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Prompting marks a paradigmatic shift in how we engage with artificial intelligence—transforming static interfaces into dynamic conversations, reshaping the relationship between user intent, system behavior, and knowledge production. This book invites readers into...
How can we teach machine learning to identify causal patterns in data? This book explores the very notion of “causality”, identifying from a naturalistic and evolutionary perspective how living systems deal with causal relationships. At the same time, using this...
Why AI does not include gender in its agenda? The role of gender in AI, both as part of the community of agents creating such technologies, as well as part of the contents processed by such technologies is, by far, conflictive. Women have been, again, obliterated by...
This interdisciplinary volume gathers selected, refereed contributions on various aspects of public health from several disciplines and research fields, including the philosophy of science, epidemiology, statistics and ethics. The contributions were originally presented...
This edited volume is about how unprejudiced approaches to real human cognition can improve the design of AI. It covers many aspects of human cognition and across 12 chapters the reader can explore multiple approaches about the complexities of human cognitive skills and...
This book analyzes the origins of statistical thinking as well as its related philosophical questions, such as causality, determinism or chance. Bayesian and frequentist approaches are subjected to a historical, cognitive and epistemological analysis, making it possible...
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