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Encounters with data and AI require contending with the uncertainties of systems that are most often understood through their inputs and outputs. Storytelling is one way to reckon with and […]
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The prevalence and technical relevance of machine learning algorithms have increased over the years, making predictive decisionmaking tools part of the everyday lives of online users. Today, it is harder […]
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The construction of authentic-feeling yet untrue information, content, experiences, and relations is central to successful mis/disinformation campaigns. The most outrageous lies can catalyze opinions, behaviours and actions–as long as they […]
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Efforts to promote equitable public policy with algorithms appear to be fundamentally constrained by the “impossibility of fairness” (an incompatibility between mathematical definitions of fairness). This technical limitation raises a […]
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A Primer on AI in/from the Majority World is a curated collection of over 160 thematic works that serve as pathways to explore the presence of artificial intelligence and technology […]
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Connie is Researcher-at-Large for Hacks/Hackers and leads the _Analysis and Response Toolkit for Trust (ARTT)_ project (artt.cs.washington.edu) and _News Quality Initiative_ (newsq.net). She is currently focused upon news and information […]
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In this paper, we present new empirical evidence to demonstrate the near impossibility for existing machine learning content moderation methods to keep pace with, let alone stay ahead of, hateful […]
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Claes De Vreese is a Distinguished University Professor of AI & Society at the University of Amsterdam with a special focus on AI, media, and democracy. He also holds the […]
