This article provides a comprehensive overview of the fairness issues in artificial intelligence
(AI) systems, delving into its background, definition, and development process. The article …

In the last few years, we have witnessed a surge in scholarly interest and scientific evidence
of how algorithms can produce discriminatory outcomes, especially with regard to gender …

Human-AI decision making is becoming increasingly ubiquitous, and explanations have
been proposed to facilitate better Human-AI interactions. Recent research has investigated …

Fairness is central to the ethical and responsible development and use of AI systems, with a
large number of frameworks and formal notions of algorithmic fairness being available …

This paper presents an intuitive explanation about why and how Rawlsian Theory of Justice
(Rawls in A theory of justice, Harvard University Press, Harvard, 1971) provides the …

The term Fairness is used in the field of Machine Learning to refer to a suite of evaluation
techniques, measures, and process adjustments focused on the reduction of bias in …

O texto apresenta reflexões sobre os princípios da flexibilidade educacional e sua
repercussão na qualidade de propostas de ensino-aprendizagem da Educação a Distância …

The Machine learning widespread adoption has inadvertently led to the amplification of
societal biases and discrimination, with many consequential decisions now influenced by …

In the era of data-driven decision-making, ensuring fairness and equality in machine
learning models has become increasingly crucial. Multiple fairness definitions have been …

As AI-based decision systems proliferate, their successful operationalization requires
balancing multiple desiderata: predictive performance, disparity across groups …