picture of information transparency and trade credit. Panel fixed effects regression is used to test the hypotheses concerning the antecedents to trade credit.

Findings

The empirical results show that: first, information transparency can significantly support corporate access to trade credit and is found to facilitate financing by mitigating perceived risk. Second, among companies with higher levels of financing constraints, weaker market power and more concentration of suppliers, information transparency promotes trade credit more markedly. Third, the outbreak of COVID-19 causes a substantial increase in uncertainty and risk in external circumstances and then the effect of information transparency is weakened. Fourth, the contribution to trade credit is likely to be stronger for disclosures containing management transparency elements compared to single financial transparency.

Originality/value

To the best of our knowledge, this study is one of the first to explore the positive role of information transparency to supply chain financing, which to a certain extent makes up for the lack of information transparency research in the supply chain. It provides new ideas for enterprises to obtain trade credit financing and promote the improvement of supervision departments’ disclosure policies.

Details

Kybernetes, vol. 53 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

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