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Abstract Personal data are produced through our daily interactions with digital technologies like search engines, social media, and online shopping, and is often referred to as our “digital exhaust.” It has been characterized as the key resource or asset for our economies in the 21st century....
Abstract Efforts to address algorithmic harms have gathered particular steam over the last few years. One area of proposed opportunity is the notion of an “algorithmic audit,” specifically an “internal audit,” a process in which a system’s developers evaluate its construction and likely...
Abstract Through a critical analysis of recent developments in the theory and practice of data science, including nascent feminist approaches to data collection and analysis, this commentary aims to signal the need for a transnational feminist orientation towards data science. I argue that while...
Abstract Machine learning systems are making considerable inroads in society owing to their ability to recognize and predict patterns. However, the decision-making logic of some widely used machine learning models, such as deep neural networks, is characterized by opacity, thereby rendering them...
Abstract With the surge in the number of data and datafied governance initiatives, arrangements, and practices across the globe, understanding various types of such initiatives, arrangements, and their structural causes has become a daunting task for scholars, policy makers, and the public. This...
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