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Wide range screening of algorithmic bias in word embedding models using large sentiment lexicons reveals underreported bias types. [PDF]
PLoS ONE, 2020 Concerns about gender bias in word embedding models have captured substantial attention in the algorithmic bias research literature. Other bias types however have received lesser amounts of scrutiny.
David Rozado
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Algorithmic bias in social research: A meta-analysis. [PDF]
PLoS ONE, 2020 Both the natural and the social sciences are currently facing a deep "reproducibility crisis". Two important factors in this crisis have been the selective reporting of results and methodological problems.
Alrik Thiem +3 more
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Potential for Algorithmic Bias in Clinical Decision Instrument Development [PDF]
npj Digital MedicineClinical decision instruments (CDIs) face an equity dilemma. They reduce disparities in patient care through data-driven standardization of best practices. However, this standardization may perpetuate bias and inequality within healthcare systems.
Jed Keenan Obra +5 more
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Identifying and mitigating algorithmic bias in the safety net [PDF]
npj Digital MedicineAlgorithmic bias occurs when predictive model performance varies meaningfully across sociodemographic classes, exacerbating systemic healthcare disparities.
Shaina Mackin +3 more
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Evaluating Algorithmic Bias in 30-Day Hospital Readmission Models: Retrospective Analysis
Journal of Medical Internet ResearchBackgroundThe adoption of predictive algorithms in health care comes with the potential for algorithmic bias, which could exacerbate existing disparities.
H Echo Wang +3 more
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Understanding algorithm bias in artificial intelligence-enabled ERP software customization [PDF]
Journal of Ethics in Entrepreneurship and Technology, 2023 Purpose – Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias in AI-enabled ERP software customization.
Sudhaman Parthasarathy, S.T. Padmapriya
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Causes and Countermeasures of Algorithmic Bias and Health Inequity [PDF]
Zhongguo quanke yixue, 2023 With the development of information technology, artificial intelligence shows great potentials for clinical diagnosis and treatment. Nevertheless, bias in algorithms derived by artificial intelligence can lead to problems such as unequal distribution of ...
CHEN Long, ZENG Kai, LI Sha, TAO Lu, LIANG Wei, WANG Haocen, YANG Rumei
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Algorithmic fairness in computational medicine
EBioMedicine, 2022 Summary: Machine learning models are increasingly adopted for facilitating clinical decision-making. However, recent research has shown that machine learning techniques may result in potential biases when making decisions for people in different ...
Jie Xu +6 more
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Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017 Algorithmic bias presents a difficult challenge within Information Retrieval. Long has it been known that certain algorithms favour particular documents due to attributes of these documents that are not directly related to relevance. The evaluation of bias has recently been made possible through the use of retrievability, a quantifiable measure of bias.
Wilkie, Colin, Azzopardi, Leif
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Algorithmic bias and Māori [PDF]
He Rourou, 2021 on algorithmic bias and Māori with Joni Angeli-Gordon (Ngāpuhi, Ngāti Whātua, Te Roroa).
Sara Stratton, Joni Angeli-Gordon
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