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(Some) algorithmic bias as institutional bias
In this paper I argue that some examples of what we label ‘algorithmic bias’ would be better understood as cases of institutional bias. Even when...
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A Genealogical Approach to Algorithmic Bias
The Fairness, Accountability, and Transparency (FAccT) literature tends to focus on bias as a problem that requires ex post solutions (e.g. fairness...
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Algorithmic bias, generalist models, and clinical medicine
The technical landscape of clinical machine learning is shifting in ways that destabilize pervasive assumptions about the nature and causes of...
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Assembled Bias: Beyond Transparent Algorithmic Bias
In this paper we make the case for the emergence of novel kind of bias with the use of algorithmic decision-making systems. We argue that the...
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Towards a holistic view of bias in machine learning: bridging algorithmic fairness and imbalanced learning
Machine learning (ML) is playing an increasingly important role in rendering decisions that affect a broad range of groups in society. This posits...
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Identifying and Mitigating Algorithmic Bias in Student Emotional Analysis
Algorithmic bias in educational environments has garnered increasing scrutiny, with numerous studies highlighting its significant impacts. This...
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Modeling algorithmic bias: simplicial complexes and evolving network topologies
Every day, people inform themselves and create their opinions on social networks. Although these platforms have promoted the access and dissemination...
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Algorithmic Bias in Education
In this paper, we review algorithmic bias in education, discussing the causes of that bias and reviewing the empirical literature on the specific...
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Mitigating Algorithmic Bias with Limited Annotations
Existing work on fairness modeling commonly assumes that sensitive attributes for all instances are fully available, which may not be true in many...
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Algorithmic Bias and Risk Assessments: Lessons from Practice
In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for...
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MinMax fairness: from Rawlsian Theory of Justice to solution for algorithmic bias
This paper presents an intuitive explanation about why and how Rawlsian Theory of Justice (Rawls in A theory of justice, Harvard University Press,...
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Disability, fairness, and algorithmic bias in AI recruitment
While rapid advances in artificial intelligence (AI) hiring tools promise to transform the workplace, these algorithms risk exacerbating existing...
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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization
The increasingly common use of neural network classifiers in industrial and social applications of image analysis has allowed impressive progress...
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Fourth International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2023)
Creating search and recommendation models responsibly requires monitoring more than just effectiveness and efficiency. Before moving these models...
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Representation-Induced Algorithmic Bias
In conceiving of autonomous agents able to employ adaptive cooperative behaviours we identify the need to effectively assess the equivalence of agent...
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Analysing Co** Strategies of Teenage Girls Towards Instagram’s Algorithmic Bias
Social media platforms encourage connection, community, and expression, but have also been associated with negative consequences like social...
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Bias and the Web
Bias is everywhere, sometimes blatantly explicit, but most of the time it’s hidden, as it often arises from that which is missing, the gaps in our...
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Algorithmic Bias and Fairness in Case-Based Reasoning
Algorithmic bias due to underestimation refers to situations where an algorithm under-predicts desirable outcomes for a protected minority. In this...
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Algorithmic evidence in U.S criminal sentencing
The use of automated risk assessment tools to predict a defendant’s risk of recidivism is necessarily unfair. There is a tradeoff between equal...
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Algorithmic Fairness
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence (AI) and machine learning...