Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic bias can be handled (...) more or less independently by technical experts who specialize in XAI methods. Drawing on resources from feminist epistemology, we show why technical XAI is mistaken. Specifically, we demonstrate that the proper detection of algorithmic bias requires relevant interpretive resources, which can only be made available, in practice, by actively involving a diverse group of stakeholders. Finally, we suggest how feminist theories can help shape integrated XAI: an inclusive social-epistemic process that facilitates the amelioration of algorithmic bias. (shrink)

1. Biomedical sciences are fast-growing fields with unprecedented speed of research outputs, especially in the quantities of papers. Philosophers aiming to study ongoing biomedical changes face cha...

Scientonomy is the field that aims to develop a descriptive theory of the actual process of scientific change (Barseghyan, 2015). Scientometrics is the field that aims to employ statistical methods to investigate the quantitative features of scientific research, especially the impact of scientific articles and the significance of scientific citations (Leydesdorff & Milojević, 2013). In this paper, we aim to illustrate how to methodologically integrate scientonomy with scientometrics to investigate both qualitative and quantitative changes of a scientific community. We will (...) use a case study to achieve our aim. The case study is about a scientific community studying a physiological phenomenon called heart-rate variability (HRV). Moreover, we will argue that this methodological integration outperforms cases in which researchers only employ the resources from one of the two fields. (shrink)

This paper aims to address some methodological issues related to case-based research in the philosophy of contemporary sciences. We focus on the selection processes by which philosophers pick or generate a particular set of papers to conduct their case-based research. We illustrate how to use various quantitative and qualitative methods to improve the epistemic features of the selection processes, and help generate some potential case-based hypotheses for further philosophical investigation.