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Approaches to fair and ethical AI have recently fell under the scrutiny of the emerging, chiefly qualitative, field of critical data studies, placing emphasis on the lack of sensitivity to context and complex social phenomena of such…
Biased news reporting poses a significant threat to informed decision-making and the functioning of democracies. This study introduces a novel methodology for scalable, minimally biased analysis of media bias in political news. The proposed…
Artificial Intelligence (AI) is revolutionizing assistive technologies. It offers innovative solutions to enhance the quality of life for individuals with visual impairments. This review examines the development, applications, and impact of…
Successful deployment of artificial intelligence (AI) in various settings has led to numerous positive outcomes for individuals and society. However, AI systems have also been shown to harm parts of the population due to biased predictions.…
Artificial intelligence (AI) is increasingly being adopted in most industries, and for applications such as note taking and checking grammar, there is typically not a cause for concern. However, when constitutional rights are involved, as…
Artificial Intelligence (AI) is an important driving force for the development and transformation of the financial industry. However, with the fast-evolving AI technology and application, unintentional bias, insufficient model validation,…
Artificial Intelligence has the potential to exacerbate societal bias and set back decades of advances in equal rights and civil liberty. Data used to train machine learning algorithms may capture social injustices, inequality or…
From massive face-recognition-based surveillance and machine-learning-based decision systems predicting crime recidivism rates, to the move towards automated health diagnostic systems, artificial intelligence (AI) is being used in scenarios…
As artificial intelligence (AI) systems become more prevalent, ensuring fairness in their design becomes increasingly important. This survey focuses on the subdomains of social media and healthcare, examining the concepts of fairness,…
Artificial intelligence (AI) holds great promise for transforming healthcare. However, despite significant advances, the integration of AI solutions into real-world clinical practice remains limited. A major barrier is the quality and…
Recently, the research community of computerized medical imaging has started to discuss and address potential fairness issues that may emerge when developing and deploying AI systems for medical image analysis. This chapter covers some of…
Given that there are a variety of stakeholders involved in, and affected by, decisions from machine learning (ML) models, it is important to consider that different stakeholders have different transparency needs. Previous work found that…
Intelligent systems for the annotation of media content are increasingly being used for the automation of parts of social science research. In this domain the problem of integrating various Artificial Intelligence (AI) algorithms into a…
The growing adoption of algorithm-powered tools in journalism enables new possibilities and raises many concerns. One way of addressing these concerns is by integrating journalistic practices and values into the design of algorithms that…
The advancement of artificial intelligence has led to its application in many areas, including news media, which makes it crucial to understand public reception of AI-generated news. This preregistered study investigates (i) the perceived…
As Artificial Intelligence (AI) increasingly influences decisions in critical societal sectors, understanding and establishing causality becomes essential for evaluating the fairness of automated systems. This article explores the…
The extensive adoption of business analytics (BA) has brought financial gains and increased efficiencies. However, these advances have simultaneously drawn attention to rising legal and ethical challenges when BA inform decisions with…
Declining newspaper revenues prompt local newsrooms to adopt automation to maintain efficiency and keep the community informed. However, current research provides a limited understanding of how local journalists work with digital data and…
The problem of algorithmic bias in machine learning has gained a lot of attention in recent years due to its concrete and potentially hazardous implications in society. In much the same manner, biases can also alter modern industrial and…
With the widespread use of AI systems and applications in our everyday lives, it is important to take fairness issues into consideration while designing and engineering these types of systems. Such systems can be used in many sensitive…