his paper introduces a first approach to miscomputations for data-driven systems. First, we establish an ontology for data-driven learning systems and categorize various computational errors based on the Levels of Abstraction ontology. Next, we consider computational errors which are associated with users’ evaluation and requirements and consider the user level ontology, identifying two additional types of miscomputation.
A Philosophical Framework for Data-Driven Miscomputations
Alessandro Buda;Giuseppe Primiero
2025-01-01
Abstract
his paper introduces a first approach to miscomputations for data-driven systems. First, we establish an ontology for data-driven learning systems and categorize various computational errors based on the Levels of Abstraction ontology. Next, we consider computational errors which are associated with users’ evaluation and requirements and consider the user level ontology, identifying two additional types of miscomputation.File in questo prodotto:
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