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Elham Albaroudi, Taha Mansouri and Ali Alameer
The study comprehensively reviews artificial intelligence (AI) techniques for addressing algorithmic bias in job hiring. More businesses are using AI in curriculum vitae (CV) screening. While the move improves efficiency in the recruitment process, it is...
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Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes and Laurent Risser
Automatic recommendation systems based on deep neural networks have become extremely popular during the last decade. Some of these systems can, however, be used in applications that are ranked as High Risk by the European Commission in the AI act?for ins...
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Laurent Risser, Agustin Martin Picard, Lucas Hervier and Jean-Michel Loubes
The problem of algorithmic bias in machine learning has recently gained a lot of attention due to its potentially strong impact on our societies. In much the same manner, algorithmic biases can alter industrial and safety-critical machine learning applic...
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Luke Balcombe and Diego De Leo
There are positives and negatives of using YouTube in terms of loneliness and mental health. YouTube?s streaming content is an amazing resource, however, there may be bias or errors in its recommendation algorithms. Parasocial relationships can also comp...
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Wonhyuk Cho, Seeyoung Choi and Hemin Choi
The advancement of data technology such as machine learning and artificial intelligence has broadened the scope of human resources (HR) analytics, commonly referred to as ?people analytics.? This field has seen significant growth in recent years as organ...
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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Rodrigo M. Peixoto, Guilherme A. S. Guimarães, Gustavo O. R. Cruz, Maira M. Araujo, Lucas L. Santos, Marco A. S. Cruz, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. S. Nascimento
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This study examines ...
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Ivan G. Ivanov, Yordan Kumchev and Vincent James Hooper
Stroke is a major public health issue with significant economic consequences. This study aims to enhance stroke prediction by addressing imbalanced datasets and algorithmic bias. Our research focuses on accurately and precisely detecting stroke possibili...
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Juliana Castaneda, Assumpta Jover, Laura Calvet, Sergi Yanes, Angel A. Juan and Milagros Sainz
Are algorithms sexist? This is a question that has been frequently appearing in the mass media, and the debate has typically been far from a scientific analysis. This paper aims at answering the question using a hybrid social and technical perspective. F...
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Haojing Shen, Haksu Lee and Dong-Jun Seo
Kalman filter (KF) and its variants and extensions are wildly used for hydrologic prediction in environmental science and engineering. In many data assimilation applications of Kalman filter (KF) and its variants and extensions, accurate estimation of ex...
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Norah Alshareef, Xiaohong Yuan, Kaushik Roy and Mustafa Atay
In biometric systems, the process of identifying or verifying people using facial data must be highly accurate to ensure a high level of security and credibility. Many researchers investigated the fairness of face recognition systems and reported demogra...
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